EP4314344A1 - Genomic predictor of outcome in cancer - Google Patents

Genomic predictor of outcome in cancer

Info

Publication number
EP4314344A1
EP4314344A1 EP22713432.7A EP22713432A EP4314344A1 EP 4314344 A1 EP4314344 A1 EP 4314344A1 EP 22713432 A EP22713432 A EP 22713432A EP 4314344 A1 EP4314344 A1 EP 4314344A1
Authority
EP
European Patent Office
Prior art keywords
expression
genes
level
timp2
myb
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP22713432.7A
Other languages
German (de)
French (fr)
Inventor
Anna BIGAS SALVANS
Lluis ESPINOSA BLAY
Teresa LOBO JARNE
Laura SOLÉ FONT
Beatriz Bellosillo Paricio
Mar IGLESIAS COMA
Marta GUIX ARNAU
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Fundacio Institut Mar dInvestigacions Mediques IMIM
Consorcio Centro de Investigacion Biomedica en Red MP
Original Assignee
Fundacio Institut Mar dInvestigacions Mediques IMIM
Consorcio Centro de Investigacion Biomedica en Red MP
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fundacio Institut Mar dInvestigacions Mediques IMIM, Consorcio Centro de Investigacion Biomedica en Red MP filed Critical Fundacio Institut Mar dInvestigacions Mediques IMIM
Publication of EP4314344A1 publication Critical patent/EP4314344A1/en
Pending legal-status Critical Current

Links

Classifications

    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/112—Disease subtyping, staging or classification
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • the present invention relates to the field of Medicine, particularly to cancer and more particularly to colorectal cancer, specifically to a new method for predicting the outcome of cancer.
  • the method has potential applications in the clinical management of cancer patients in terms of medical treatment.
  • CT Chemotherapy
  • SASP senescence-associated-secretory-phenotype
  • senescent cells may contribute to cancer progression and disease recurrence (e.g., after senescent cell reactivation) (Saleh et al., 2019). Therefore, even using chemotherapy in combination with other approaches, such as surgical removal of the tumor, not all cancer patients are cured.
  • CRC colorectal cancer
  • 5-FU 5-fluorouracil
  • Iri irinotecan
  • CRC remains the second leading cause of cancer-related death.
  • CT metastasis and chemotherapy
  • the inventors have found valuable informative markers about the prediction of the outcome of cancer.
  • the inventors have found that when a subject has a signature comprising differential expression of genes form table 1 , in particular, when the subject presents upregulation of the expression of certain genes of table 2 in combination with the downregulation of certain genes of table 3, then the subject has a bad prediction for the outcome (bad prognosis).
  • the inventors have identified that the genetic signature that was acquired by the TQL cells in vitro when using low doses of chemotherapy also predicted cancer outcome in cancer patients including patients which did not received yet chemotherapy (exemplified for CRC and demonstrated in three cohort of patients, see examples 3-5).
  • the inventors have demonstrated that ratio between the level of expression of genes of table 2 and genes of table 3 provide valuable information that predicted poor disease outcome of cancer patients (see example 5).
  • the inventors have found a signature useful for the prediction of the outcome of cancer, e.g., CRC, for the determination of the efficacy of an anti-cancer chemotherapy and for deciding or recommending a medical regime to a subject with cancer (e.g., with CRC).
  • CRC cancer-specific hormone
  • the first aspect of the invention refers to an in vitro method for the prediction of the outcome in a subject suffering cancer, the method comprising the step of: a. determining in an isolated sample of a subject the level of expression of
  • a second aspect of the invention refers to an in vitro method to determine the efficacy of an anti-cancer chemotherapy in a subject suffering cancer comprising the steps of:
  • step (a1) at least one gene selected from table 2 or any combination thereof, and (a2) at least one gene selected from table 3 or any combination thereof; and b) determining a ratio between the level of expression of the gene(s) determined in step (a1) and the gene(s) determined in step (a2) before and after starting the anti-cancer chemotherapy, wherein, if the ratio of gene expression after starting the anti-cancer chemotherapy is higher than or equal to the ratio obtained before starting the anti-cancer chemotherapy, this is indicative of the inefficiency of the anti cancer chemotherapy.
  • a third aspect of the invention refers to an in vitro method for deciding or recommending a medical regime to a subject suffering cancer the method comprising:
  • a fourth aspect of the invention refers to a use of a kit for predicting the outcome in a subject suffering cancer as defined in the method of the first aspect of the invention, or for determining the efficacy of an anti-cancer chemotherapy in a subject suffering cancer as defined in the second aspect of the invention, or for deciding or recommending a medical regime to a subject suffering cancer as defined in the method of the third aspect of the invention, wherein the kit comprises means for determining the level of expression of at least one of the genes selected from table 2 and at least one of the genes selected from table 3 or any combinations thereof.
  • a fifth aspect of the invention refers to a combined use of an expression product of at least one gene selected from table 2 and at least one gene selected form table 3 or any combination thereof, as a marker of prediction of progression of cancer, or of determining the efficacy of an anti-cancer chemotherapy in a subject suffering cancer, or of deciding or recommending a medical regime in a subject suffering cancer.
  • Fig. 1 Shows that CT-induced quiescent cells acquired a fetal intestinal stem cells signature: (A) western blotting (WB) analysis of control (untreated) and treated PD05 collected at the indicated time points after 5FU+lri treatment. (B) RT-qPCR analysis of selected p53 target genes from control (untreated) and IC20- treated PD05 cells.
  • WB western blotting
  • B RT-qPCR analysis of selected p53 target genes from control (untreated) and IC20- treated PD05 cells.
  • Fig.2. Shows that CT-induced quiescent cells displayed a fetal intestinal stem cell signature that was TP53 dependent:
  • the 88 remaining genes are indicated as white dots (within the upper right quadrant (genes upregulated) and the lower left quadrant (genes downregulated)).
  • B RT-qPCR analysis of normalized expression of selected 28up+8down-felSC signature genes in control (untreated) and treated PD05 as indicated.
  • C WB analysis of several feISC genes of control and treated PD05 collected at the indicated time points (in hours) after 5FU+lri treatment.
  • D, E RT-qPCR analysis of normalized relative expression of selected 28up+8down-felSC signature genes in control (untreated) and treated
  • E the TP53 mutant PD04.
  • Fig. 3 Identification of a fetal ISC signature with prognostic value in CRC: Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 28up/8down-felSC signature selected according to the "Marisa”, “Jorissen” and “TCGA” colorectal cancer databases.
  • Fig. 4 Kaplan-Meier curves representing the disease-free survival of patient groups from (A) stage II and (B) stage II and III from Marisa colorectal cancer database, selected according to their cluster analysis of the 28up/8down-felSC signature. Hazard ratio (HR).
  • Fig. 5 Kaplan-Meier curves representing the disease-free survival of patient groups classified according to their cluster analysis of the 28up+8down-felSC signature for patient groups from TP53 wild type ("P53 WT”) and TP53 mutant (P53 MUT) in (A) Marisa and (B) TCGA colorectal cancer databases.
  • Fig. 6 Kaplan-Meier representation of disease-free survival probability over time of Marisa patient's tumors previously categorized as CMS4 and classified according to their cluster analysis of the 28up+8down-felSC signature.
  • Fig. 7 Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 8up/8down-felSC signature according for the "Marisa”, “Jorissen” and “TCGA” colorectal cancer databases.
  • Fig. 8 Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 8up/8down-felSC signature of (A) stage III and (B) stage II and III "Marisa” colorectal database, selected according to their unsupervised hierarchical cluster analysis.
  • Fig. 9. Shows the optimized 5up/3down-felSC signature: (A) RT-qPCR analysis of selected fetal genes from control (untreated) and IC20-treated PD05 cells. Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 5up/3down-felSC signature (B) and 5up/4down signature (C) according for the "Marisa”, “Jorissen” and "TCGA” colorectal cancer databases.
  • Fig. 10 Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 5up/3down-felSC signature of (A) stage II and (B) stage II and III "Marisa” colorectal database, selected according to their unsupervised hierarchical cluster analysis.
  • Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 5up/4down-felSC signature of (C) stage II and (D) stage II and III "Marisa” colorectal database selected according to their unsupervised hierarchical cluster analysis.
  • Fig. 11 Shows that the acquisition of feISC by CT treatments was dependent of YAP1 activation:
  • A WB analysis of p53 and YAP1 protein levels in control and TP53-depleted PD05 KO# 3 cells collected after 72 hours of 5-FU+lri. treatment.
  • B WB analysis of TP53 wild type (HCT116 and Ls174T) and TP53 mutant (SW480 and HT29-M6) colorectal cancer cell lines untreated ("-") and collected after 72 hours of 5-FU+iri. Treatment ("+”).
  • C RT-qPCR analysis of normalized relative expression of selected 28up-felSC signature genes in control (untreated) and treated PD05 with 5-FU+lri.
  • Fig. 12 Kaplan-Meier representation of disease-free survival probability over time for patients from TCGA Stage I with high or low expression of the reduced signatures
  • A 5up/4down TIMP2, TSPAN4, TUBB6, MRAS and ARL4C up and MYB, AGMAT, CDX and HOOK1 down.
  • B rA 5up+3down.
  • C rG 28up+8down.
  • D 8up/8down.
  • Fig. 13 Kaplan-Meier representations of disease-free survival probability over time for patients with high or low expression of the reduced signatures selected according to the "Marisa”, “Jorissen” and “TCGA” colorectal cancer databases.
  • A rA: TIMP2, TSPAN4, TUBB6, MRAS, ARL4C up and MYB, AGMAT, CDX down.
  • B rB: TIMP2, TSPAN4 up and MYB, AGMAT down.
  • C rC: TIMP2, TUBB6 up and MYB, HOOK1 down
  • D rD: TIMP2, TSPAN4, TUBB6 up and MYB, HOOK down.
  • rE TIMP2, TUBB6 up and MYB, AGMAT, HOOK1 down.
  • F rF: TIMP2, TSPAN4, TUBB6 up and MYB, HOOK, AGMAT down.
  • G rG 28up+8down.
  • H rH: TIMP2, TSPAN4 up and MYB down.
  • I rl: TIMP2 up and MYB, AGMAT down.
  • J rJ: TIMP2, TUBB6 up and MYB down.
  • K rK: TIMP2 up and MYB, HOOK down.
  • L rL: TIMP2, TUBB6, TSPAN4 up and CDX1 down.
  • (M) rM TIMP2, TSPAN4 up and CDX1 down;
  • Fig. 14 Kaplan-Meier representations of disease-free survival probability over time for patients classified according to a gene set enrichment score, of the reduced signatures, selected by combining the "Marisa”, “Jorissen” and “TCGA” colorectal cancer databases, d are subset of up genes and c2 are subset of down genes from the reduced signatures. Quartiles were used to define high and low groups.
  • B rB TIMP2, TSPAN4 and MYB, AGMAT.
  • C rC TIMP2, TUBB6 and MYB, HOOK1.
  • the present invention refers to an in vitro method for the prediction of the outcome in a subject suffering cancer, the method comprising the step of determining in an isolated sample from a subject the level of expression of at least one gene of Table 1, for example, the method comprising the step of determining in an isolated sample from a subject the level of expression of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
  • determining the level of expression of at least one gene e.g., 1, 2, 3, 4, 5,
  • prognosis is the natural evolution of the disease in terms of survival if there is no treatment in between.
  • bad outcome refers to recurrence, relapse, or progression of a cancer in a subject previously identified with the cancer.
  • good outcome refers to no recurrence, or no relapse of the cancer after at least 4 years of follow-up in a subject previously identified with cancer. Bad outcome is, therefore, bad prognosis and good outcome is good prognosis.
  • genes cited herein in tables 1, 2 and 3 are described by their number identifier in the public data base Ensembl (European Molecular Biology Laboratory-European Bioinformatics Institute, EMBL-EBI) and Entrez ID from the National Center for Biotechnology Information (NCBI) at day 25 November 2020. Moreover, for the genes indicated in tables 4 and 5 GenBank® (NCBI) and UniProt (EMBL-EBI) references are provided for expression products of the genes (see the material and method section below) (reference number at day 25 November 2020).
  • the "feISC signature” as described herein is characterized by the detection of at least one gene of Table 1; e.g., the upregulation of at least one gene of table 2 and the down regulation of at least one gene of table 3; e.g., the upregulation of at least one gene of table 4 and the down regulation of at least one gene of table 5; e.g., the "28up/8down” signature, or the “8up/8down” signature, or the "5up/3down” signature explained in the present invention.
  • the first aspect of the invention refers to an in vitro method for the prediction of the outcome in a subject suffering cancer, the method comprising the step of: a. determining in an isolated sample of a subject the level of expression of
  • the method for the prediction of the outcome further comprises the step: b) determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2) (ratio level of expression of the genes determined in step (a1):level of expression of the genes determined in step (a2)).
  • the method for the prediction of the outcome further comprises the step: b. determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2) (ratio level of expression of the genes determined in step (a1):level of expression of the genes determined in step (a2)); wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is, for example, higher than 1, for example is higher or equal to 1.01, and the subject is considered as having good outcome if the ratio obtained in step (b) is for example, lower than 1, for example, is lower or equal to 0.99.
  • step (b) It has been found that the risk of a bad outcome is directly proportional to the increase of the ratio obtained in step (b). This ratio can be considered as a hazard ratio, where patients scoring higher have a worst prognosis.
  • the method for the prediction of the outcome in a subject suffering cancer comprises the step: b. comparing the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of expression of the gene(s) of table 2 is higher, than the corresponding reference value, and wherein the level of expression of the gene(s) of table 3 is lower than the corresponding reference value.
  • the method comprising the determination of the level of expression product of at least 1, 2, 3,
  • the gene(s) form table 2 is(are) selected from the group consisting of: TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, RHOD, and any combinations thereof.
  • the gene(s) form table 3 is(are) selected from the group consisting of: MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5, SLC27A2 genes, and any combinations thereof.
  • the in vitro method for the prediction of the outcome in a subject suffering cancer comprising determining in an isolated sample of a subject the level of expression of at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 genes) selected from the group consisting of: TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, RHOD (genes of table 4) and any combination thereof; and the level of expression of at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 genes) selected from the group
  • An embodiment of the first aspect of the present invention refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein in step (a) it is determined the level of expression of:
  • (a1) at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 gene(s)) selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR,
  • gene e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 gene(s) selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR,
  • gene e.g., 1, 2, 3, 4, 5, 6, 7, 8 gene(s)
  • the method for the prediction of the outcome in a subject suffering colorectal cancer comprises the steps: a. determining in an isolated sample of a subject the level of expression of:
  • (a1) at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 gene(s)) selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN,
  • gene e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 gene(s) selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1,
  • the method comprises an alternative step (b) which comprises comparing the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression of any of the gene(s)of step (a1) is higher (e.g., at least 2-fold higher), than the corresponding reference value, and wherein the level of the expression for each one of the genes of step (a2) is lower (e.g., at least 2-fold lower) than the corresponding reference value.
  • step (b) which comprises comparing the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression of any of the gene(s)of step (a1) is higher (e.g., at least 2-fold higher), than the corresponding reference value, and wherein the level of the expression for each one of the genes of step (a2) is lower (e.g., at least 2-fold lower) than the corresponding reference value.
  • An embodiment of the first aspect of the present invention refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC) wherein in step (a) it is determined the level of expression of:
  • An embodiment of the first aspect of the present invention refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC) comprising the following steps: a. determining in an isolated sample of a subject the level of expression of (a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes (e.g. in combination with at least one of the other genes of table 4, e.g., in combination with 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 or 23 gene(s) of table 4); and
  • step (a2) at least each one of MYB, AGMAT and CDX1 genes (e.g. in combination with at least one of the other genes of table 5, e.g. with 1, 2, 3, 4 or 5 gene(s) of table 5); and b) determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2); wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99, 0.95 or 0.90.
  • This embodiment can comprise an alternative step (b) which compares the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes (e.g., also in combination with any other gene of table 4) is higher (e.g., at least 2-fold higher) than the corresponding reference value, and wherein the level of the expression of each one of MYB, AGMAT and CDX1 genes (e.g. also in combination with any other gene of table 5, is lower (e.g., at least 2-fold lower) with respect to the corresponding reference value.
  • step (b) which compares the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes (e.g., also in combination with any other gene of table 4) is higher
  • An embodiment of the first aspect of the present invention refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein in step (a) it is determined the level of expression of: (a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes (e.g., in combination with at least one of the other genes of table 4, e.g., in combination with 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 gene(s) of table 4); and (a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes.
  • CRC colorectal cancer
  • An embodiment of the first aspect of the present invention refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), the method comprising the steps of: a. determining in an isolated sample of a subject the level of expression of
  • step (a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; and b. determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2); wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99, 0.95 or 0.90.
  • This embodiment can comprise an alternative step (b) which compares the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1, and TPM2 genes (e.g., also in combination with any other gene of table 4) is higher (e.g., at least 2-fold higher) than the corresponding reference value, and wherein the level of the expression of each one of MYB,
  • An embodiment of the first aspect of the present invention refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), the method comprising the step of: a. determining in an isolated sample of a subject the level of expression of
  • An embodiment of the first aspect of the present invention refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), the method comprising the steps of: a. determining in an isolated sample of a subject the level of expression of
  • step (a1) determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2); wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99, 0.95 or 0.90.
  • This embodiment can comprise an alternative step (b) which compares the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1,
  • SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2 and RHOD genes is higher (e.g., at least 2-fold higher), than the corresponding reference value, and wherein the level of the expression for each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes is lower (e.g., at least 2-fold lower) than the corresponding reference value.
  • step (a) contemplate determining in step (a) the level of expression of the following combinations of genes (reduced signatures): (a1) at least TIMP2 and TUBB6, and (a2) at least one gene selected from MYB,CDX1, HOOK1, and any combination thereof
  • the method comprises determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2) of the reduced signatures, wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99, 0.95 or 0.90.
  • step (b) may comprise comparing the level of the expression of each gene disclosed for the reduced signatures with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression for each one of the genes in (a1) is higher (e.g., at least 2-fold higher), than the corresponding reference value, and the level of the expression for each one of the genes in (a2) is lower (e.g., at least 2-fold lower) than the corresponding reference value.
  • step (b) comprises comparing the level of the expression of each gene determined in (a1) and (a2) with a corresponding reference value and, subsequently, determining a ratio between the level of expression of the genes determined in step (a1) as compared to their reference values and the genes determined in step (a2) as compared to their reference values, wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01 and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99.
  • step (b) comprises: (b1) calculating the mean relative expression of all the genes determined in (a1), (b2) calculating the mean relative expression of all the genes determined in (a2), and (b3) determining the ration between (b1) and (b2), i.e. (b1)/(b2).
  • the relative expression is understood as the level of expression of the gene in the sample with respect to its corresponding reference value. More particularly, the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99, 0.95 or 0.90.
  • An embodiment of the first aspect of the present invention refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein the method further comprises identifying the mutation status of TP53 gene (Gene ID: 7157) (ENSEMBL: ENSG0000014151 ), wherein the subject is considered as having bad outcome when the TP53 gene is the TP53 wild-type gene, or, alternatively, when the TP53 gene is a non-inactivating mutated TP53 (i.e., which does not lead to a loss of function of the p53).
  • This method can also comprise the detection of the p53 protein mutational status, wherein when functional p53 protein (i.e., a p53 WT or a p53 with non-inactivating mutation) is detected is indicative of the subject having bad outcome.
  • This method can also refer to the method wherein the subject is considered as having bad outcome when an inactivating TP53 mutation (i.e., which lead to a p53 with loss of function) it is present in a low percentage of tumoral cells.
  • An embodiment of the first aspect of the present invention optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein the subject has received anti-cancer chemotherapy.
  • CRC colorectal cancer
  • reference value in the context of the present invention is to be understood as a predefined level of expression product of the genes in a sample or group of samples. This value is used as a threshold to discriminate subjects wherein the condition to be analysed is present from those wherein such condition is absent.
  • the samples are taken from a well-defined control subject or group of control subjects having no cancer, e.g., no CRC.
  • the skilled person in the art, making use of the general knowledge is able to choose the subject or group of subjects more adequate for obtaining the reference value. Methods for obtaining the reference value from the group of subjects selected are well known in the state of the art.
  • the reference value is determined from a subject or group of subjects that do not suffer from cancer.
  • the reference value is determined from a healthy subject or group of healthy subjects.
  • the reference value is normal tissue, for example, adjacent normal tissue, from the same subject suffering the cancer (e.g., CRC).
  • the reference value is from a reference tumor (e.g., a CRC) that does not present the signature of the present invention.
  • the reference value is obtained from a group of CRC tumoral tissue samples. More particularly, the CRC tumoral tissue samples are from patients suffering colorectal cancer at the same stage as the patient whose prognosis is being determined.
  • An embodiment of the first aspect of the present invention refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein the reference value is the level of expression of each gene in colorectal cancer tissue from a patient whose tumor does not relapse in the 4 first years of follow-up.
  • CRC colorectal cancer
  • the expression “higher than a reference value” is understood as any increase in the level of expression product, for example at least 1.2-fold, or 1.5-fold increase of expression product with respect to the reference value. In particular embodiments, “higher than a reference value” is understood as at least 2-fold increase of expression product with respect to the reference value.
  • the expression “lower than a reference value” is understood as any decrease in the level of expression product, for example at least 1.2-fold, or 1.5-fold decrease of expression product with respect to the reference value. In particular embodiments, “lower than a reference value” is understood as at least 2-fold decrease of expression product with respect to the reference value.
  • the subject is considered as having bad cancer outcome if the level of expression of the gene(s) product(s) selected form table 2 or table 4 is at least 1.2-fold higher, 1.5-fold higher, 2-fold higher, 3-fold higher, 4-fold higher, 5-fold higher, 6-fold higher, 7-fold higher, 8-fold higher, 9-fold higher, or 10-fold higher with respect to a corresponding reference value; and/or wherein the level of expression of the gene(s) product(s) selected from table 3 or table 5 is lower, e.g.
  • the subject is considered as having good outcome if the level of expression of the gene(s) of table 2 or table 4 is equal or lower, than the corresponding reference value, and wherein the level of expression of the gene(s) of table 3 or table 5 is equal or higher than the corresponding reference value.
  • Another embodiment of the first aspect of the present invention refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein it compares the level of expression with a tumor that it is known to contain the signature of the present invention.
  • CRC colorectal cancer
  • a second aspect of the invention refers to an in vitro method to determine the efficacy (i.e., efficiency or effectiveness) of an anti-cancer chemotherapy in a subject suffering cancer comprising the steps of:
  • (a1) at least one gene selected from the group consisting of at least one gene selected from Table 2 (e.g., least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 17, 18, 17, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
  • Table 2 e.g., least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 17, 18, 17, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38,
  • (a2) at least one gene selected from Table 3 (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 17, 18, 17, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 gene(s)) in an isolated sample from the subject, and any combinations thereof;
  • Table 3 e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 17, 18, 17, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 gene(s)
  • step (b) ) optionally comprises determining a ratio between the level of expression of the gene(s) determined in step (a1) and the gene(s) determined in step (a2) before and after starting the anti-cancer chemotherapy, wherein, if the ratio of gene expression after starting the anti-cancer chemotherapy is higher than or equal to the ratio obtained before starting the anti-cancer chemotherapy this is indicative of the inefficiency of the anti cancer chemotherapy (thus, wherein, if the ratio of gene expression after starting the anti-cancer chemotherapy is lower than the ratio obtained before starting the anti-cancer chemotherapy this is indicative of the efficacy of the anti-cancer chemotherapy); alternatively, the efficacy of the anti-cancer chemotherapy can be performed by comparing the level of expression before and after starting the anti-cancer chemotherapy, wherein, if there is an increase between the level of the expression product of any gene of table 2 determined before starting the anticancer chemotherapy and there is a reduction between the level of the expression product of any gene of table 3 after starting the anticancer chemotherapy, this is indicative of the inefficiency of the
  • An anti-cancer chemotherapy is considered inefficient when the size of the tumor increases significantly (for example, a 20% or higher increase of its size in imaging tests) despite receiving the treatment.
  • An embodiment of the second aspect of the present invention refers to an in vitro method to determine the efficacy of an anti-cancer chemotherapy in a subject suffering colorectal cancer (CRC) comprising the steps of:
  • (a1) at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 gene(s)) selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD (genes of table 4) and any combination thereof; and
  • (a2) at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8 gene(s)) selected from the group consisting of: MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 (genes of table 5) and any combination thereof; or, alternatively,
  • step (b) can refer to comparing the level of the expression before and after starting the anti-cancer chemotherapy, wherein, if there is an increase between the level of the expression of any gene of table 4 (e.g., of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 or 23 gene(s)) determined after the initiation of the therapy in comparison with before starting the anti-cancer chemotherapy and there is a reduction between the level of the expression of any gene of table 5 (e.g., of 1, 2, 3, 4, 5, 6, 7 or 8 gene(s)) determined after in comparison with before starting the anti-cancer chemotherapy; or, alternatively, when there is an increase between the level of the expression of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes (e.g., also of any other gene of table 4) determined after in comparison with before starting the anti-cancer chemotherapy and there is a reduction between the level of expression of each one of MYB, AGMAT and CDX1 genes (e.g.,
  • CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes determined after in comparison with before starting the anti-cancer chemotherapy, this is indicative of the inefficiency of the anti-cancer chemotherapy.
  • Other embodiments of the second aspect of the invention contemplate determining in step (a) the level of expression of the following combinations of genes (reduced signatures):
  • the method comprises determining in a step b) a ratio between the level of expression of the gene(s) determined in step (a1) and the gene(s) determined in step (a2) before and after starting the anti-cancer chemotherapy, wherein, if the ratio of gene expression after starting the anti-cancer chemotherapy is higher than the ratio obtained before starting the anti-cancer chemotherapy this is indicative of the inefficiency of the anti-cancer chemotherapy.
  • step (b) can refer to comparing the level of the expression before and after starting the anti-cancer chemotherapy, wherein, if there is an increase between the level of the expression of each of the genes in (a1) determined after the initiation of the therapy in comparison with before starting the anti-cancer chemotherapy and there is a reduction between the level of the expression of each of the genes in (a2) determined after in comparison with before starting the anti-cancer chemotherapy, this is indicative of the inefficiency of the anti-cancer chemotherapy.
  • step (b) comprises determining a ratio between the level of expression of the genes determined in step (a1) after starting the anti-cancer chemotherapy as compared to their level of expression before the anti-cancer therapy and the genes determined in step (a2) after starting the anti-cancer chemotherapy as compared to their level of expression before the anti-cancer therapy, wherein anti-cancer chemotherapy is considered to be ineffective if the ratio is higher than or equal to 1.01.
  • step (b) comprises: (b1) calculating the mean relative expression of all the genes determined in (a1), (b2) calculating the mean relative expression of all the genes determined in (a2), and (b3) determining the ratio between (b1) and (b2), i.e. (b1)/(b2).
  • the relative expression is understood, in this case, for the second aspect of the invention, as the level of expression of the gene in a sample obtained from the patient after the anti-cancer treatment with respect to the level of expression of the same gene in a sample obtained from the patient before the anti-cancer treatment. More particularly, the anti-cancer therapy is considered to be ineffective if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22.
  • An embodiment of the second aspect of the present invention refers to the in vitro method to determine the efficacy of an anti cancer chemotherapy in a subject suffering colorectal cancer (CRC), wherein the method further comprises identifying the TP53 (Gene ID: 7157; ENSEMBL: ENSG0000014151; identifiers at day 25 November 2020) mutational status wherein when TP53 wild-type gene is determined, or, alternatively, when the TP53 gene is a non-inactivating mutated TP53 (i.e., which does not lead to a loss of function of the p53 protein) this is indicative of the inefficiency of the anti-cancer chemotherapy.
  • TP53 Gene ID: 7157; ENSEMBL: ENSG0000014151; identifiers at day 25 November 2020
  • This method can also comprise the detection of the p53 protein mutational status, wherein when functional p53 protein is detected is indicative of the inefficiency of the anti-cancer chemotherapy.
  • This method can also refer to the method wherein when an inactivating TP53 mutation it is present in a low percentage of tumoral cells, this is indicative of the inefficiency of the anti-cancer chemotherapy.
  • An embodiment of the second aspect of the present invention refers to the in vitro method to determine the efficacy of an anti cancer chemotherapy in a subject suffering cancer (e.g., CRC) wherein the time after starting the anti-cancer chemotherapy is at least after 4-6 cycles of chemotherapy treatment, for example, after 2-3 months after initiating the anti-cancer chemotherapy.
  • a subject suffering cancer e.g., CRC
  • the time after starting the anti-cancer chemotherapy is at least after 4-6 cycles of chemotherapy treatment, for example, after 2-3 months after initiating the anti-cancer chemotherapy.
  • An embodiment of the second aspect of the present invention refers to the in vitro method to determine the efficacy of an anti cancer chemotherapy in a subject suffering cancer (e.g., CRC) wherein the time after starting the anti-cancer chemotherapy is at any time after the completion of said chemotherapy treatment.
  • a subject suffering cancer e.g., CRC
  • the second aspect of the invention is also understood as an in vitro method to determine the efficacy of an anti-cancer chemotherapy in a subject suffering colorectal cancer (CRC) wherein in step (a) the determination of the level of expression in an isolated sample of a subject is performed comparing the level of expression in an intermediate time point during an anti-cancer chemotherapy and the level of expression in a posterior time point after starting said anti-cancer chemotherapy.
  • CRC colorectal cancer
  • the anti-cancer chemotherapy is selected from the group consisting of fluoropyrimidine (for example, 5-fluorouracile and/or capecitabine), oxaliplatin, irinotecan and any combination thereof, for example, 5-fluorouracile and irinotecan, for example, as commonly used to treat CRC patients.
  • fluoropyrimidine for example, 5-fluorouracile and/or capecitabine
  • oxaliplatin for example, 5-fluorouracile and irinotecan, for example, as commonly used to treat CRC patients.
  • the anticancer chemotherapy is combined with any chemotherapy of biological drug used to treat CRC patients, for example, is combined with an antiangiogenic drug (e.g., bevacizumab y aflibercept) and/or an EGFR inhibitor (e.g., cetuximab y panitumumab).
  • an antiangiogenic drug e.g., bevacizumab y aflibercept
  • an EGFR inhibitor e.g., cetuximab y panitumumab.
  • a third aspect of the invention refers to an in vitro method for deciding or recommending a medical regime to a subject suffering cancer the method comprising:
  • An embodiment of the third aspect of the present invention optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for deciding or recommending a medical regime to a subject suffering colorectal cancer (CRC) the method comprising:
  • the medical regime decided or recommended is chemotherapy (for example, FOLFOX4, mFOLFOX6, FOLFIRI, CAPOX, FLOX, or de Gramont regime) combined with a YAP1 inhibitor, e.g., porphyrin compounds such as Verteporfin®, protoporphyrin ix or hematoporphyrin; e.g., Verteporfin®; e.g., is 5FU and irinotecan combined with Verteporfin®.
  • a YAP1 inhibitor e.g., porphyrin compounds such as Verteporfin®, protoporphyrin ix or hematoporphyrin; e.g., Verteporfin®; e.g., is 5FU and irinotecan combined with Verteporfin®.
  • the medical regime decided or recommended is surgery, a different anti-cancer chemotherapy, a different chemotherapy regime using the same anti-cancer chemotherapy, radiation therapy, immunotherapy, targeted therapy hormone therapy or any combination thereof.
  • the anti-cancer treatment is selected from the above-mentioned options based on type and stage of cancer, the results of clinical trials as well as histopathologic findings.
  • the medical regime decided or recommended is not a senolytic drug.
  • the subject is suffering colorectal cancer at stages II or III.
  • the level of expression of the gene is determined by measuring or determining the amount of corresponding mRNA or protein (e.g., full-length protein product or a proteolytic fragment thereof), depending on the detection technique to be used.
  • Determining the amount of mRNA can be performed by any method known to the skilled person, provided that said method permits the detection and quantification of mRNA in a biological sample. Included among the examples of these procedures are PCR, quantitative real-time PCR (QPCR), multiplex PCR, NASBA, LCR, RT-PCR, RNA sequencing, array hybridization or "Northern” transfer, or combinations of these.
  • the level of expression of the gene is determined (quantified) by measuring the amount of mRNA by a nucleic acid amplification-based technique (e.g., PCR, RT-PCR, quantitative PCR (qPCR), or quantitative RT-PCR (qRT-PCR or RT-qPCR)).
  • a nucleic acid amplification-based technique e.g., PCR, RT-PCR, quantitative PCR (qPCR), or quantitative RT-PCR (qRT-PCR or RT-qPCR).
  • the level of expression of the gene is determined (quantified) by measuring the amount of mRNA by qRT-PCR.
  • the amount of mRNA for each one of the gene markers provided by the invention via a hybridization technique, employing oligonucleotide probes.
  • the method may be carried out by combining isolated mRNA with reagents to convert to cDNA according to standard methods well known in the art, treating the converted cDNA with amplification reaction reagents (such as cDNA PCR reaction reagents) in a container along with an appropriate mixture of nucleic acid primers; reacting the contents of the container to produce amplification products; and analyzing the amplification products to detect the presence of one or more of the cancer markers in the sample.
  • the analysis step may be further accomplished by quantitatively detecting the presence of polynucleotide cancer markers in the amplification product and comparing the quantity of marker detected against a panel of expected values for the known presence or absence of such markers in normal and malignant tissue derived using similar primers.
  • the present invention optionally requires performing a ratio between the level of expression of any gene of table 2 and of table 3; or, alternatively, a ratio between the level of expression of any gene of table 4 and of table 5; or, alternatively, a ratio between the level of expression of the genes of any gen of step (a1) and of step (a2) of the above-mentioned methods of the invention.
  • the ratio is performed by performing the arithmetic mean of the level of expression of a subset of genes of table 2 divided by the arithmetic mean of the level of expression of a subset of genes of table 3, or alternatively, by performing the arithmetic mean of the level of expression of a subset of genes of table 4 divided by the arithmetic mean of the level of expression of a subset of genes of table 5.
  • the present invention optionally requires comparing the level of expression of the genes with a reference value.
  • the reference value is obtained from a control subject or group of control subjects or is a normal tissue, for example, adjacent normal tissue from the same subject suffering the cancer (e.g., CRC) or is a reference tumor (e.g., a CRC) that does not present the signature of the present invention.
  • the skilled person may use any available method to establish the described comparison. For instance, as method of relative quantification, the 2-MCt of Livak and Schmittgen may be employed (Methods, 2001 vol. 25, issue 4, p.402-8).
  • microarrays are used which include one or more probes corresponding to one or more of biomarkers identified in Tables 1, 2, 3, 4 or 5.
  • This method results in the production of hybridization patterns of labeled target nucleic acids on the array surface.
  • the resultant hybridization patterns of labeled nucleic acids may be visualized or detected in a variety of ways, with the particular manner of detection selected based on the particular label of the target nucleic acid.
  • Representative detection means include scintillation counting, autoradiography, fluorescence measurement, calorimetric measurement, light emission measurement, light scattering, and the like.
  • the level of expression of the gene is determined by the detection and/or quantification of the protein, e.g., by a specific antibody or a fragment thereof able to bind to the target protein(s).
  • the expression product of the genes which is determined in the context of the present invention is the full-length protein encoded by the genes, or a fragment of said protein.
  • the level of the protein markers or fragments thereof is determined by a quantitative test selected from the group consisting of an immunological test, bioluminescence, fluorescence, chemiluminescence, electrochemistry and mass spectrometry.
  • the proteins and/or mRNAs to be determined are those shown in table 6 (identified with their GenBank® and/or UniProt reference number on day 25 November 2020).
  • the level of encoded protein or fragment thereof is detected by mass spectrometry, for example, by Shotgun Liquid Chromatography Mass Spectrometry (LC-MS/MS) or Multiple reaction monitoring (MRM) mass spectrometry, immunochemistry or by an immunoassay.
  • mass spectrometry for example, by Shotgun Liquid Chromatography Mass Spectrometry (LC-MS/MS) or Multiple reaction monitoring (MRM) mass spectrometry, immunochemistry or by an immunoassay.
  • immunochemistry refers to a variety of techniques for detecting antigens (in the present case any of the proteins encoded by the above genes or antigenic fragments thereof) in a sample by exploiting the principle of antibodies binding specifically to the target protein(s). Visualizing an antibody- antigen interaction can be then accomplished in a number of ways, usually by conjugating the antibody to an enzyme, such as peroxidase, that can catalyse a colour-producing reaction, or to a fluorophore, such as fluorescein or rhodamine.
  • an enzyme such as peroxidase
  • fluorophore such as fluorescein or rhodamine.
  • the immunochemistry technique can be direct or indirect.
  • Suitable immunoassay procedures include enzyme-linked immunosorbent assays (ELISA, such as multiplex ELISA), enzyme immunodot assay, agglutination assay, antibody-antigen-antibody sandwich assay, antigen- antibody-antigen sandwich assay, immunocromatography, or other immunoassay formats well-known to the ordinarily skilled artisan, such as radioimmunoassay, as well as protein microarray formats.
  • ELISA enzyme-linked immunosorbent assays
  • enzyme immunodot assay enzyme immunodot assay
  • agglutination assay antibody-antigen-antibody sandwich assay
  • antigen- antibody-antigen sandwich assay antigen- antibody-antigen sandwich assay
  • immunocromatography or other immunoassay formats well-known to the ordinarily skilled artisan, such as radioimmunoassay, as well as protein microarray formats.
  • the level of the protein is determined by an immunoassay.
  • the level of expression of protein is
  • antibody or a fragment thereof able to bind to the target protein(s) is to be understood as any immunoglobulin or fragment thereof able to selectively bind the target protein(s) referred in the aspects and embodiments of the present invention. It includes monoclonal and polyclonal antibodies.
  • fragment thereof encompasses any part of an antibody having the size and conformation suitable to bind an epitope of the target protein. Suitable fragments include F(ab), F(ab') and Fv.
  • An "epitope" is the part of the antigen being recognized by the immune system (B-cells, T-cells or antibodies).
  • the mRNA and/or protein is at least one of the mRNA or protein described in table 6, or any combinations thereof.
  • the present invention also refers to a method of treatment of a subject suffering cancer (e.g., CRC) in need thereof, the method comprising:
  • the cancer is CRC and the CRC contains TP53 wild type gene, or a non inactivating TP53 mutation (i.e., which does not lead to a loss of function of the p53 protein) or a TP53 mutation that is present in a low percentage of tumoral cells.
  • This method can also comprise the detection of the p53 protein mutational status, wherein when functional p53 protein is detected is indicative of the inefficiency of the anti-cancer chemotherapy, or the anti-cancer chemotherapy is considered ineffective.
  • the treatment provided in step (b) is chemotherapy (for example, FOLFOX4, mFOLFOX6, FOLFIRI, CAPOX, FLOX, or de Gramont regime) combined with a YAP1 inhibitor, e.g., porphyrin compounds such as Verteporfin®, protoporphyrin ix or hematoporphyrin ; e.g., Verteporfin®; e.g., is 5FU and irinotecan combined with Verteporfin®.
  • chemotherapy for example, FOLFOX4, mFOLFOX6, FOLFIRI, CAPOX, FLOX, or de Gramont regime
  • a YAP1 inhibitor e.g., porphyrin compounds such as Verteporfin®, protoporphyrin ix or hematoporphyrin ; e.g., Verteporfin®; e.g., is 5FU and irinote
  • the treatment provided in step (b) is surgery, a different anti-cancer chemotherapy, a different chemotherapy regime using the same anti-cancer chemotherapy, radiation therapy, immunotherapy, targeted therapy hormone therapy or any combination thereof.
  • the anti-cancer treatment is selected from the above-mentioned options based on type and stage of cancer, the results of clinical trials as well as histopathologic findings.
  • the sample is an isolated tissue sample, or a or a biological fluid sample (e.g., blood, plasma, serum, ascitic fluid, broncoalveolar lavage, and urine).
  • a biological fluid sample e.g., blood, plasma, serum, ascitic fluid, broncoalveolar lavage, and urine.
  • the sample is an isolated colon tissue sample, a rectal tissue sample, a biological fluid sample (for example, blood, serum or plasma), or a stool sample.
  • a biological fluid sample for example, blood, serum or plasma
  • the sample is a tissue sample or a biological fluid sample suspected to contain tumoral cells, in particular a CRC tissue sample.
  • the sample is fresh, frozen, fixed or fixed and embedded in paraffin; in an example, the sample is a paraffin embedded cancer tissue.
  • the patient is a mammal, preferably is a human.
  • the patient can be of any age, gender or race.
  • the CRC is a colon or rectum adenocarcinoma.
  • the present invention also refers to a kit that comprises means for predicting the outcome of a subject suffering CRC by the method of the first aspect of the invention, or for determining the efficacy of an anti cancer chemotherapy in a subject suffering CRC by the method of the second aspect of the invention, or for deciding or recommending a medical regime to subject suffering CRC by the method of the third aspect of the invention, the kit comprising means for determining the level of expression of at least one (e.g., of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 or 23 gene(s)) of the genes in table 4 and at least one (e.g., of 1, 2, 3, 4, 5, 6, 7, 8 gene(s)) of the genes in table 5; or, alternatively, of each one of TIMP2, T
  • ABHD4, GSN, CXCL16, CD99L2, and RHOD genes and of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes.
  • the kit can also comprise instructions (such as a leaflet) with the indication for performing the first, second, or third aspects or the fourth method of the present invention.
  • the kit can also comprise a reference sample, for example, a positive control (a sample from a tumor (e.g., CRC) with the signature of the present invention) and/or a negative control (for example from a normal tissue, or a reference tumor (e.g., a CRC) that does not present the signature of the present invention).
  • a positive control a sample from a tumor (e.g., CRC) with the signature of the present invention
  • a negative control for example from a normal tissue, or a reference tumor (e.g., a CRC) that does not present the signature of the present invention.
  • a fourth aspect of the invention refers to a use of a kit for predicting the outcome of a subject suffering CRC by the method of the first aspect of the invention, or for determining the efficacy of an anti-cancer chemotherapy in a subject suffering CRC by the method of the second aspect of the invention, or for deciding or recommending a medical regime to subject suffering CRC by the method of the third aspect of the invention
  • the kit comprising means for determining the level of expression of at least one (e.g., of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 or 23 gene(s)) of the genes in table 4 and at least one (e.g., of 1, 2, 3, 4, 5, 6, 7, 8 gene(s)) of the genes in table 5; or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes (optionally in combination with at least any other gene of table 4), and of an expression product of each one of MYB, AGMAT and CDX1 genes (
  • the nature of the means depends on the technique selected to identify the gene. Details about their nature have been provided above (primers, probes, antibodies, and fluorescent dyes, among others).
  • the kit may additionally comprise further means (additives, solvents) to visualize the interactions (dipsticks, chemiluminescent reagents, turbidimetric reagents, etc.). Suitable additives, solvents and reagents to visualize the identification are disclosed in the examples.
  • the antibodies and/or primers as specific for the protein and/or mRNA, respectively, of any one of the products of expression included in table 6 of the present invention.
  • the antibodies and/or primers as specific for the protein and/or mRNA, respectively, of any one of the products of expression included in table 6 of the present invention can be at least one pair of primers disclosed in table 8 of the present invention.
  • the fifth aspect of the invention refers to a combined use of an expression product of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes, and of an expression product of each one of MYB, AGMAT and CDX1 genes; or, alternatively, of a combined use of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes, and of an expression product of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; or, alternatively, a combined use of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, W
  • Another aspect of the invention refers to the use of the ratio of the level of expression of an expression product of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes, and the level of expression of an expression product of each one of MYB, AGMAT and CDX1 genes; or, alternatively, to the use of the ratio of the level of expression of an expression product of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes, and the level of expression of an expression product of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; or, alternatively to the use of the ratio of the level of expression of an expression product of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A
  • the in vitro methods of the invention provide prognostic information, information for determining the efficacy of an anti-cancer chemotherapy or information for deciding or recommending a medical regime.
  • the methods of the invention further comprise the steps of (i) collecting said information, and (ii) saving the information in a data carrier.
  • a “data carrier” is to be understood as any means that contain meaningful information data for the prognosis of cancer, such as paper.
  • the carrier may also be any entity or device capable of carrying the prognosis data.
  • the carrier may comprise a storage medium, such as a ROM, for example a CD ROM or a semiconductor ROM, or a magnetic recording medium, for example a floppy disc or hard disk.
  • the carrier may be a transmissible carrier such as an electrical or optical signal, which may be conveyed via electrical or optical cable or by radio or other means.
  • the carrier When the prognosis data are embodied in a signal that may be conveyed directly by a cable or other device or means, the carrier may be constituted by such cable or other device or means.
  • Other carriers relate to USB devices and computer archives. Examples of suitable data carrier are paper, CDs, USB, computer archives in PCs, or sound registration with the same information.
  • PDOs patient-derived organoids
  • Tumour spheres were collected and digested with an adequate amount of trypsin to single cells and re-plated in culture. Cultures were maintained at 37°C, 5% C0 2 and medium changed every week. PDOs were expanded by serial passaging and kept frozen in liquid Nitrogen for being used in subsequent experiments. Mutations for certain genes, including TP53, (see Table 7) in the PDOs were studied using lllumina® platform following manufacturer's instructions. In table 7 the corresponding chemotherapy concentrations that reduced a 20 and 30% of the cell growth (IC2oand IC30, respectively) are indicated for each PDO.
  • Patient-derived organoids (PDO) PD04, PD05, PD08, PDO10, PD011 and PD015 were deposited at MARBiobancfrom Hospital del Mar (Barcelona).
  • Patient- derived organoid 66 (PDO66) was kindly provided by Alberto Munoz Lab (Fernandez-Barral etal., 2020).
  • CRC cell lines HCT116 and Ls174T (KRAS mutated and TP53 WT), SW480 (KRAS and TP53 mutated) and HT29 (BRAF and TP53 mutated) were obtained from the American Type Culture Collection (ATCC, USA). All cells were grown in Dulbecco's modified Eagle's medium (Invitrogen) plus 10% fetal bovine serum (Biological Industries) and were maintained in a 5% CO2 incubator at 37°C. 5-FU+lri.
  • concentrations that reduced 30% of each cell growth were as follows: HCT116, 0.01 pg/mL 5-FU and 0.004 pg/mL Iri.; Ls174T, 0.025 pg/mL 5-FU and 0.01 pg/mL Iri.; SW480, 0.28 pg/mL 5-FU and 0.11 pg/mL Iri.; HT29, 0.33 pg/mL 5-FU and 0.13 pg/mL Iri.
  • Antibodies used Mouse monoclonal anti-p53 DO-1 (ab1101) (RRID:AB_297667), Rabbit monoclonal anti-p21 [EPR362] (ab 109520) (RRI D : AB_10860537), Rabbit monoclonal anti-CKN2A/p16INK4a [EPR1473] (ab108349) (RRI D : AB_10858268) , Rabbit polyclonal anti-CD99L2 (ab224164), Mouse monoclonal anti-
  • TIMP2 [3A4] (ab1828) (RRID:AB_2256129), Rabbit polyclonal anti-MRas (ab26303) (RRID:AB_470849), Anti- TUBB6 (PA5-P8948), Recombinant Anti-ICAMI antibody [EPR4776] (ab109361) (RRI D : AB_10958467) , Recombinant Anti-Hsp47 antibody [EPR4217] (ab109117) (RRI D : AB_10888995), Recombinant Anti-YAP1 antibody [EP1674Y] (ab52771) (RRID:AB_2219141), Anti-Histone H3 antibody-Nuclear Marker and ChIP Grade (ab791) (RRID:AB_302613) and Anti-Histone H4 antibody-ChIP Grade (ab1015) (RRID:AB_296888) from Abeam.
  • Mouse monoclonal anti-yH2AX (pS139) (564719) (RRID:AB_2738913) from BD, Biosciences; Mouse monoclonal anti-Ki67 (MM1) (NCL-Ki67-MM1) (RRI D : AB_442101) from Leica Biosystems; Rabbit polyclonal anti-Cleaved Caspase-3 (Asp175) (9661) (RRID:AB_2341188) from Cell Signaling; Goat polyclonal anti-EphB2 (AF467) (RRID:AB_355375) from RD Systems; TSPAN4 Polyclonal Antibody (PA5-69344) (RRID:AB_2688603) from Thermo Fisher Scientific; Monoclonal Anti-S100A4 antibody produced in mouse
  • D-Luciferin (Cat#LUCK) from Goldbio. PhosSTOP phosphatase inhibitor cocktail (Cat#PHOSS-RO) and Complete Mini protease inhibitor cocktail (Cat#11836170001) from Roche. DAPI Fluoromount-G (Cat#0100-20) from Southern Biotech. Protein A- Sepharose CL-4B (Cat#17-0780-01) and Protein G-Sepharose 4 Fast Flow (Cat#17-0618-01) from GE Healthcare.
  • APC BrdU Flow Kit (Cat#552598), from BD Biosciences. Senescence b-Galactosidase Staining Kit (Cat#9860S) from Cell Signaling. Cell Event Senescence Green Flow Cytometry Assay KiT (Cat#C10840) and Annexin V Apoptosis Detection Kit APC (Cat#88-8007) from Invitrogen. CometAssay Kit (Cat#4250-050- K) from Trevigen. RNeasy Micro Kit (Cat#74004) from Qiagen. SYBR Green I Master Kit (Cat#04887352001) from Roche. Lenti-X Concentrator (Cat#631232) from Clontech.
  • RRID:SCR_015687 ChIP-seeker package from Bioconductor. Corrplot, survimer, survival, heatmaply and pheatma packages from CRAN. TopHat (RRID:SCR_013035), from Kim etal. 2013. HTSeq (RRID:SCR_05514) from Anders etal. 2015. The stats package from R Core Team. Oligonucleotides: Table 8 (see below) shows the oligonucleotides for RT-qPCR and ChIP-qPCR and sgRNA for CIRSPR/Cas9 knockout used (SEQ ID NO: 1-71).
  • tumoroids were plated in 96-well plates in Matrigel and after 6 days in culture were treated with combinations of 5-FU and Irinotecan. Following 72 hours of treatment, it was changed to fresh medium and treated with increasing concentrations of either 5-FU, Irinotecan, dasatinib or combinations for 72 hours at the indicated concentrations. Cell viability was determined as described. Tumor-initiating assays
  • PDOs patient-derived organoids
  • Paraffin blocks were obtained from tissues and PDOs, previous fixation in 4% formaldehyde overnight at room temperature. Paraffin-embedded sections of 4 pm, for tissues, and 2.5 pm, for PDOs, were de-paraffinized, rehydrated and endogenous peroxidase activity was quenched (20 min, 1.5% H 2 0 2 ). EDTA- or citrate-based antigen retrieval was used depending on the primary antibody used. All primary antibodies were diluted in PBS containing 0.05% BSA, incubated overnight at 4 °C and developed with the Envision+ System HRP Labelled Polymer anti-Rabbit or anti-Mouse and 3,3'-diaminobenzidine (DAB). Samples were mounted in DPX mountant and images were obtained with an Olympus BX61 microscope.
  • DAB Envision+ System HRP Labelled Polymer anti-Rabbit or anti-Mouse and 3,3'-diaminobenzidine
  • Fluorescent in-situ hybridization (FISH) FISH analyses from control and IC30-treated PDOs were performed using commercial probes (Abbott Molecular Inc, Des Plaines, IL, USA), one including the centromeric alfa-satellite region specific for chromosome 8 (probe "30-70008 CEP 8 SpOrange”), and a second one containing locus-specific probes from the long arm of chromosome 13 and 21 (probe "33-171076 Aneuvysion 13 Sgreen/21 SpOrange”).
  • a cytospin to concentrate nuclei in the FISH slide was performed. Slides were pre-treated with pepsin for 5 minutes at 37°C.
  • Samples and probe were co-denaturated at 80°C for five minutes and hybridized overnight at 37°C in a hot plate (Hybrite chamber, Abbot Molecular Inc.). Post-hybridization washes were performed at 73°C in 2xsodium salt ctrate buffer (SSC) and at room temperature in 2xSSC, 0.1% NP-40 solution. Samples were counterstained with 4,6-diamino-2-phenilindole (DAPI) (Abbott Molecular Inc, Des Plaines, IL, USA). Results were analyzed in a fluorescence microscope (Olympus, BX51) using the Cytovision software (Applied Imaging, Santa Clara, CA). A minimum of 50 nuclei per case was analysed.
  • SSC 2xsodium salt ctrate buffer
  • DAPI 4,6-diamino-2-phenilindole
  • Cell senescence assays Cell senescence was identified by the presence of SA- -galactosidase activity using two different approaches. On one hand, staining for SA- -galactosidase activity in cultured cells was carried out using the Senescence b-Galactosidase Staining Kit. Briefly, PDOs were seeded in 24-well plates (3000 cells per well). After 6 days, PDOs were treated with combinations of 5-FU and Irinotecan for 72 hours and were subsequent stained with the b-Galactosidase Staining Solution for 2 hours, according to the manufacturer's instructions. Sections embedded in paraffin were counterstained with Fast Red for nuclei visualization.
  • Annexin V binding was determined by flow cytometry using the standard Annexin V Apoptosis Detection Kit APC. Single cells of treated PDOs with indicated combinations of 5-FU+lri. were obtained and stained according to the manufacturer's instructions, with Propidium Iodide staining for the DNA content. The cells were analysed in the Fortessa analyser.
  • PDO Initiating Capacity assay 300 or 600 single PDO cells were plated in 96-well plates in 10 pL Matrigel. After 11 days in culture, the number of PDOs in each well was counted, photographs were taken for PDO diameter determination and cell viability was measured.
  • Tumoroid Initiating Capacity assay 300 or 600 single PDO cells were plated in 96-well plates in 10 pL Matrigel. After 11 days in culture, the number of PDOs in each well was counted, photographs were taken for PDO diameter determination and cell viability was measured.
  • Treated PDOs were lysed for 20 min on ice in 300 pL of PBS plus 0.5% Triton X-100, 1 mM EDTA, 100 mM NA-orthovanadate, 0.2 mM phenyl-methylsulfonyl fluoride, and complete protease and phosphatase inhibitor cocktails. Lysates were analysed by western blotting using standard SDS-polyacrylamide gel electrophoresis (SDS-PAGE) techniques. In brief, protein samples were boiled in Laemmli buffer, run in polyacrylamide gels, and transferred onto polyvinylidene difluoride (PVDF) membranes.
  • PVDF polyvinylidene difluoride
  • the membranes were incubated with the appropriate primary antibodies overnight at 4°C, washed and incubated with specific secondary horseradish peroxidase-linked antibodies. Peroxidase activity was visualized using the enhanced chemiluminescence reagent and autoradiography films.
  • RNA from treated PDOs was extracted with the RNeasy Micro Kit, and cDNA was produced with the RT-First Strand cDNA Synthesis Kit.
  • RT-qPCR was performed in LightCycler 480 system using SYBR Green I Master Kit. Samples were normalized to the mean of the housekeeping genes TBP, HPRT1 and ACTB. Primers used for qPCR are listed in Table 8 (SEQ ID NO: 1 to 60) (see below).
  • Chromatin-immunoprecipitation assay ChIP
  • Control and IC20-treated PDOs were subjected to ChIP following standard procedures. Briefly, PDO cells were extracted with formaldehyde crosslinked for 10 min at room temperature and lysed for 20 min on ice with 500 pL of H 2 0 plus 10 mM Tris-HCI pH 8.0, 0.25% Triton X-100, 10 mM EDTA, 0.5 mM EGTA, 20 mM b- glycerol-phosphate, 100 mM NA-orthovanadate, 10 mM NaButyrate and complete protease inhibitor cocktail.
  • IC20-treated PD05 was subjected to ChIP as previously described (Mulero etal., 2013). Briefly, formaldehyde crosslinked cell extracts were sonicated, and chromatin fractions were incubated for 16 h with anti-p53 [Abeam ab 1101] antibody in RIPA buffer and then precipitated with protein A/G-sepharose [GE Healthcare, Refs. 17- 0618-01 and 17-0780-01], Crosslinkage was reversed, and 6-10 ng of precipitated chromatin was directly sequenced in the genomics facility of Parc de Recerca Biomedica de Barcelona (PRBB) using lllumina® HiSeq platform.
  • PRBB Parc de Recerca Biomedica de Barcelona
  • Raw single-end 50-bp sequences were filtered by quality (Q > 30) and length (length > 20 bp) with Trim Galore (Krueger etal., 2012). Filtered sequences were aligned against the reference genome (hg38) with Bowtie2 (Langmead & Salzberg, 2012). MACS2 software (Zhang et al., 2008) was run first for each replicate using unique alignments (q-value ⁇ 0.1). Peak annotation was performed with ChIPseeker package and peak visualization was done with Integrative Genomics Viewer (Robinson etal., 2011).
  • lentiCRISPR v2 was used for knock-out experiments.
  • Three sgRNA against TP53 gene were designed using Benchling (table 8, SEQ ID NO: 69-71). Lentiviral production was performed transfecting in HEK293T cells the lentiviral vectors (pMD2.G and pCMVR8.2 plasmids) and the plasmid of interest (lentiCRISPR v2 as CRISPR control plasmid and the 3 sgRNA).
  • PDOs were infected by resuspending single cells in concentrated virus diluted in complete medium, centrifuged for 1 h at 650 ref, and incubated for 5 hours at 37°C. Cells were then washed in complete culture medium and seeded as described above.
  • RNA from untreatred and treated PDOs was extracted using RNeasy Micro Kit.
  • the RNA concentration and integrity were determined using Agilent Bioanalyzer (Agilent Technologies, following manufacturer's instructions). Libraries were prepared at the Genomics Unit of Barcelona Biomedical Research Park (PRBB) (Barcelona, Spain) using standard protocols, and cDNA was sequenced using lllumina® HiSeq platform (HiSeq® 2500 Sequencing System, following manufacturer's instructions), obtaining ⁇ 25-30million 50-bp single-end reads per sample. Adapter sequences were trimmed with Trim Galore. Sequences were filtered by quality (Q > 30) and length (> 20 bp).
  • the CRC cell line LS174T was treated with sublethal doses of 5FU+irinotecan for 72h, alone or in combination with the YAP1 inhibitor verterporfin®, at a concentration of 5mM.
  • CRC cell line LS 174T ( TP53 WT) was obtained from ATCC, was grown in Dulbecco's modified Eagle's medium (Invitrogen) plus 10% fetal bovine serum (Biological Industries) and was maintained in a 5% CO 2 incubator at 37°C.
  • the membranes were incubated with the appropriate primary antibodies overnight at 4°C, washed and incubated with specific secondary horseradish peroxidase-linked antibodies. Peroxidase activity was visualized using the enhanced chemiluminescence reagent and autoradiography films.
  • Example 1 Low-dose CT treatment of colorectal cancer PDOs induced a non-senescent quiescent phenotype in the absence of sustained DNA damage.
  • CRC PDOs were treated with serial dilutions of the first-line CT agents 5-FU+lri. to define doses that reduced cell numbers about 20- 30% after 72 hours of treatment (hereafter referred as IC20 and IC30, for Inhibitory Concentration 20 and 30), which were specific for each PDO (see table 7).
  • IC20 and IC30 were treated with serial dilutions of the first-line CT agents 5-FU+lri. to define doses that reduced cell numbers about 20- 30% after 72 hours of treatment (hereafter referred as IC20 and IC30, for Inhibitory Concentration 20 and 30), which were specific for each PDO (see table 7).
  • Microscopy analysis of PDOs indicated that IC20 and IC30 did not promote detectable cell death after 72 hours but imposed a dose-dependent growth arrest that persisted for at least 2 weeks after drug washout.
  • SA senescence-associated
  • IHC immunohystochemistry
  • Example 2 The TQL phenotype was associated with acquisition of a fetal intestinal stem cell (feISC) signature.
  • feISC fetal intestinal stem cell
  • RNA sequencing RNA sequencing (RNAseq) of control, IC20- and IC30- treated PD05 cells and differentially expressed genes (DEGs) between conditions were assessed.
  • RNAseq RNA sequencing of control, IC20- and IC30- treated PD05 cells and differentially expressed genes (DEGs) between conditions were assessed.
  • DEGs differentially expressed genes
  • GSEA Gene Set Enrichment Analysis
  • GSEA analysis also detected association with the NF-KB, apoptosis and interferon gamma (IFNy) pathways (p53 pathway, TNFA siganling via NFKB, coagulation, myogenesis, epithelial-mesenchymal transition, Kras signalling Down (DN), apoptosis, Kras signalling up and Interferon gamma response pathways in descending order of enrichment score (normalized enrichment score).
  • IFNy interferon gamma pathway
  • Example 3 The feISC signature shows a coordinate expression in human CRC and is dependent of functional p53.
  • the genes included in the 28up/8down signature were the following: "28up” were TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2 and RHOD genes (see table 4 below); and the "8down” were MYB, AGMAT, CDX1, H00K1,
  • PDSS1, HUNK, KCNK5 and SLC27A2 genes see table 5 below.
  • ChIP-sequencing ChIP-sequencing assay of 5FU+iri (IC20) treated-PD05 cells, it was only detected p53 binding at the promoter of PLK2, PHLDA3 and GSN genes, consistent with the fact that only 5 of the 28up-felSC genes had been previously identified as p53 targets.
  • RNAseq data from Lee and collaborators demonstrated that feISC genes were expressed in the epithelial component of untreated tumors, particularly in state 1, 5 and 6 that were associated with secretory and migratory pathways.
  • acquisition of the TQL phenotype was linked with the expression of specific fetal ISC signature that was differentially expressed in cancer cells and dependent on the presence of a functional p53 pathway.
  • This feISC signature was expressed in a coordinate manner in untreated human CRC tumors in the CMS4 subtype and tumors in the secretory and migratory epithelial states 1 , 5 and 6 from Guinney and collaborators.
  • TQL cancer cells displayed in vitro and in vivo tumor initiation capacity Whether TQL cells preserved the tumor initiation capacity of untreated PDOs was studied. There were seeded 300 single cells from untreated or PDO cells treated for 72 hours in 3D cultures as indicated in the material and method section. It was found that CT-treated and untreated cells displayed comparable tumor initiation capacity (TIC) as indicated by the equal number of PDOs formed, although CT-treatment resulted in dose- dependent reduction of PDO diameter consistent with their low proliferation rates. In contrast, IC20- 5Fu+iri pre-treatment of p53 mutant PD04 and PD08 cells resulted in TIC abrogation, which was in agreement with the massive accumulation of DNA damage detected in comer assays.
  • TIC tumor initiation capacity
  • a p53 WT PD05 carrying a doxycycline-inducible histone-GFP reporter that has been previously demonstrated to label the quiescent tumor population after doxycycline withdrawal (Puig et al., 2018).
  • PD05 cells were treated with 5-FU+lri. for 72h and, after 2 weeks of doxycycline washout, cells were analyzed by flow cytometry and GFP high and GFP
  • Sorted GPF high which represented the quiescent population of CT-treated cells, displayed identical capacity for organoid generation as GFP high plus GFP
  • IC20 and IC30-treated PDOs were inoculated comparable numbers of untreated, IC20 and IC30-treated PDOs in the cecum of nude mice (2, 4 and 5 mice, respectively). Tumor growth was evaluated by palpation of the mice cecum weekly.
  • IHC analysis of the proliferation marker ki67 indicated that tumors generated from untreated PDOs contained 60-80% of proliferating cells, whereas tumors derived from IC20 and IC30-treated PDOs showed a mixed pattern of quiescent (ki67 negative) and proliferative (ki67 positive) areas.
  • 40,000 single PD05 cells (untreated, IC20 or IC30) expressing a luciferase reporter were injected intracardiac to NSG mice. Mice were analysed weekly for metastatic growth using the IVIS animal imaging system. PD05 treated with 5-FU+lri displayed a slightly superior metastatic capacity than untreated cells.
  • mice transplanted with untreated PD05 cells contained metastatic lesions at week 15 after transplantation.
  • 4 of 6 mice transplanted with IC20-treated cells and 5 of 6 mice with IC30-treated cells showed visible implants 15 weeks after injection.
  • Example 5 The CT induced feISC signature was predictive of poor patient prognosis, with higher statistical power in p53 WT tumors. The possibility that the feISC signature present in TQL cells was associated with cancer patient's outcome was studied. It was analyzed the predictive capacity of 28up/8down-felSC gene signature in the Marisa (Marisa etal., 2013), Jorissen (Jorissen etal., 2009) and TCGA (TCGA Portal) CRC data sets (following the method described for the "Association of the signatures with clinical outcome” in the material and method section above).
  • the 8up/8down-felSC signature included TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, C0L18A1, SERPINH1, TPM2 genes as the 8up genes, and MYB, AGMAT, CDX1, H00K1, PDSS1, HUNK, KCNK5 and SLC27A2 as the 8down genes.
  • genes were selected by two ways. First, genes were scored by their coordinate expression taking into account the 3 CRC datasets analysed. Then it was evaluated the prognosis value by adding a value of single genes to the simplest signature composed by the highest scored 28up plus the highest scored 8down-felSC. This method uncovered a more simplified signature (see Table 9), named as "5up+3down” signature, which included 5 upregulated genes TIMP2, TSPAN4, TUBB6, MRAS, and ARL4C, and 3 down regulated genes MYB, AGMAT and CDX1.
  • genes were selected by two conditions: first by a correlation score higher than 0.8 (or if not, higher than the maximum of its table) and second, statistically significant, this is a correlation lower than a significant level of 5% . Then it was evaluated the prognosis value by adding a value of single genes to the simplest signature composed by genes that appeared in at least two of the three cohorts analyzed or that comprised the "5up+3down” signature.
  • rC "TUBB6" and “TIMP2” as up-regulated genes and “MYB” and “HOOK” as down-regulated genes.
  • rD “TUBB6”, “TIMP2” and “TSPAN4" as up-regulated genes and “MYB” and “HOOK” as down-regulated genes.
  • rE “TUBB6” and “TIMP2” as up-regulated genes and “MYB”, “HOOK” and “AGMAT” as down-regulated genes.
  • rF “TUBB6", “TIMP2” and “TSPAN4" as up-regulated genes and "MYB”, “HOOK” and “AGMAT” as down-regulated genes.
  • rJ "TUBB6" and “TIMP2” as up-regulated genes and "MYB” as down-regulated gene.
  • rK “TIMP2” as up-regulated gene and “MYB” and “H00K1” as down-regulated genes.
  • rL “TIMP2, “TUBB6” and “TSPAN4" as up-regulated genes and "CDX1” as down-regulated gene.
  • rM “TIMP2” and “TSPAN4" as up-regulated genes and "CDX1” as down-regulated gene.
  • the arithmetic mean of the 28up genes divided by the arithmetic mean of the 8down genes was analysed, either for the group with highest 28up and lowest 8down- felSC levels (poorest outcome), as well as for the group with lowest 28up and highest 8down-felSC levels, in the Marisa dataset. This gave rise to a ratio of 1.22 within the patients with the poorest outcome. It was performed a series of supervised analysis for TCGA, Jorissen and Marisa dataset for the purpose of finding the optimized ratios.
  • Example 6 Acquisition of feISC by CT treatment was linked to and dependent on YAP1 activation and the feISC signature was reversed by using the YAP1 inhibitor Verteporfin®
  • FIG. 11 A An in vitro experiment using PD05 cells (Fig. 11 A) and a various CRC cell lines (Fig. 11 B) showed increased YAP1 expression after 5-FU+lri treatment, that was restricted to cells carrying WT P53.
  • Nuclear (active) YAP1 accumulated in the IC20- and IC30- derived PD05 tumors at 2 months after implantation in mice.
  • IHC analysis of ki67 in 62 paired human CRC samples collected at diagnosis (biopsy) and after DNA damaging-based neoadyuvant treatment (surgery) the proliferation status of the tumors was determined.
  • tumors exhibited similar proliferation rates after treatment, as determined by Ki67 staining (type 1), a large subset of tumors displayed reduced proliferation with no morphological evidences of senescence (type 2), such as enlarged nuclei or expression of the senescence marker p16 which were detected in scarce tumors at surgery (type 3). No differences were detected in patient prognosis when comparing type 1 and type 2 tumors that were readily observed in patient carrying type 3 tumors (no events of relapse in the follow up period).
  • nuclear YAP1 which was already detected in few epithelial cells of untreated tumors, was massively increased in neoadjuvant treated tumors independently of the proliferation status associated with expression of the feISC markers S100A4 and SERPINH1.
  • YAP1 activity was required for transcriptional induction of feISC genes by CT
  • PD05 cells were incubated with the YAP1 inhibitor verteporfin® (Fig. 11C), which precluded the induction of all tested feISC genes following IC205FU+irinotecan treatment.
  • treatment of the colorectal p53 WT cell line (cell line LS174T) with IC205FU+irinotecan for 72h led to an increase in YAP1, SERPINH1 and TSPAN4 protein levels, which was abrogated by the verterporfin® (Fig. 11D).
  • Low CT doses led to nuclear YAP1 accumulation that was abrogated by incubation with verteporfin®.
  • Verteporfin® also led to a reduction in protein levels of YAP1 and the feISC markers SERPINH1 and TSPAN4 (Fig. 11 D). Importantly, verteporfin® alone or in combination with low doses of CT promoted tumor cell death specifically in the P53 WT PD05. In contrast, PD08 carrying mutant P53 showed higher resistance to YAP1 inhibition.
  • Table 6 Expression products of the genes of tables 4 and 5: mRNA Ref SEQ and protein RefSeq were the reference sequence of GenBank; HGNC, HUGO Gene Nomenclature Committee at 25 November 2020.
  • Table 7 Patient-derived organoids used. The mutations and the corresponding chemotherapy concentrations that reduce a 20 and 30% of the cell growth (IC20 and IC30, respectively) are indicated for each PDO.
  • Table 8 List of oligonucleotides for RT-qPCR and ChIP-qPCR and sgRNA for CIRSPR/Cas9 knockout used.
  • Table 9 Pearson correlation punctuation score for the genes included in the 28up/8down firm.
  • (a1) at least one gene selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4,
  • GSN GSN, CXCL16, CD99L2, RHOD (genes of table 4) and any combination thereof; and (a2) at least one gene selected from the group consisting of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5, SLC27A2 (genes of table 5) and any combination thereof.
  • the in vitro method for the prediction of the outcome which further comprises the step: b) determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2); wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01 and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99.
  • step (b) 3.
  • the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01 , 1.05, 1.10 or 1.2; and the subject is considered as having good outcome if the ratio obtained in step
  • (b) is lower than or equal to 0.99, 0.95 or 0.90.
  • step (a) comprises determining in an isolated sample of a subject the level of expression of (a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes;
  • step (a) comprises determining in an isolated sample of a subject the level of expression of (a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and
  • step (a) comprises determining in an isolated sample of a subject the level of expression of
  • the method further comprises identifying the mutation status of TP53 gene, wherein the subject is considered as having bad outcome when the TP53 gene is the TP53 wild-type gene or, alternatively, when the TP53 gene is a non-inactivating mutated TP53.
  • (a1) at least one gene selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD (genes of table 4) and any combination thereof; and
  • (a2) at least one gene selected from the group consisting of: MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 (genes of table 5) and any combination thereof; or, alternatively,
  • An in vitro method for deciding or recommending a medical regime to a subject suffering colorectal cancer (CRC) comprising:
  • kits for predicting the outcome of a subject suffering colorectal cancer as defined in any one of claims 1 to 8 or 11 or 13, or for determining the efficacy of an anti-cancer chemotherapy in a subject suffering colorectal cancer as defined in any one of claims 9 to 11 or 13, for deciding or recommending a medical regime to subject suffering colorectal cancer as defined in any one of claims 12-13 the kit comprising means for determining the level of expression of at least one of the genes in table 4 and at least one of the genes in table 5; or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes, and of each one of MYB, AGMAT and CDX1 genes; or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and
  • TPM2 genes and of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C,
  • TopHat2 Accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biology, doi.org/10.1186/gb-2013-14-4-r36.

Abstract

The present invention refers to an in vitro method for the prediction of the outcome in a subject suffering cancer, in particular colorectal cancer. The present invention also refers to an in vitro method to determine the efficacy of an anti-cancer chemotherapy in a cancer patient and to an in vitro method for deciding or recommending a medical regime to a subject with cancer, in particular, colorectal cancer; the methods comprising determining in an isolated sample of a subject the level of expression of selected genes.

Description

Genomic predictor of outcome in cancer
This application claims the benefit of European Patent Application EP21382269.5 filed on 31.03.2021.
Technical Field
The present invention relates to the field of Medicine, particularly to cancer and more particularly to colorectal cancer, specifically to a new method for predicting the outcome of cancer. The method has potential applications in the clinical management of cancer patients in terms of medical treatment.
Background Art
Chemotherapy (CT) is a common current therapy against cancer which is founded on DNA-damaging agents that either kill or inflict a senescent phenotype to highly proliferative malignant cells. In general, anticancer agents are designed to eradicate tumors by inducing double-strand breaks in highly proliferative cells leading to cell death (Brenner et al., 2014). It has been recurrently shown that sub-lethal doses of CT impose a senescent phenotype to cancer cells, characterized by high p16 and/or p21 levels, cessation of proliferation and presence of a senescence-associated-secretory-phenotype (SASP) that effectively delays disease progression in cellular and animal models (He and Sharpless, 2017). Nevertheless, senescent cells may contribute to cancer progression and disease recurrence (e.g., after senescent cell reactivation) (Saleh et al., 2019). Therefore, even using chemotherapy in combination with other approaches, such as surgical removal of the tumor, not all cancer patients are cured.
For example, in colorectal cancer (CRC) the first-line treatment for CRC currently involves surgery, radiotherapy and/or combinations of 5-fluorouracil (5-FU) plus oxaliplatin or irinotecan (Iri), in neoadjuvant or adjuvant settings. Nevertheless, CRC remains the second leading cause of cancer-related death. Even after adequate treatment, around 25-30% of CRC patients in the less aggressive stage II tumors and up to 30-50% in stage III relapse and most of them eventually die due to metastasis and chemotherapy (CT) resistance.
To date, there are no reliable indications, beyond tumor staging, that predict chemotherapy response in cancer patients. Despite the efforts made, there is a need of tools which allow accurate prediction of the progression of a patient suffering cancer.
Summary of Invention
The inventors have found valuable informative markers about the prediction of the outcome of cancer. The inventors have found that when a subject has a signature comprising differential expression of genes form table 1 , in particular, when the subject presents upregulation of the expression of certain genes of table 2 in combination with the downregulation of certain genes of table 3, then the subject has a bad prediction for the outcome (bad prognosis). By performing in vitro experiments in patient-derived cancer cells (exemplified by colorectal cancer cells) grown as 3D cultures (herein referred as PDOs) treated with low doses of chemotherapy (exemplified by 5- fluorouracil plus irinotecan (5-FU+lri)), the inventors have found that those cells acquired a non-senescent quiescent-like phenotype (see example 1). In the present application it is demonstrated that those therapy- induced quiescent-like (TQL) cells displayed in vitro and in vivo tumor initiating capacity (TIC) (see example 2). Moreover, In the present application it is demonstrated that chemotherapy negatively impacts on cancer progression in case of incomplete remission (exemplified in vitro by low doses of chemotherapy (example 2, IC20 or IC30 versus IC60)). Moreover, the inventors have identified a genetic signature that was acquired by the TQL cells that predicted cancer outcome in cancer patients. The inventors have found that the up- regulation of at least one gene of table 2 and the combined downregulation of at least one gene of table 3 in an isolated sample from a subject with cancer can provide useful information about the prognosis of said cancer in the subject, exemplified by colorectal cancer (CRC). Moreover, the inventors have identified that the genetic signature that was acquired by the TQL cells in vitro when using low doses of chemotherapy also predicted cancer outcome in cancer patients including patients which did not received yet chemotherapy (exemplified for CRC and demonstrated in three cohort of patients, see examples 3-5). The inventors have demonstrated that ratio between the level of expression of genes of table 2 and genes of table 3 provide valuable information that predicted poor disease outcome of cancer patients (see example 5).
In CRC the inventors have demonstrated that the upregulation of at least five genes of table 2 and the downregulation of three genes of table 3 provides information about the outcome CRC disease outcome, in particular for stages II and III (examples 3-5). For CRC the inventors have found by patient-derived evidence that a signature included in the gene signature of tables 1 , which includes upregulated genes of tables 2 and downregulated genes of table 3, herein named as "5up+3down”, "5up+4down”, "8up+8down” and "28up+8down signatures are useful for the prediction of the outcome of CRC (see figures 3-10). These signatures are useful also in stage I, stage II and stage III CRC (see figures 4A, 4B, 8A, 8B, 10A, 10B, 10C, 10D and 12), which are of special interest due to the uncertainty of progression in these stages. The inventors have also found that these signatures are useful on patients independently of the p53 status but are particularly useful for patients with wild-type p53, as it was found that the outcome for patients having wild- type TP53 gene was worst that those with mutated TP53 (that lead to non-functional p53) when the signatures were detected (see figure 5A and 5B). Moreover, the inventors have surprisingly found that using YAP1 inhibitors in vitro there is a reversal of the expression of certain genes included in the gene signatures of the present invention (example 6 and figure 11).
From the data provided below, it is remarkable that when a differential regulation was identified for the genes included in the signature disclosed in table 1, in particular upregulation of genes of table 2 and downregulation of genes of table 3, in a sample, then the patient with cancer was associated with bad outcome (see section 4 of the results wherein it is exemplified for CRC).
The results provided below support that the overexpression of at least one gene of table 2 and the downregulation of at least one gene of table 3 is indicative of bad prognosis of cancer. These prognosis markers can help in the determination of the efficacy of a chemotherapeutic regime and in the decision or recommendation of a medical regime for a cancer patient. This can be of great value for the physician in order to decide the best therapeutic strategy to successfully overcome the disease, such as to undergo a more aggressive chemotherapy regime in a patient that has already received chemotherapy. The inventors have found a signature useful for the prediction of the outcome of cancer, e.g., CRC, for the determination of the efficacy of an anti-cancer chemotherapy and for deciding or recommending a medical regime to a subject with cancer (e.g., with CRC).
Thus, the first aspect of the invention refers to an in vitro method for the prediction of the outcome in a subject suffering cancer, the method comprising the step of: a. determining in an isolated sample of a subject the level of expression of
(a1) at least one gene selected from table 2 or any combination thereof, and (a2) at least one gene selected from table 3 or any combination thereof.
A second aspect of the invention refers to an in vitro method to determine the efficacy of an anti-cancer chemotherapy in a subject suffering cancer comprising the steps of:
(a) determining in an isolated sample of a subject before and after starting the anti-cancer chemotherapy the level of expression of
(a1) at least one gene selected from table 2 or any combination thereof, and (a2) at least one gene selected from table 3 or any combination thereof; and b) determining a ratio between the level of expression of the gene(s) determined in step (a1) and the gene(s) determined in step (a2) before and after starting the anti-cancer chemotherapy, wherein, if the ratio of gene expression after starting the anti-cancer chemotherapy is higher than or equal to the ratio obtained before starting the anti-cancer chemotherapy, this is indicative of the inefficiency of the anti cancer chemotherapy.
A third aspect of the invention refers to an in vitro method for deciding or recommending a medical regime to a subject suffering cancer the method comprising:
(a) predicting the outcome of the subject suffering colorectal cancer by the method of the first aspect of the invention, or, alternatively, determining the efficacy of an anti-cancer chemotherapy by the method of the second aspect of the invention, and
(b) recommending a therapeutic medical regime if the subject is predicted to have bad outcome, or, alternatively, recommending an alternative medical regime if the anti-cancer chemotherapy is ineffective. A fourth aspect of the invention refers to a use of a kit for predicting the outcome in a subject suffering cancer as defined in the method of the first aspect of the invention, or for determining the efficacy of an anti-cancer chemotherapy in a subject suffering cancer as defined in the second aspect of the invention, or for deciding or recommending a medical regime to a subject suffering cancer as defined in the method of the third aspect of the invention, wherein the kit comprises means for determining the level of expression of at least one of the genes selected from table 2 and at least one of the genes selected from table 3 or any combinations thereof.
A fifth aspect of the invention refers to a combined use of an expression product of at least one gene selected from table 2 and at least one gene selected form table 3 or any combination thereof, as a marker of prediction of progression of cancer, or of determining the efficacy of an anti-cancer chemotherapy in a subject suffering cancer, or of deciding or recommending a medical regime in a subject suffering cancer.
Brief Description of Drawings
Fig. 1. Shows that CT-induced quiescent cells acquired a fetal intestinal stem cells signature: (A) western blotting (WB) analysis of control (untreated) and treated PD05 collected at the indicated time points after 5FU+lri treatment. (B) RT-qPCR analysis of selected p53 target genes from control (untreated) and IC20- treated PD05 cells.
Fig.2. Shows that CT-induced quiescent cells displayed a fetal intestinal stem cell signature that was TP53 dependent: (A) Displays the coordinated expression of the feISC signature by a scatter plot, with the linear regression line, of the genes differentially expressed between CT treated and control PDOs and fetal compared with adult intestinal stem cell. Dots represent the log2 fold change values of genes for treated versus control (x-axis) and fetal versus adult intestinal stem cell (y-axis). The Pearson correlation and p value are shown. Genes included in the 28up/8down signature are indicated as black dots within the upper right quadrant (genes upregulated) and the lower left quadrant (genes downregulated). The 88 remaining genes are indicated as white dots (within the upper right quadrant (genes upregulated) and the lower left quadrant (genes downregulated)). (B) RT-qPCR analysis of normalized expression of selected 28up+8down-felSC signature genes in control (untreated) and treated PD05 as indicated. (C) WB analysis of several feISC genes of control and treated PD05 collected at the indicated time points (in hours) after 5FU+lri treatment. (D, E) RT-qPCR analysis of normalized relative expression of selected 28up+8down-felSC signature genes in control (untreated) and treated (D) PD066 TP53 wild type (WT) and (E) the TP53 mutant PD04. (F) WB analysis of p53 and its downstream target p21 in three CRISPR-Cas9-enginireed p53 KO pools and their control (an empty CRISPR-Cas9 vector). (G) RT-qPCR analysis of normalized relative expression of selected 28up+8down-felSC signature genes in control and treated PD05 TP53 KO #3 ("untreat.”, untreated) (for each gene from left to right: PD05 untreated, PDO IC20, PDO KO#3 untreated and PDO KO#3 IC20). (FI) WB analysis of various CRC cell lines untreated ("-") or collected after 72 hours of 5-FU+lri. treatment ("+”).
Fig. 3. Identification of a fetal ISC signature with prognostic value in CRC: Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 28up/8down-felSC signature selected according to the "Marisa”, "Jorissen” and "TCGA” colorectal cancer databases.
Fig. 4. Kaplan-Meier curves representing the disease-free survival of patient groups from (A) stage II and (B) stage II and III from Marisa colorectal cancer database, selected according to their cluster analysis of the 28up/8down-felSC signature. Hazard ratio (HR).
Fig. 5. Kaplan-Meier curves representing the disease-free survival of patient groups classified according to their cluster analysis of the 28up+8down-felSC signature for patient groups from TP53 wild type ("P53 WT”) and TP53 mutant (P53 MUT) in (A) Marisa and (B) TCGA colorectal cancer databases.
Fig. 6. Kaplan-Meier representation of disease-free survival probability over time of Marisa patient's tumors previously categorized as CMS4 and classified according to their cluster analysis of the 28up+8down-felSC signature.
Fig. 7. Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 8up/8down-felSC signature according for the "Marisa”, "Jorissen” and "TCGA” colorectal cancer databases.
Fig. 8. Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 8up/8down-felSC signature of (A) stage III and (B) stage II and III "Marisa” colorectal database, selected according to their unsupervised hierarchical cluster analysis.
Fig. 9. Shows the optimized 5up/3down-felSC signature: (A) RT-qPCR analysis of selected fetal genes from control (untreated) and IC20-treated PD05 cells. Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 5up/3down-felSC signature (B) and 5up/4down signature (C) according for the "Marisa”, "Jorissen” and "TCGA” colorectal cancer databases.
Fig. 10. Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 5up/3down-felSC signature of (A) stage II and (B) stage II and III "Marisa” colorectal database, selected according to their unsupervised hierarchical cluster analysis. Kaplan-Meier representation of disease-free survival probability over time for patients with high or low expression of the 5up/4down-felSC signature of (C) stage II and (D) stage II and III "Marisa” colorectal database, selected according to their unsupervised hierarchical cluster analysis.
Fig. 11. Shows that the acquisition of feISC by CT treatments was dependent of YAP1 activation: (A) WB analysis of p53 and YAP1 protein levels in control and TP53-depleted PD05 KO# 3 cells collected after 72 hours of 5-FU+lri. treatment. (B) WB analysis of TP53 wild type (HCT116 and Ls174T) and TP53 mutant (SW480 and HT29-M6) colorectal cancer cell lines untreated ("-") and collected after 72 hours of 5-FU+iri. Treatment ("+”). (C) RT-qPCR analysis of normalized relative expression of selected 28up-felSC signature genes in control (untreated) and treated PD05 with 5-FU+lri. alone or in combination with verteporfin® at a final concentration of 0.2 mM (for each gene from left to right: control, IC20 and IC20+verteporfin®). (D) WB analysis of control (untreated with 5-FU+lri.) and treated TP53 wild type Ls174T colorectal cancer cells collected after 24 hours of 5-FU+lri. treatment alone ("-") or in combination with the YAP1 inhibitor verteporfin® at a final concentration of 5 mM ("+”).
Fig. 12. Kaplan-Meier representation of disease-free survival probability over time for patients from TCGA Stage I with high or low expression of the reduced signatures (A) 5up/4down TIMP2, TSPAN4, TUBB6, MRAS and ARL4C up and MYB, AGMAT, CDX and HOOK1 down. (B) rA 5up+3down. (C) rG 28up+8down. (D) 8up/8down.
Fig. 13. Kaplan-Meier representations of disease-free survival probability over time for patients with high or low expression of the reduced signatures selected according to the "Marisa”, "Jorissen” and "TCGA” colorectal cancer databases. (A) rA: TIMP2, TSPAN4, TUBB6, MRAS, ARL4C up and MYB, AGMAT, CDX down. (B) rB: TIMP2, TSPAN4 up and MYB, AGMAT down. (C) rC: TIMP2, TUBB6 up and MYB, HOOK1 down (D) rD: TIMP2, TSPAN4, TUBB6 up and MYB, HOOK down. (E) rE: TIMP2, TUBB6 up and MYB, AGMAT, HOOK1 down. (F) rF: TIMP2, TSPAN4, TUBB6 up and MYB, HOOK, AGMAT down. (G) rG 28up+8down. (H) rH: TIMP2, TSPAN4 up and MYB down. (I) rl: TIMP2 up and MYB, AGMAT down. (J) rJ: TIMP2, TUBB6 up and MYB down. (K) rK: TIMP2 up and MYB, HOOK down. (L) rL: TIMP2, TUBB6, TSPAN4 up and CDX1 down.
(M) rM: TIMP2, TSPAN4 up and CDX1 down; (N) 5up/4down: TIMP2, TSPAN4, TUBB6, MRAS, ARL4C up and MYB, AGMAT, CDX, HOOK1 down.(O) 8up/8down: TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1, TPM2 up and MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5, and SLC27A2 down,
Fig. 14. Kaplan-Meier representations of disease-free survival probability over time for patients classified according to a gene set enrichment score, of the reduced signatures, selected by combining the "Marisa”, "Jorissen” and "TCGA” colorectal cancer databases, d are subset of up genes and c2 are subset of down genes from the reduced signatures. Quartiles were used to define high and low groups. (A) rA TIMP2, TSPAN4, TUBB6, MRAS, ARL4C and MYB, AGMAT, CDX1. (B) rB TIMP2, TSPAN4 and MYB, AGMAT. (C) rC TIMP2, TUBB6 and MYB, HOOK1. (D) rD TIMP2, TSPAN4, TUBB6 and MYB, HOOK. (E) rE TIMP2, TUBB6 and MYB, HOOK1, AGMAT. (F) rF TIMP2, TSPAN4, TUBB6 and MYB, HOOK, AGMAT. (G) rG 28up+8down. (H) rH TIMP2, TSPAN4 and MYB. (I) rL TIMP2, TSPAN4, TUBB6 and CDX1. (J) rM TIMP2, TSPAN4 and CDX1. (K) 5up/4down TIMP2, TSPAN4, TUBB6, MRAS, ARL4C and MYB, AGMAT, CDX, HOOK1. (L) 8up/8down TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1, TPM2 and MYB, AGMAT, CDX, HOOK1, PDSS1, HUNK, KCNK5, SLC27A2. Fig. 15. Kaplan-Meier representations of disease-free survival probability over time for patients with high or low expression selected according to several ratios of the reduce signature rF TIMP2, TSPAN4, TUBB6 and MYB, HOOK, AGMAT in (A) Jorissen and (B) TCGA colorectal databases. Detailed description of the invention
All terms as used herein in this application, unless otherwise stated, shall be understood in their ordinary meaning as known in the art. Other more specific definitions for certain terms as used in the present application are as set forth below and are intended to apply uniformly throughout the specification and claims unless an otherwise expressly set out definition provides a broader definition. The definitions given herein are included for the purpose of understanding and expected to be applied throughout description, claims and drawings.
The present invention refers to an in vitro method for the prediction of the outcome in a subject suffering cancer, the method comprising the step of determining in an isolated sample from a subject the level of expression of at least one gene of Table 1, for example, the method comprising the step of determining in an isolated sample from a subject the level of expression of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
15, 17, 18, 17, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73,
74, 75, 76, 77, 78, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102,
103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123 or
124 genes of Table 1. For example, determining the level of expression of at least one gene (e.g., 1, 2, 3, 4, 5,
6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35 or
36 genes) selected from the group consisting of: TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1 , PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, RHOD, MYB, AGMAT, CDX1,
HOOK1 , PDSS1, HUNK, KCNK5 and SLC27A2, and any combinations thereof.
The term "outcome” means prognosis. The term "prognosis” is the natural evolution of the disease in terms of survival if there is no treatment in between.
The term "bad outcome” refers to recurrence, relapse, or progression of a cancer in a subject previously identified with the cancer. The term "good outcome” refers to no recurrence, or no relapse of the cancer after at least 4 years of follow-up in a subject previously identified with cancer. Bad outcome is, therefore, bad prognosis and good outcome is good prognosis.
In the present invention the genes cited herein in tables 1, 2 and 3 (see material and method section below) are described by their number identifier in the public data base Ensembl (European Molecular Biology Laboratory-European Bioinformatics Institute, EMBL-EBI) and Entrez ID from the National Center for Biotechnology Information (NCBI) at day 25 November 2020. Moreover, for the genes indicated in tables 4 and 5 GenBank® (NCBI) and UniProt (EMBL-EBI) references are provided for expression products of the genes (see the material and method section below) (reference number at day 25 November 2020).
The "feISC signature” as described herein is characterized by the detection of at least one gene of Table 1; e.g., the upregulation of at least one gene of table 2 and the down regulation of at least one gene of table 3; e.g., the upregulation of at least one gene of table 4 and the down regulation of at least one gene of table 5; e.g., the "28up/8down” signature, or the "8up/8down” signature, or the "5up/3down” signature explained in the present invention.
The first aspect of the invention refers to an in vitro method for the prediction of the outcome in a subject suffering cancer, the method comprising the step of: a. determining in an isolated sample of a subject the level of expression of
(a1) at least one gene selected from table 2 or any combination thereof, and
(a2) at least one gene selected from table 3 or any combination thereof.
In an embodiment of the first aspect of the invention, optionally in combination with any of the embodiments provided below, the method for the prediction of the outcome further comprises the step: b) determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2) (ratio level of expression of the genes determined in step (a1):level of expression of the genes determined in step (a2)).
In an embodiment of the first aspect of the invention, optionally in combination with any of the embodiments provided below, the method for the prediction of the outcome further comprises the step: b. determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2) (ratio level of expression of the genes determined in step (a1):level of expression of the genes determined in step (a2)); wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is, for example, higher than 1, for example is higher or equal to 1.01, and the subject is considered as having good outcome if the ratio obtained in step (b) is for example, lower than 1, for example, is lower or equal to 0.99.
It has been found that the risk of a bad outcome is directly proportional to the increase of the ratio obtained in step (b). This ratio can be considered as a hazard ratio, where patients scoring higher have a worst prognosis.
Alternatively, in another embodiment of the first aspect of the invention, optionally in combination with any of the embodiments provided below, the method for the prediction of the outcome in a subject suffering cancer, comprises the step: b. comparing the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of expression of the gene(s) of table 2 is higher, than the corresponding reference value, and wherein the level of expression of the gene(s) of table 3 is lower than the corresponding reference value.
In an embodiment of the first aspect of the invention, optionally in combination with any of the embodiments provided below, the method comprising the determination of the level of expression product of at least 1, 2, 3,
4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 17, 18, 17, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,
35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63,
64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92,
93, or 94 gene(s) selected from Table 2 and at least one gene selected from Table 3; or, alternatively, at least 1 gene selected from Table 2 and at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 17, 18, 17, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 gene(s) selected from Table 3, or any combinations thereof.
In an embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the gene(s) form table 2 is(are) selected from the group consisting of: TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, RHOD, and any combinations thereof.
In an embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, in the in vitro method for the prediction of the outcome the gene(s) form table 3 is(are) selected from the group consisting of: MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5, SLC27A2 genes, and any combinations thereof.
In an embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the in vitro method for the prediction of the outcome in a subject suffering cancer, wherein the method comprising determining in an isolated sample of a subject the level of expression of at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 genes) selected from the group consisting of: TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, RHOD (genes of table 4) and any combination thereof; and the level of expression of at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7 or 8 genes) selected from the group consisting of: MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 (genes of table 5) and any combination thereof. An embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein in step (a) it is determined the level of expression of:
(a1) at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 gene(s)) selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR,
S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, RHOD (genes of table 4) and any combination thereof; and (a2) at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8 gene(s)) selected from the group consisting of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5, SLC27A2 (genes of table 5) and any combination thereof.
In an embodiment of the first aspect of the invention, optionally in combination with any of the embodiments provided below, the method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), comprises the steps: a. determining in an isolated sample of a subject the level of expression of:
(a1) at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 gene(s)) selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN,
CXCL16, CD99L2, RHOD (genes of table 4) and any combination thereof; and (a2) at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7 or 8 gene(s)) selected from the group consisting of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5, SLC27A2 (genes of table 5) and any combination thereof; and b) determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2); wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2, or 1.22; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99, 0.95 or 0.90.
In another embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, in a subject suffering colorectal cancer (CRC), the method comprises an alternative step (b) which comprises comparing the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression of any of the gene(s)of step (a1) is higher (e.g., at least 2-fold higher), than the corresponding reference value, and wherein the level of the expression for each one of the genes of step (a2) is lower (e.g., at least 2-fold lower) than the corresponding reference value.
An embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC) wherein in step (a) it is determined the level of expression of:
(a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes (e.g. in combination with at least one of the other genes of table 4, e.g., in combination with 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22 or 23 gene(s) of table 4); and (a2) at least each one of MYB, AGMAT and CDX1 genes (e.g. in combination with at least one of the other genes of table 5, e.g. with 1, 2, 3, 4 or 5 gene(s) of table 5).
An embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC) comprising the following steps: a. determining in an isolated sample of a subject the level of expression of (a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes (e.g. in combination with at least one of the other genes of table 4, e.g., in combination with 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 or 23 gene(s) of table 4); and
(a2) at least each one of MYB, AGMAT and CDX1 genes (e.g. in combination with at least one of the other genes of table 5, e.g. with 1, 2, 3, 4 or 5 gene(s) of table 5); and b) determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2); wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99, 0.95 or 0.90.
This embodiment can comprise an alternative step (b) which compares the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes (e.g., also in combination with any other gene of table 4) is higher (e.g., at least 2-fold higher) than the corresponding reference value, and wherein the level of the expression of each one of MYB, AGMAT and CDX1 genes (e.g. also in combination with any other gene of table 5, is lower (e.g., at least 2-fold lower) with respect to the corresponding reference value.
An embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein in step (a) it is determined the level of expression of: (a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes (e.g., in combination with at least one of the other genes of table 4, e.g., in combination with 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 gene(s) of table 4); and (a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes. An embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), the method comprising the steps of: a. determining in an isolated sample of a subject the level of expression of
(a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes (e.g., in combination with at least one of the other genes of table 4, e.g., in combination with 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 gene(s) of table 4); and
(a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; and b. determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2); wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99, 0.95 or 0.90.
This embodiment can comprise an alternative step (b) which compares the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1, and TPM2 genes (e.g., also in combination with any other gene of table 4) is higher (e.g., at least 2-fold higher) than the corresponding reference value, and wherein the level of the expression of each one of MYB,
AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes is lower (e.g., at least 2-fold lower) with respect to the corresponding reference value.
An embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), the method comprising the step of: a. determining in an isolated sample of a subject the level of expression of
(a1) each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD genes; and
(a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes.
An embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), the method comprising the steps of: a. determining in an isolated sample of a subject the level of expression of
(a1) each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD genes; and (a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; and b. determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2); wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99, 0.95 or 0.90.
This embodiment can comprise an alternative step (b) which compares the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1,
SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2 and RHOD genes is higher (e.g., at least 2-fold higher), than the corresponding reference value, and wherein the level of the expression for each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes is lower (e.g., at least 2-fold lower) than the corresponding reference value.
Other embodiments of the first aspect of the invention, optionally in combination with any of the embodiments provided above or below, contemplate determining in step (a) the level of expression of the following combinations of genes (reduced signatures): (a1) at least TIMP2 and TUBB6, and (a2) at least one gene selected from MYB,CDX1, HOOK1, and any combination thereof
(a1) at least TIMP2 and TUBB6, and (a2) at least MYB or HOOK1.
(a1) at least TIMP2 and TUBB6, and (a2) at least MYB.
(a1) at least TIMP2, TUBB6, and TSPAN4, and (a2) at least MYB and HOOK1. (a1) at least TIMP2, TUBB6, and TSPAN4 and (a2) at least MYB, HOOK1 and AGMAT.
(a1) at least TSPAN4 and (a2) at least one gene selected from MYB.CDX1, HOOK1, and any combination thereof.
(a1) at least TIMP2, TUBB6, and TSPAN4 and (a2) at least CDX1.
(a1) at least TIMP2 and TSPAN4, and (a2) at least MYB. (a1) at least Tl MP2 and TSPAN4, and (a2) at least MYB and AGMAT.
(a1) at least TIMP2 and TSPAN4 and (a2) at least CDX1.
(a1) at least TIMP2 and (a2) at least MYB and AGMAT
(a1) at least TUBB6 and TIMP2 and (a2) at least MYB, HOOK1 and AGMAT.
(a1) at least TUBB6, TIMP2 and TSPAN4 and (a2) at least MYB, HOOK1 and AGMAT (a1) at least TIMP2" and (a2) at least MYB and HOOK1.
(a1) at least TSPAN4, TUBB6 and TIMP2, and (a2) at least MYB or CDX1.
(a1) at least TIMP2, TSPAN4, TUBB6, MRAS and ARL4C and (a2) at least MYB, AGMAT, HOOK1 and CDX1. As disclosed above for other embodiments of the first aspect, the method comprises determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2) of the reduced signatures, wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99, 0.95 or 0.90. Alternatively, step (b) may comprise comparing the level of the expression of each gene disclosed for the reduced signatures with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression for each one of the genes in (a1) is higher (e.g., at least 2-fold higher), than the corresponding reference value, and the level of the expression for each one of the genes in (a2) is lower (e.g., at least 2-fold lower) than the corresponding reference value.
For all the above embodiments where different set of genes are determined in step (a) of the method of the first aspect of the invention, a particular embodiment is contemplated in which step (b) comprises comparing the level of the expression of each gene determined in (a1) and (a2) with a corresponding reference value and, subsequently, determining a ratio between the level of expression of the genes determined in step (a1) as compared to their reference values and the genes determined in step (a2) as compared to their reference values, wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01 and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99. In one particular embodiment, step (b) comprises: (b1) calculating the mean relative expression of all the genes determined in (a1), (b2) calculating the mean relative expression of all the genes determined in (a2), and (b3) determining the ration between (b1) and (b2), i.e. (b1)/(b2). The relative expression is understood as the level of expression of the gene in the sample with respect to its corresponding reference value. More particularly, the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99, 0.95 or 0.90.
An embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein the method further comprises identifying the mutation status of TP53 gene (Gene ID: 7157) (ENSEMBL: ENSG0000014151 ), wherein the subject is considered as having bad outcome when the TP53 gene is the TP53 wild-type gene, or, alternatively, when the TP53 gene is a non-inactivating mutated TP53 (i.e., which does not lead to a loss of function of the p53). This method can also comprise the detection of the p53 protein mutational status, wherein when functional p53 protein (i.e., a p53 WT or a p53 with non-inactivating mutation) is detected is indicative of the subject having bad outcome.
This method can also refer to the method wherein the subject is considered as having bad outcome when an inactivating TP53 mutation (i.e., which lead to a p53 with loss of function) it is present in a low percentage of tumoral cells. An embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein the subject has received anti-cancer chemotherapy.
The term "reference value” in the context of the present invention is to be understood as a predefined level of expression product of the genes in a sample or group of samples. This value is used as a threshold to discriminate subjects wherein the condition to be analysed is present from those wherein such condition is absent. The samples are taken from a well-defined control subject or group of control subjects having no cancer, e.g., no CRC. The skilled person in the art, making use of the general knowledge, is able to choose the subject or group of subjects more adequate for obtaining the reference value. Methods for obtaining the reference value from the group of subjects selected are well known in the state of the art. In one embodiment of the present invention, the reference value is determined from a subject or group of subjects that do not suffer from cancer. In another embodiment the reference value is determined from a healthy subject or group of healthy subjects. In another embodiment the reference value is normal tissue, for example, adjacent normal tissue, from the same subject suffering the cancer (e.g., CRC). In another embodiment, the reference value is from a reference tumor (e.g., a CRC) that does not present the signature of the present invention. In a particular embodiment, the reference value is obtained from a group of CRC tumoral tissue samples. More particularly, the CRC tumoral tissue samples are from patients suffering colorectal cancer at the same stage as the patient whose prognosis is being determined.
An embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein the reference value is the level of expression of each gene in colorectal cancer tissue from a patient whose tumor does not relapse in the 4 first years of follow-up.
In the sense of the present invention, the expression "higher than a reference value” is understood as any increase in the level of expression product, for example at least 1.2-fold, or 1.5-fold increase of expression product with respect to the reference value. In particular embodiments, "higher than a reference value” is understood as at least 2-fold increase of expression product with respect to the reference value.
In the sense of the present invention, the expression "lower than a reference value” is understood as any decrease in the level of expression product, for example at least 1.2-fold, or 1.5-fold decrease of expression product with respect to the reference value. In particular embodiments, "lower than a reference value” is understood as at least 2-fold decrease of expression product with respect to the reference value.
In an embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the subject is considered as having bad cancer outcome if the level of expression of the gene(s) product(s) selected form table 2 or table 4 is at least 1.2-fold higher, 1.5-fold higher, 2-fold higher, 3-fold higher, 4-fold higher, 5-fold higher, 6-fold higher, 7-fold higher, 8-fold higher, 9-fold higher, or 10-fold higher with respect to a corresponding reference value; and/or wherein the level of expression of the gene(s) product(s) selected from table 3 or table 5 is lower, e.g. at least 1.2-fold lower, 1.5-fold lower, 2- fold lower, 3-fold lower, 4-fold lower, 5-fold lower, 6-fold lower, 7-fold lower, 8-fold lower, 9-fold lower, or 10- fold lower, with respect to a corresponding reference value. In another embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the subject is considered as having good outcome if the level of expression of the gene(s) of table 2 or table 4 is equal or lower, than the corresponding reference value, and wherein the level of expression of the gene(s) of table 3 or table 5 is equal or higher than the corresponding reference value.
Another embodiment of the first aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), wherein it compares the level of expression with a tumor that it is known to contain the signature of the present invention.
A second aspect of the invention refers to an in vitro method to determine the efficacy (i.e., efficiency or effectiveness) of an anti-cancer chemotherapy in a subject suffering cancer comprising the steps of:
(a) determining in an isolated sample of a subject before starting an anti-cancer chemotherapy and after the initiation of the anti-cancer chemotherapy the level of expression of
(a1) at least one gene selected from the group consisting of at least one gene selected from Table 2 (e.g., least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 17, 18, 17, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
90, 91, 92, 93, or 94 gene(s)) and
(a2) at least one gene selected from Table 3 (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 17, 18, 17, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 gene(s)) in an isolated sample from the subject, and any combinations thereof;
(b) ) optionally comprises determining a ratio between the level of expression of the gene(s) determined in step (a1) and the gene(s) determined in step (a2) before and after starting the anti-cancer chemotherapy, wherein, if the ratio of gene expression after starting the anti-cancer chemotherapy is higher than or equal to the ratio obtained before starting the anti-cancer chemotherapy this is indicative of the inefficiency of the anti cancer chemotherapy (thus, wherein, if the ratio of gene expression after starting the anti-cancer chemotherapy is lower than the ratio obtained before starting the anti-cancer chemotherapy this is indicative of the efficacy of the anti-cancer chemotherapy); alternatively, the efficacy of the anti-cancer chemotherapy can be performed by comparing the level of expression before and after starting the anti-cancer chemotherapy, wherein, if there is an increase between the level of the expression product of any gene of table 2 determined before starting the anticancer chemotherapy and there is a reduction between the level of the expression product of any gene of table 3 after starting the anticancer chemotherapy, this is indicative of the inefficiency of the anti-cancer chemotherapy (thus, if there is an decrease between the level of the expression product of any gene of table 2 determined before starting the anticancer chemotherapy and there is an increase between the level of the expression product of any gene of table 3 after starting the anticancer chemotherapy, this is indicative of the efficacy of the anti-cancer chemotherapy).
An anti-cancer chemotherapy is considered inefficient when the size of the tumor increases significantly (for example, a 20% or higher increase of its size in imaging tests) despite receiving the treatment. In the present invention, is understood as the inability of an anti-cancer chemotherapy to produce the desire beneficial effect.
All the embodiments of the first aspect of the invention also apply to the second aspect of the invention.
An embodiment of the second aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method to determine the efficacy of an anti-cancer chemotherapy in a subject suffering colorectal cancer (CRC) comprising the steps of:
(a) determining in an isolated sample of a subject before and after starting the anti-cancer chemotherapy the level of expression of
(a1) at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 gene(s)) selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD (genes of table 4) and any combination thereof; and
(a2) at least one gene (e.g., 1, 2, 3, 4, 5, 6, 7, 8 gene(s)) selected from the group consisting of: MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 (genes of table 5) and any combination thereof; or, alternatively,
(a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes ((e.g., in combination with at least one of the other genes of table 4, e.g., in combination with 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 gene(s) of table 4);); and (a2) at least each one of MYB, AGMAT and CDX1 genes (e.g., in combination with at least one of the other genes of table 5, e.g., in combination with 1, 2, 3, 4, 5 gene(s) of table 5); or, alternatively, (a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes (e.g., in combination with at least one of the other genes of table 4, e.g., in combination with 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 gene(s) of table 4); and (a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; or, alternatively,
(a1) each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN,
GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD genes; and (a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; and optionally, b) determining a ratio between the level of expression of the gene(s) determined in step (a1) and the gene(s) determined in step (a2) before and after starting the anti-cancer chemotherapy, wherein, if the ratio of gene expression after starting the anti-cancer chemotherapy is higher than the ratio obtained before starting the anti-cancer chemotherapy this is indicative of the inefficiency of the anti-cancer chemotherapy. Alternatively, step (b) can refer to comparing the level of the expression before and after starting the anti-cancer chemotherapy, wherein, if there is an increase between the level of the expression of any gene of table 4 (e.g., of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 or 23 gene(s)) determined after the initiation of the therapy in comparison with before starting the anti-cancer chemotherapy and there is a reduction between the level of the expression of any gene of table 5 (e.g., of 1, 2, 3, 4, 5, 6, 7 or 8 gene(s)) determined after in comparison with before starting the anti-cancer chemotherapy; or, alternatively, when there is an increase between the level of the expression of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes (e.g., also of any other gene of table 4) determined after in comparison with before starting the anti-cancer chemotherapy and there is a reduction between the level of expression of each one of MYB, AGMAT and CDX1 genes (e.g., also of any other gene of table 5) determined after in comparison with before starting the anti-cancer chemotherapy; or, alternatively, when there is an increase between the level of the expression of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes (e.g., also of any other gene of table 4) determined after in comparison with before starting the anti-cancer chemotherapy and there is a reduction in the level of expression of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes determined after in comparison with before starting the anti-cancer chemotherapy; or, alternatively, when there is an increase between the level of the expression of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD genes determined after in comparison with before starting the anti- cancer chemotherapy and there is a reduction in the level of expression of each one of MYB, AGMAT,
CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes determined after in comparison with before starting the anti-cancer chemotherapy, this is indicative of the inefficiency of the anti-cancer chemotherapy. Other embodiments of the second aspect of the invention, optionally in combination with any of the embodiments provided above or below, contemplate determining in step (a) the level of expression of the following combinations of genes (reduced signatures):
(a1) at least TIMP2 and TUBB6, and (a2) at least one gene selected from MYB.CDX1, HOOK1, and any combination thereof
(a1) at least TIMP2 and TUBB6, and (a2) at least MYB or HOOK1.
(a1) at least TIMP2 and TUBB6, and (a2) at least MYB.
(a1) at least TIMP2, TUBB6, and TSPAN4, and (a2) at least MYB and HOOK1.
(a1) at least TIMP2, TUBB6, and TSPAN4 and (a2) at least MYB, HOOK1 and AGMAT. (a1) at least TSPAN4 and (a2) at least one gene selected from MYB.CDX1, HOOK1, and any combination thereof.
(a1) at least TIMP2, TUBB6, and TSPAN4 and (a2) at least CDX1.
(a1) at least TIMP2 and TSPAN4, and (a2) at least MYB.
(a1) at least TIMP2 and TSPAN4, and (a2) at least MYB and AGMAT. (a1) at least TIMP2 and TSPAN4 and (a2) at least CDX1.
(a1) at least TIMP2 and (a2) at least MYB and AGMAT
(a1) at least TUBB6 and TIMP2 and (a2) at least MYB, H00K1 and AGMAT.
(a1) at least TUBB6, TIMP2 and TSPAN4 and (a2) at least MYB, H00K1 and AGMAT (a1) at least TIMP2" and (a2) at least MYB and H00K1.
(a1) at least TSPAN4, TUBB6 and TIMP2, and (a2) at least MYB or CDX1.
(a1) at least TIMP2, TSPAN4, TUBB6, MR AS and ARL4C and (a2) at least MYB, AGMAT, H00K1 and CDX1. As disclosed above for other embodiments of the first aspect, the method comprises determining in a step b) a ratio between the level of expression of the gene(s) determined in step (a1) and the gene(s) determined in step (a2) before and after starting the anti-cancer chemotherapy, wherein, if the ratio of gene expression after starting the anti-cancer chemotherapy is higher than the ratio obtained before starting the anti-cancer chemotherapy this is indicative of the inefficiency of the anti-cancer chemotherapy. Alternatively, step (b) can refer to comparing the level of the expression before and after starting the anti-cancer chemotherapy, wherein, if there is an increase between the level of the expression of each of the genes in (a1) determined after the initiation of the therapy in comparison with before starting the anti-cancer chemotherapy and there is a reduction between the level of the expression of each of the genes in (a2) determined after in comparison with before starting the anti-cancer chemotherapy, this is indicative of the inefficiency of the anti-cancer chemotherapy. In particular embodiments of the second aspect, step (b) comprises determining a ratio between the level of expression of the genes determined in step (a1) after starting the anti-cancer chemotherapy as compared to their level of expression before the anti-cancer therapy and the genes determined in step (a2) after starting the anti-cancer chemotherapy as compared to their level of expression before the anti-cancer therapy, wherein anti-cancer chemotherapy is considered to be ineffective if the ratio is higher than or equal to 1.01. In one particular embodiment, step (b) comprises: (b1) calculating the mean relative expression of all the genes determined in (a1), (b2) calculating the mean relative expression of all the genes determined in (a2), and (b3) determining the ratio between (b1) and (b2), i.e. (b1)/(b2). The relative expression is understood, in this case, for the second aspect of the invention, as the level of expression of the gene in a sample obtained from the patient after the anti-cancer treatment with respect to the level of expression of the same gene in a sample obtained from the patient before the anti-cancer treatment. More particularly, the anti-cancer therapy is considered to be ineffective if the ratio obtained in step (b) is higher than or equal to 1.01, 1.05, 1.10, 1.2 or 1.22.
An embodiment of the second aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to the in vitro method to determine the efficacy of an anti cancer chemotherapy in a subject suffering colorectal cancer (CRC), wherein the method further comprises identifying the TP53 (Gene ID: 7157; ENSEMBL: ENSG0000014151; identifiers at day 25 November 2020) mutational status wherein when TP53 wild-type gene is determined, or, alternatively, when the TP53 gene is a non-inactivating mutated TP53 (i.e., which does not lead to a loss of function of the p53 protein) this is indicative of the inefficiency of the anti-cancer chemotherapy. This method can also comprise the detection of the p53 protein mutational status, wherein when functional p53 protein is detected is indicative of the inefficiency of the anti-cancer chemotherapy. This method can also refer to the method wherein when an inactivating TP53 mutation it is present in a low percentage of tumoral cells, this is indicative of the inefficiency of the anti-cancer chemotherapy.
An embodiment of the second aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to the in vitro method to determine the efficacy of an anti cancer chemotherapy in a subject suffering cancer (e.g., CRC) wherein the time after starting the anti-cancer chemotherapy is at least after 4-6 cycles of chemotherapy treatment, for example, after 2-3 months after initiating the anti-cancer chemotherapy.
An embodiment of the second aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to the in vitro method to determine the efficacy of an anti cancer chemotherapy in a subject suffering cancer (e.g., CRC) wherein the time after starting the anti-cancer chemotherapy is at any time after the completion of said chemotherapy treatment.
The second aspect of the invention is also understood as an in vitro method to determine the efficacy of an anti-cancer chemotherapy in a subject suffering colorectal cancer (CRC) wherein in step (a) the determination of the level of expression in an isolated sample of a subject is performed comparing the level of expression in an intermediate time point during an anti-cancer chemotherapy and the level of expression in a posterior time point after starting said anti-cancer chemotherapy.
In an embodiment of the first and second aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the anti-cancer chemotherapy is selected from the group consisting of fluoropyrimidine (for example, 5-fluorouracile and/or capecitabine), oxaliplatin, irinotecan and any combination thereof, for example, 5-fluorouracile and irinotecan, for example, as commonly used to treat CRC patients. In another embodiment, the anticancer chemotherapy is combined with any chemotherapy of biological drug used to treat CRC patients, for example, is combined with an antiangiogenic drug (e.g., bevacizumab y aflibercept) and/or an EGFR inhibitor (e.g., cetuximab y panitumumab).
A third aspect of the invention refers to an in vitro method for deciding or recommending a medical regime to a subject suffering cancer the method comprising:
(a) predicting the outcome of the subject suffering cancer by the method of the first aspect of the invention, or, alternatively, determining the efficacy of an anti-cancer chemotherapy by the method of the second aspect of the invention, and
(b) recommending a therapeutic medical regime if the subject is predicted to have bad outcome, or, alternatively, recommending an alternative medical regime if the anti-cancer chemotherapy is ineffective. All the embodiments of the first and second aspect of the invention also apply to the third aspect of the invention. An embodiment of the third aspect of the present invention, optionally in combination with any of the embodiments provided above or below, refers to an in vitro method for deciding or recommending a medical regime to a subject suffering colorectal cancer (CRC) the method comprising:
(a) predicting the outcome of the subject suffering colorectal cancer by the method of the first aspect of the invention, or, alternatively, determining the efficacy of an anti-cancer chemotherapy of the second aspect of the invention and
(b) recommending a therapeutic medical regime if the subject is predicted to have bad outcome, or, alternatively, recommending an alternative medical regime if the anti-cancer chemotherapy is ineffective. In an embodiment of the third aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the medical regime decided or recommended is chemotherapy (for example, FOLFOX4, mFOLFOX6, FOLFIRI, CAPOX, FLOX, or de Gramont regime) combined with a YAP1 inhibitor, e.g., porphyrin compounds such as Verteporfin®, protoporphyrin ix or hematoporphyrin; e.g., Verteporfin®; e.g., is 5FU and irinotecan combined with Verteporfin®.
In an embodiment of the third aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the medical regime decided or recommended is surgery, a different anti-cancer chemotherapy, a different chemotherapy regime using the same anti-cancer chemotherapy, radiation therapy, immunotherapy, targeted therapy hormone therapy or any combination thereof. In another embodiment, the anti-cancer treatment is selected from the above-mentioned options based on type and stage of cancer, the results of clinical trials as well as histopathologic findings.
In an embodiment of the third aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the medical regime decided or recommended is not a senolytic drug.
In an embodiment of the first, second or third aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the subject is suffering colorectal cancer at stages II or III.
In an embodiment of the first, second or third aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the level of expression of the gene is determined by measuring or determining the amount of corresponding mRNA or protein (e.g., full-length protein product or a proteolytic fragment thereof), depending on the detection technique to be used.
Determining the amount of mRNA can be performed by any method known to the skilled person, provided that said method permits the detection and quantification of mRNA in a biological sample. Included among the examples of these procedures are PCR, quantitative real-time PCR (QPCR), multiplex PCR, NASBA, LCR, RT-PCR, RNA sequencing, array hybridization or "Northern" transfer, or combinations of these.
In an embodiment of the first, second or third aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the level of expression of the gene is determined (quantified) by measuring the amount of mRNA by a nucleic acid amplification-based technique (e.g., PCR, RT-PCR, quantitative PCR (qPCR), or quantitative RT-PCR (qRT-PCR or RT-qPCR)).
In an embodiment of the first, second or third aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the level of expression of the gene is determined (quantified) by measuring the amount of mRNA by qRT-PCR.
Alternatively, in another embodiment of any of the methods provided by the present invention, optionally in combination with any of the embodiments provided above or below, it is determined the amount of mRNA for each one of the gene markers provided by the invention via a hybridization technique, employing oligonucleotide probes.
When using mRNA, the method may be carried out by combining isolated mRNA with reagents to convert to cDNA according to standard methods well known in the art, treating the converted cDNA with amplification reaction reagents (such as cDNA PCR reaction reagents) in a container along with an appropriate mixture of nucleic acid primers; reacting the contents of the container to produce amplification products; and analyzing the amplification products to detect the presence of one or more of the cancer markers in the sample. The analysis step may be further accomplished by quantitatively detecting the presence of polynucleotide cancer markers in the amplification product and comparing the quantity of marker detected against a panel of expected values for the known presence or absence of such markers in normal and malignant tissue derived using similar primers.
The present invention optionally requires performing a ratio between the level of expression of any gene of table 2 and of table 3; or, alternatively, a ratio between the level of expression of any gene of table 4 and of table 5; or, alternatively, a ratio between the level of expression of the genes of any gen of step (a1) and of step (a2) of the above-mentioned methods of the invention. In a preferred embodiment, the ratio is performed by performing the arithmetic mean of the level of expression of a subset of genes of table 2 divided by the arithmetic mean of the level of expression of a subset of genes of table 3, or alternatively, by performing the arithmetic mean of the level of expression of a subset of genes of table 4 divided by the arithmetic mean of the level of expression of a subset of genes of table 5.
The present invention optionally requires comparing the level of expression of the genes with a reference value. The reference value, as mentioned above, is obtained from a control subject or group of control subjects or is a normal tissue, for example, adjacent normal tissue from the same subject suffering the cancer (e.g., CRC) or is a reference tumor (e.g., a CRC) that does not present the signature of the present invention. The skilled person may use any available method to establish the described comparison. For instance, as method of relative quantification, the 2-MCt of Livak and Schmittgen may be employed (Methods, 2001 vol. 25, issue 4, p.402-8).
In another embodiment, microarrays are used which include one or more probes corresponding to one or more of biomarkers identified in Tables 1, 2, 3, 4 or 5. This method results in the production of hybridization patterns of labeled target nucleic acids on the array surface. The resultant hybridization patterns of labeled nucleic acids may be visualized or detected in a variety of ways, with the particular manner of detection selected based on the particular label of the target nucleic acid. Representative detection means include scintillation counting, autoradiography, fluorescence measurement, calorimetric measurement, light emission measurement, light scattering, and the like.
In an embodiment of the first, second or third aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the level of expression of the gene is determined by the detection and/or quantification of the protein, e.g., by a specific antibody or a fragment thereof able to bind to the target protein(s). In an embodiment the expression product of the genes which is determined in the context of the present invention is the full-length protein encoded by the genes, or a fragment of said protein. In particular embodiment of the methods provided by the present invention, the level of the protein markers or fragments thereof is determined by a quantitative test selected from the group consisting of an immunological test, bioluminescence, fluorescence, chemiluminescence, electrochemistry and mass spectrometry.
In an embodiment of the first, second or third aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the proteins and/or mRNAs to be determined are those shown in table 6 (identified with their GenBank® and/or UniProt reference number on day 25 November 2020).
In one embodiment the level of encoded protein or fragment thereof is detected by mass spectrometry, for example, by Shotgun Liquid Chromatography Mass Spectrometry (LC-MS/MS) or Multiple reaction monitoring (MRM) mass spectrometry, immunochemistry or by an immunoassay.
The term "immunochemistry" as used herein refers to a variety of techniques for detecting antigens (in the present case any of the proteins encoded by the above genes or antigenic fragments thereof) in a sample by exploiting the principle of antibodies binding specifically to the target protein(s). Visualizing an antibody- antigen interaction can be then accomplished in a number of ways, usually by conjugating the antibody to an enzyme, such as peroxidase, that can catalyse a colour-producing reaction, or to a fluorophore, such as fluorescein or rhodamine. The immunochemistry technique can be direct or indirect. Suitable immunoassay procedures include enzyme-linked immunosorbent assays (ELISA, such as multiplex ELISA), enzyme immunodot assay, agglutination assay, antibody-antigen-antibody sandwich assay, antigen- antibody-antigen sandwich assay, immunocromatography, or other immunoassay formats well-known to the ordinarily skilled artisan, such as radioimmunoassay, as well as protein microarray formats. In one embodiment, the level of the protein is determined by an immunoassay. In another embodiment, the level of expression of protein is determined by ELISA.
The term "antibody or a fragment thereof able to bind to the target protein(s)" is to be understood as any immunoglobulin or fragment thereof able to selectively bind the target protein(s) referred in the aspects and embodiments of the present invention. It includes monoclonal and polyclonal antibodies. The term "fragment thereof encompasses any part of an antibody having the size and conformation suitable to bind an epitope of the target protein. Suitable fragments include F(ab), F(ab') and Fv. An "epitope" is the part of the antigen being recognized by the immune system (B-cells, T-cells or antibodies).
In an embodiment of the first, second or third aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the mRNA and/or protein is at least one of the mRNA or protein described in table 6, or any combinations thereof.
The present invention also refers to a method of treatment of a subject suffering cancer (e.g., CRC) in need thereof, the method comprising:
(a) predicting the outcome of the subject suffering cancer (e.g., CRC) by the method of the first aspect of the invention, or, alternatively, determining the efficacy of an anti-cancer chemotherapy by the method of the second aspect of the invention, and
(b) treating the subject when it is predicted to have bad outcome, or, alternatively, when the anti cancer chemotherapy is considered ineffective, with a treatment comprising an anti-YAP1 inhibitor, for example, with a porphyrin compound such as Verteporfin®, protoporphyrin ix or hematoporphyrin, for example with Verteporfin®.
This method named herein as the "fourth method of the present invention”.
All the embodiments of the first, second and third aspect of the invention also apply to the fourth method of the invention.
In an embodiment of the fourth method of the invention, optionally in combination with any of the embodiments provided above or below, the cancer is CRC and the CRC contains TP53 wild type gene, or a non inactivating TP53 mutation (i.e., which does not lead to a loss of function of the p53 protein) or a TP53 mutation that is present in a low percentage of tumoral cells. This method can also comprise the detection of the p53 protein mutational status, wherein when functional p53 protein is detected is indicative of the inefficiency of the anti-cancer chemotherapy, or the anti-cancer chemotherapy is considered ineffective. In an embodiment of the fourth method of the invention, optionally in combination with any of the embodiments provided above or below, the treatment provided in step (b) is chemotherapy (for example, FOLFOX4, mFOLFOX6, FOLFIRI, CAPOX, FLOX, or de Gramont regime) combined with a YAP1 inhibitor, e.g., porphyrin compounds such as Verteporfin®, protoporphyrin ix or hematoporphyrin ; e.g., Verteporfin®; e.g., is 5FU and irinotecan combined with Verteporfin®.
In an embodiment of the fourth method of the invention of the present invention, optionally in combination with any of the embodiments provided above or below, alternatively, the treatment provided in step (b) is surgery, a different anti-cancer chemotherapy, a different chemotherapy regime using the same anti-cancer chemotherapy, radiation therapy, immunotherapy, targeted therapy hormone therapy or any combination thereof. In another embodiment, the anti-cancer treatment is selected from the above-mentioned options based on type and stage of cancer, the results of clinical trials as well as histopathologic findings.
In an embodiment of the first, second or third aspect of the present invention and the fourth method of the present invention, optionally in combination with any of the embodiments provided above or below, the sample is an isolated tissue sample, or a or a biological fluid sample (e.g., blood, plasma, serum, ascitic fluid, broncoalveolar lavage, and urine).
In an embodiment of the first, second or third aspect of the present invention and the fourth method of the present invention, optionally in combination with any of the embodiments provided above or below, the sample is an isolated colon tissue sample, a rectal tissue sample, a biological fluid sample (for example, blood, serum or plasma), or a stool sample.
In an embodiment of the first, second or third aspect of the present invention and the fourth method of the present invention, optionally in combination with any of the embodiments provided above or below, the sample is a tissue sample or a biological fluid sample suspected to contain tumoral cells, in particular a CRC tissue sample.
In an embodiment of the first, second or third aspect of the present invention and the fourth method of the present invention, optionally in combination with any of the embodiments provided above or below, the sample is fresh, frozen, fixed or fixed and embedded in paraffin; in an example, the sample is a paraffin embedded cancer tissue.
In the present invention the patient is a mammal, preferably is a human. The patient can be of any age, gender or race.
In an embodiment of the first, second or third aspect of the present invention and the fourth method of the present invention, optionally in combination with any of the embodiments provided above or below, the CRC is a colon or rectum adenocarcinoma. The present invention also refers to a kit that comprises means for predicting the outcome of a subject suffering CRC by the method of the first aspect of the invention, or for determining the efficacy of an anti cancer chemotherapy in a subject suffering CRC by the method of the second aspect of the invention, or for deciding or recommending a medical regime to subject suffering CRC by the method of the third aspect of the invention, the kit comprising means for determining the level of expression of at least one (e.g., of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 or 23 gene(s)) of the genes in table 4 and at least one (e.g., of 1, 2, 3, 4, 5, 6, 7, 8 gene(s)) of the genes in table 5; or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes (optionally in combination with at least any other gene of table 4), and of an expression product of each one of MYB, AGMAT and CDX1 genes (optionally in combination with at least any other gene of table 5); or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes (optionally in combination with at least any other gen of table 4), and of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP,
ABHD4, GSN, CXCL16, CD99L2, and RHOD genes, and of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes.
The kit can also comprise instructions (such as a leaflet) with the indication for performing the first, second, or third aspects or the fourth method of the present invention.
The kit can also comprise a reference sample, for example, a positive control (a sample from a tumor (e.g., CRC) with the signature of the present invention) and/or a negative control (for example from a normal tissue, or a reference tumor (e.g., a CRC) that does not present the signature of the present invention).
A fourth aspect of the invention refers to a use of a kit for predicting the outcome of a subject suffering CRC by the method of the first aspect of the invention, or for determining the efficacy of an anti-cancer chemotherapy in a subject suffering CRC by the method of the second aspect of the invention, or for deciding or recommending a medical regime to subject suffering CRC by the method of the third aspect of the invention, the kit comprising means for determining the level of expression of at least one (e.g., of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 or 23 gene(s)) of the genes in table 4 and at least one (e.g., of 1, 2, 3, 4, 5, 6, 7, 8 gene(s)) of the genes in table 5; or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes (optionally in combination with at least any other gene of table 4), and of an expression product of each one of MYB, AGMAT and CDX1 genes (optionally in combination with at least any other gene of table 5); or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes (optionally in combination with at least any other gen of table 4), and of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1 , PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD genes, and of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes.
The nature of the means depends on the technique selected to identify the gene. Details about their nature have been provided above (primers, probes, antibodies, and fluorescent dyes, among others). The kit may additionally comprise further means (additives, solvents) to visualize the interactions (dipsticks, chemiluminescent reagents, turbidimetric reagents, etc.). Suitable additives, solvents and reagents to visualize the identification are disclosed in the examples. In an embodiment of the fourth aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the antibodies and/or primers as specific for the protein and/or mRNA, respectively, of any one of the products of expression included in table 6 of the present invention.
In an embodiment of the fourth aspect of the present invention, optionally in combination with any of the embodiments provided above or below, the antibodies and/or primers as specific for the protein and/or mRNA, respectively, of any one of the products of expression included in table 6 of the present invention. For example, the primers can be at least one pair of primers disclosed in table 8 of the present invention.
The fifth aspect of the invention refers to a combined use of an expression product of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes, and of an expression product of each one of MYB, AGMAT and CDX1 genes; or, alternatively, of a combined use of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes, and of an expression product of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; or, alternatively, a combined use of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD genes, and of an expression product of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; as a marker of prediction of progression of CRC or of determining the efficacy of an anti-cancer chemotherapy in a subject suffering CRC or of deciding or recommending a medical regime in a subject suffering CRC.
Another aspect of the invention refers to the use of the ratio of the level of expression of an expression product of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes, and the level of expression of an expression product of each one of MYB, AGMAT and CDX1 genes; or, alternatively, to the use of the ratio of the level of expression of an expression product of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes, and the level of expression of an expression product of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; or, alternatively to the use of the ratio of the level of expression of an expression product of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD genes, and the level of expression of an expression product of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; as a marker of prediction of progression of CRC or of determining the efficacy of an anti-cancer chemotherapy in a subject suffering CRC or of deciding or recommending a medical regime in a subject suffering CRC.
The in vitro methods of the invention provide prognostic information, information for determining the efficacy of an anti-cancer chemotherapy or information for deciding or recommending a medical regime. In one embodiment, the methods of the invention further comprise the steps of (i) collecting said information, and (ii) saving the information in a data carrier.
In the sense of the invention a "data carrier” is to be understood as any means that contain meaningful information data for the prognosis of cancer, such as paper. The carrier may also be any entity or device capable of carrying the prognosis data. For example, the carrier may comprise a storage medium, such as a ROM, for example a CD ROM or a semiconductor ROM, or a magnetic recording medium, for example a floppy disc or hard disk. Further, the carrier may be a transmissible carrier such as an electrical or optical signal, which may be conveyed via electrical or optical cable or by radio or other means. When the prognosis data are embodied in a signal that may be conveyed directly by a cable or other device or means, the carrier may be constituted by such cable or other device or means. Other carriers relate to USB devices and computer archives. Examples of suitable data carrier are paper, CDs, USB, computer archives in PCs, or sound registration with the same information.
Throughout the description and claims the word "comprise" and variations of the word, are not intended to exclude other technical features, additives, components, or steps. Furthermore, the word "comprise” encompasses the case of "consisting of”. Additional objects, advantages and features of the invention will become apparent to those skilled in the art upon examination of the description or may be learned by practice of the invention. The following examples and drawings are provided by way of illustration, and they are not intended to be limiting of the present invention. Reference signs related to drawings and placed in parentheses in a claim, are solely for attempting to increase the intelligibility of the claim, and shall not be construed as limiting the scope of the claim. Furthermore, the present invention covers all possible combinations of particular and preferred embodiments described herein.
Examples
MATERIAL AND METHODS:
MATERIALS:
Animal studies Fragments of human colorectal carcinoma tumors from stage II and III obtained from Parc de Salut MAR Biobank (MARbiobank) with the informed consent of patients and following all recommendations of Hospital del Mar' Ethics Committee, the Spanish regulations, and the Helsinki declaration's Guide were transplanted and expanded in the cecum of nude mice (NU/J (Foxn1m) (JAX: 002019)) as orthoxenografts. In all our procedures, animals were kept under pathogen-free conditions, and animal work was conducted according to the guidelines from the Animal Care Committee at the Generalitat de Catalunya. The Committee for Animal Experimentation at the Institute of Biomedical Research of Bellvitge (Barcelona) approved these studies.
Patient-derived organoids and culture conditions Samples from patients (human colorectal carcinoma tumors from stage II and III) were kindly provided by MARBiobank and IdiPAZ Biobank, integrated in the Spanish Hospital Biobanks Network (RetBioH; "redbiobancos”). Informed consent was obtained from all participants and protocols were approved by institutional ethical committees. For patient-derived organoids (PDOs) generation, primary or xenografted human colorectal tumors were disaggregated in 1.5 mg/mL collagenase II and 20 pg/mL hyaluronidase after 40min of incubation at 37°C, filtered in 100 pm cell strainer and seeded in 50 pL Matrigel in 24-well plates, as previously described (Sato et al., 2011). After polymerization, 450 pL of complete medium was added (DMEM/F12 plus penicillin (100 U/mL) and streptomycin (100 pg/mL), 100 pg/mL Primocin, 1X N2 and B27, 10mM Nicotinamide; 1.25 mM N-Acetyl-L-cysteine, 100 ng/mL Noggin and 100 ng/mL R-spondin-1, 10 pM Y- 27632, 10 nM PGE2, 3 pM SB202190, 0.5 pM A-8301, 50 ng/mL EGF and 10 nM Gastrin I). Tumour spheres were collected and digested with an adequate amount of trypsin to single cells and re-plated in culture. Cultures were maintained at 37°C, 5% C02 and medium changed every week. PDOs were expanded by serial passaging and kept frozen in liquid Nitrogen for being used in subsequent experiments. Mutations for certain genes, including TP53, (see Table 7) in the PDOs were studied using lllumina® platform following manufacturer's instructions. In table 7 the corresponding chemotherapy concentrations that reduced a 20 and 30% of the cell growth (IC2oand IC30, respectively) are indicated for each PDO. Patient-derived organoids (PDO) PD04, PD05, PD08, PDO10, PD011 and PD015were deposited at MARBiobancfrom Hospital del Mar (Barcelona). Patient- derived organoid 66 (PDO66) was kindly provided by Alberto Munoz Lab (Fernandez-Barral etal., 2020).
Cell lines CRC cell lines HCT116 and Ls174T (KRAS mutated and TP53 WT), SW480 (KRAS and TP53 mutated) and HT29 (BRAF and TP53 mutated) were obtained from the American Type Culture Collection (ATCC, USA). All cells were grown in Dulbecco's modified Eagle's medium (Invitrogen) plus 10% fetal bovine serum (Biological Industries) and were maintained in a 5% CO2 incubator at 37°C. 5-FU+lri. concentrations that reduced 30% of each cell growth were as follows: HCT116, 0.01 pg/mL 5-FU and 0.004 pg/mL Iri.; Ls174T, 0.025 pg/mL 5-FU and 0.01 pg/mL Iri.; SW480, 0.28 pg/mL 5-FU and 0.11 pg/mL Iri.; HT29, 0.33 pg/mL 5-FU and 0.13 pg/mL Iri.
Human colorectal samples
Formalin-fixed, paraffin-embedded tissue blocks of gastrointestinal and colorectal tumor samples from stage II and stage II, from patients at diagnosis and after neoadjuvant therapy at the time of surgery, were obtained from Parc de Salut Mar Biobank (MARBiobank, Barcelona). Samples were retrieved under informed consent and approval of the Tumor Bank Committees according to Spanish ethical regulations and the guidelines of the Declaration of Helsinki. Patient identity for pathological specimens remained anonymous in the context of this study. Patient data was collected and immunohistochemistry (IHC) analyses were performed as described below in the method section.
Reagents, antibodies and software
Antibodies used: Mouse monoclonal anti-p53 DO-1 (ab1101) (RRID:AB_297667), Rabbit monoclonal anti-p21 [EPR362] (ab 109520) (RRI D : AB_10860537), Rabbit monoclonal anti-CKN2A/p16INK4a [EPR1473] (ab108349) (RRI D : AB_10858268) , Rabbit polyclonal anti-CD99L2 (ab224164), Mouse monoclonal anti-
TIMP2 [3A4] (ab1828) (RRID:AB_2256129), Rabbit polyclonal anti-MRas (ab26303) (RRID:AB_470849), Anti- TUBB6 (PA5-P8948), Recombinant Anti-ICAMI antibody [EPR4776] (ab109361) (RRI D : AB_10958467) , Recombinant Anti-Hsp47 antibody [EPR4217] (ab109117) (RRI D : AB_10888995), Recombinant Anti-YAP1 antibody [EP1674Y] (ab52771) (RRID:AB_2219141), Anti-Histone H3 antibody-Nuclear Marker and ChIP Grade (ab791) (RRID:AB_302613) and Anti-Histone H4 antibody-ChIP Grade (ab1015) (RRID:AB_296888) from Abeam. Mouse monoclonal anti-yH2AX (pS139) (564719) (RRID:AB_2738913) from BD, Biosciences; Mouse monoclonal anti-Ki67 (MM1) (NCL-Ki67-MM1) (RRI D : AB_442101) from Leica Biosystems; Rabbit polyclonal anti-Cleaved Caspase-3 (Asp175) (9661) (RRID:AB_2341188) from Cell Signaling; Goat polyclonal anti-EphB2 (AF467) (RRID:AB_355375) from RD Systems; TSPAN4 Polyclonal Antibody (PA5-69344) (RRID:AB_2688603) from Thermo Fisher Scientific; Monoclonal Anti-S100A4 antibody produced in mouse
(AMAB90599) (RRID:AB_2665603) from Atlas Antibodies; Mouse monoclonal anti-alpha-Tubulin (B-5-1-2) (T607) (RRID:AB_477582) from Sigma-Aldrich.
Chemicals, Peptides, and Recombinant Proteins used: Collagenase II from Clostridium histolyticum (Cat#C6885), Hyaluronidase from bovine testes (Cat#H3506), Nicotinamide (Cat#N3376), N-Acetyl-L-cysteine
(Cat#A7250), Y-27632 dihydrochloride (ROCK inhibitor) (Cat#Y0503), SB 202190 (Cat#S7067), A8301 (ALK inhibitor) (Cat#SML0788), hEGF (Cat#E9644) and DPX mountant (Cat#06522) from Sigma-Aldrich. DMEM/F- 12 Advanced (Cat#12634028), B-27 Supplement (50X) (Cat#17504044) and N-2 supplement (100X)
(Cat#17502048) from Gibco. Primocin (Cat#ant-pm-1) from Invitrogen. Recombinant Human Noggin (Cat#120- 10C) and Recombinant Human R-Spondin-1 (Cat#120-38) from PeproTech. Prostaglandin E2 (Cat#2296) and Gastrin I (human) (Cat#3006) from Tocris. Corning Matrigel Basement Membrane Matrix, LDEV-free (Cat#354234) from Corning. 5-Fluorouracil (5-FU or 5FU) (Cat#606544.3) and Irinotecan (Cat#713386.5) (“Iri" or “Iri.") from Accord Healthcare. D-Luciferin (Cat#LUCK) from Goldbio. PhosSTOP phosphatase inhibitor cocktail (Cat#PHOSS-RO) and Complete Mini protease inhibitor cocktail (Cat#11836170001) from Roche. DAPI Fluoromount-G (Cat#0100-20) from Southern Biotech. Protein A- Sepharose CL-4B (Cat#17-0780-01) and Protein G-Sepharose 4 Fast Flow (Cat#17-0618-01) from GE Healthcare.
Critical Commercial Assays used: Dako Envision+ System-HRP Labelled Polymer anti-Rabbit (Cat#K4003), Envision+ System-HRP Labelled Polymer anti-Mouse (Cat#K4001) and Dako Liquid DAB+ Substrate Chromogen System (Cat#K3468) from Agilent. TSA Plus Cyanine 3/Fluorescein System (Cat#NEL753001KT) from PerkinElmer. EZ-ECL Chemiluminescence Detection Kit for HRP (Cat#20-500-120) from Biological Industries. ECL Prime Western Blotting System (Cat#RPN2232) and RT-First Strand cDNA Synthesis Kit (Cat#27-9261-01) from GE Healthcare. CellTiter-Glo Luminescent Cell Viability Assay (Cat#G7571) from
Promega. APC BrdU Flow Kit (Cat#552598), from BD Biosciences. Senescence b-Galactosidase Staining Kit (Cat#9860S) from Cell Signaling. Cell Event Senescence Green Flow Cytometry Assay KiT (Cat#C10840) and Annexin V Apoptosis Detection Kit APC (Cat#88-8007) from Invitrogen. CometAssay Kit (Cat#4250-050- K) from Trevigen. RNeasy Micro Kit (Cat#74004) from Qiagen. SYBR Green I Master Kit (Cat#04887352001) from Roche. Lenti-X Concentrator (Cat#631232) from Clontech.
Experimental Models: Mouse: NU/J (Foxn1m) (JAX: 002019) and NOD-sc/cf gamma (NSG) (JAX:005557) from The Jackson Laboratory. Recombinant DNA: pMD2.G plasmid (Addgene plasmid #12259) from Trono Lab pCMV-dR8.2 dvpr plasmid (Addgene plasmid #8455) from Stewart et al., 2003, lentiCRISPR v2 plasmid (Addgene plasmid #52961) from Sanjana etal., 2014, pLEX-hFLiG plasmid gift from Toni Celia-Terrassa (Celia-Terrasa & Kang, 2018) Lab and pLTPC-H2BeGFP plasmid gift from Hector G. Palmer Lab. Software and algorithms: GraphPad Prism (RRID: SCR_002798) from Graphpad Software. Fiji (Image J) (RRID: SCR_002285) from Schneider etal., 2012. Benchling CRISPR design (RRID: SCR_013955) from Benchling. FlowJo 10.6.2 (RRID: SCR_008520) from BD Biosciences. LightCycler Software (RRID: SCR_012155) from Roche. Adobe Photoshop (RRID: SCR_014199) from Adobe Software. R Project for Statistical Computing (RRID:SCR_001905) and stats package from RStudio Team. GSEA (RRI D: SCR_003199), Ggplot2 (RRID:SCR_014601), Limma (RRID:SCR_010943), DESeq2 R package
(RRID:SCR_015687) and ChIP-seeker package from Bioconductor. Corrplot, survimer, survival, heatmaply and pheatma packages from CRAN. TopHat (RRID:SCR_013035), from Kim etal. 2013. HTSeq (RRID:SCR_05514) from Anders etal. 2015. The stats package from R Core Team. Oligonucleotides: Table 8 (see below) shows the oligonucleotides for RT-qPCR and ChIP-qPCR and sgRNA for CIRSPR/Cas9 knockout used (SEQ ID NO: 1-71).
METHODS:
Patient-derived organoids viability assays 600 single PDO cells were plated in 96-well plates in 10 pL Matrigel with 100 pL of complete medium. After 6 days in culture, growing PDOs were treated with combinations of 5-FU and Irinotecan for 72 hours at the concentrations that reduced a 20 and 30% of the cell growth (IC20 and IC30, respectively), which were specific for each tumoroid as described in Table 7 (see below). After 72 hours of treatment, it was changed to fresh medium and measured the cell viability after 3 days, 1 week and 2 weeks using the CellTiter-Glo 3D Cell Viability Assay following manufacturer's instructions in an Orion II multiplate luminometer. Images were obtained with an Olympus BX61 microscope at the indicated time points and the diameter of at least 70 tumoroids per condition was determined using Adobe Photoshop. For dose-response curves, tumoroids were plated in 96-well plates in Matrigel and after 6 days in culture were treated with combinations of 5-FU and Irinotecan. Following 72 hours of treatment, it was changed to fresh medium and treated with increasing concentrations of either 5-FU, Irinotecan, dasatinib or combinations for 72 hours at the indicated concentrations. Cell viability was determined as described. Tumor-initiating assays
To perform tumor-initiating assays, two approaches were used. Firstly, intracardiac injection of 40.000 CT (n=8) and IC20 (n=7) or IC30 (n=6) -treated PD05 cells carrying a luciferase reporter to NSG mice was performed. For checking that the injection was performed correctly, after injection animals were anesthetized and were given 100mI of substrate D-luciferin at 15 mg/ml by intraorbital injection. Bioluminescent imaging was performed placing the animals into the MS Lumina III In Vivo Imaging System (PerkinElmer). Images were recorded with an exposure time of 2 minutes and were taken every week. Quantification was done using Living Image® software (PerkinElmer). Secondly, equivalent amounts of disaggregated patient-derived organoids (PDOs), previously treated as indicated, were implanted as orthoxenografts. Follow-up of the growing tumors was done by palpation and animals were sacrificed when controls developed tumors of around 2 cm of diameter.
Immunohistochemical staining
Paraffin blocks were obtained from tissues and PDOs, previous fixation in 4% formaldehyde overnight at room temperature. Paraffin-embedded sections of 4 pm, for tissues, and 2.5 pm, for PDOs, were de-paraffinized, rehydrated and endogenous peroxidase activity was quenched (20 min, 1.5% H202). EDTA- or citrate-based antigen retrieval was used depending on the primary antibody used. All primary antibodies were diluted in PBS containing 0.05% BSA, incubated overnight at 4 °C and developed with the Envision+ System HRP Labelled Polymer anti-Rabbit or anti-Mouse and 3,3'-diaminobenzidine (DAB). Samples were mounted in DPX mountant and images were obtained with an Olympus BX61 microscope.
Immunofluorescence analysis
For tissues and PDOs, the same protocol as IHC was followed. Flowever, the samples were developed with Tyramide Signal Amplification System (TSA) and mounted in DAPI Fluoromount-G. Images were taken in an SP5 upright confocal microscope (Leica).
Hematoxylin and eosin staining
Previously de-paraffinized sections were incubated with hematoxylin 30 s, tap water 5 min, 80% ethanol 0.15% HCI 30 s, water 30 s, 30% ammonia water (NH3(aq)) 30 s, water 30 s, 96% ethanol 5 min, eosin 3 s, and absolute ethanol 1 min. Samples were dehydrated and mounted in DPX mountant, and images were obtained with an Olympus BX61 microscope.
Fluorescent in-situ hybridization (FISH) FISH analyses from control and IC30-treated PDOs were performed using commercial probes (Abbott Molecular Inc, Des Plaines, IL, USA), one including the centromeric alfa-satellite region specific for chromosome 8 (probe "30-70008 CEP 8 SpOrange”), and a second one containing locus-specific probes from the long arm of chromosome 13 and 21 (probe "33-171076 Aneuvysion 13 Sgreen/21 SpOrange”). In brief, a cytospin to concentrate nuclei in the FISH slide was performed. Slides were pre-treated with pepsin for 5 minutes at 37°C. Samples and probe were co-denaturated at 80°C for five minutes and hybridized overnight at 37°C in a hot plate (Hybrite chamber, Abbot Molecular Inc.). Post-hybridization washes were performed at 73°C in 2xsodium salt ctrate buffer (SSC) and at room temperature in 2xSSC, 0.1% NP-40 solution. Samples were counterstained with 4,6-diamino-2-phenilindole (DAPI) (Abbott Molecular Inc, Des Plaines, IL, USA). Results were analyzed in a fluorescence microscope (Olympus, BX51) using the Cytovision software (Applied Imaging, Santa Clara, CA). A minimum of 50 nuclei per case was analysed.
Cell cycle analysis
Cell cycle was determined by flow cytometry using the standard APC BrdU Flow Kit. Briefly, treated PDOs with combinations of 5-FU and Irinotecan, as indicated, were stained with bromodeoxyuridine (BrdU) for 24 hours. Single cells were obtained and processed according to the manufacturer's instructions, with DAPI staining for the DNA content. The cells were analysed in the LSR II analyser.
Cell senescence assays Cell senescence was identified by the presence of SA- -galactosidase activity using two different approaches. On one hand, staining for SA- -galactosidase activity in cultured cells was carried out using the Senescence b-Galactosidase Staining Kit. Briefly, PDOs were seeded in 24-well plates (3000 cells per well). After 6 days, PDOs were treated with combinations of 5-FU and Irinotecan for 72 hours and were subsequent stained with the b-Galactosidase Staining Solution for 2 hours, according to the manufacturer's instructions. Sections embedded in paraffin were counterstained with Fast Red for nuclei visualization. Images were obtained with an Olympus BX61 microscope. On the other hand, SA^-galactosidase activity was addressed by flow cytometry using the Cell Event Senescence Green Flow Cytometry Assay Kit following the manufacturer's instructions, and analysed in the LSR II analyser. Comet assay
Comet assays were performed using Comet Assay Kit following manufacturer's instructions. Pictures were taken using a Nikon Eclipse Ni-E epifluorescence microscope and tail moment was calculated using the OPENCOMET plugin for Fiji. Annexin V binding assay
Annexin V binding was determined by flow cytometry using the standard Annexin V Apoptosis Detection Kit APC. Single cells of treated PDOs with indicated combinations of 5-FU+lri. were obtained and stained according to the manufacturer's instructions, with Propidium Iodide staining for the DNA content. The cells were analysed in the Fortessa analyser.
PDO initiating capacity assay
For PDO Initiating Capacity assay, 300 or 600 single PDO cells were plated in 96-well plates in 10 pL Matrigel. After 11 days in culture, the number of PDOs in each well was counted, photographs were taken for PDO diameter determination and cell viability was measured.
Tumoroid initiating capacity assay
For Tumoroid Initiating Capacity assay, 300 or 600 single PDO cells were plated in 96-well plates in 10 pL Matrigel. After 11 days in culture, the number of PDOs in each well was counted, photographs were taken for PDO diameter determination and cell viability was measured.
Cell lysis and Western Blot
Treated PDOs were lysed for 20 min on ice in 300 pL of PBS plus 0.5% Triton X-100, 1 mM EDTA, 100 mM NA-orthovanadate, 0.2 mM phenyl-methylsulfonyl fluoride, and complete protease and phosphatase inhibitor cocktails. Lysates were analysed by western blotting using standard SDS-polyacrylamide gel electrophoresis (SDS-PAGE) techniques. In brief, protein samples were boiled in Laemmli buffer, run in polyacrylamide gels, and transferred onto polyvinylidene difluoride (PVDF) membranes. The membranes were incubated with the appropriate primary antibodies overnight at 4°C, washed and incubated with specific secondary horseradish peroxidase-linked antibodies. Peroxidase activity was visualized using the enhanced chemiluminescence reagent and autoradiography films.
RT-qPCR analysis
Total RNA from treated PDOs was extracted with the RNeasy Micro Kit, and cDNA was produced with the RT-First Strand cDNA Synthesis Kit. RT-qPCR was performed in LightCycler 480 system using SYBR Green I Master Kit. Samples were normalized to the mean of the housekeeping genes TBP, HPRT1 and ACTB. Primers used for qPCR are listed in Table 8 (SEQ ID NO: 1 to 60) (see below).
Chromatin-immunoprecipitation assay (ChIP)
Control and IC20-treated PDOs were subjected to ChIP following standard procedures. Briefly, PDO cells were extracted with formaldehyde crosslinked for 10 min at room temperature and lysed for 20 min on ice with 500 pL of H20 plus 10 mM Tris-HCI pH 8.0, 0.25% Triton X-100, 10 mM EDTA, 0.5 mM EGTA, 20 mM b- glycerol-phosphate, 100 mM NA-orthovanadate, 10 mM NaButyrate and complete protease inhibitor cocktail. The supernatants were sonicated, centrifuged at 13,000 rpm for 15 min, and supernatants were incubated overnight with anti-p53 antibody in RIPA buffer. Precipitates were captured with 35 mL of protein A- Sepharose, extensively washed and analysed by ChIP-qPCR. Primers used are listed in Table 8 (SEQ ID NO: 61-68). Inputs were used to normalize the ChIP-qPCR and samples were compared to control IgGs.
ChIP-sequencing analysis
IC20-treated PD05 was subjected to ChIP as previously described (Mulero etal., 2013). Briefly, formaldehyde crosslinked cell extracts were sonicated, and chromatin fractions were incubated for 16 h with anti-p53 [Abeam ab 1101] antibody in RIPA buffer and then precipitated with protein A/G-sepharose [GE Healthcare, Refs. 17- 0618-01 and 17-0780-01], Crosslinkage was reversed, and 6-10 ng of precipitated chromatin was directly sequenced in the genomics facility of Parc de Recerca Biomedica de Barcelona (PRBB) using lllumina® HiSeq platform. Raw single-end 50-bp sequences were filtered by quality (Q > 30) and length (length > 20 bp) with Trim Galore (Krueger etal., 2012). Filtered sequences were aligned against the reference genome (hg38) with Bowtie2 (Langmead & Salzberg, 2012). MACS2 software (Zhang et al., 2008) was run first for each replicate using unique alignments (q-value < 0.1). Peak annotation was performed with ChIPseeker package and peak visualization was done with Integrative Genomics Viewer (Robinson etal., 2011).
PDOs infection hFLiG plasmid was used for in vivo detection of metastasis, H2BeGFP plasmid was used for flow cytometry experiments and lentiCRISPR v2 was used for knock-out experiments. Three sgRNA against TP53 gene were designed using Benchling (table 8, SEQ ID NO: 69-71). Lentiviral production was performed transfecting in HEK293T cells the lentiviral vectors (pMD2.G and pCMVR8.2 plasmids) and the plasmid of interest (lentiCRISPR v2 as CRISPR control plasmid and the 3 sgRNA). One day after transfection, medium was changed, and viral particles were collected 24 hours later and then concentrated using Lenti-X Concentrator. PDOs were infected by resuspending single cells in concentrated virus diluted in complete medium, centrifuged for 1 h at 650 ref, and incubated for 5 hours at 37°C. Cells were then washed in complete culture medium and seeded as described above.
RNA-sequencing experiments and data analysis
Total RNA from untreatred and treated PDOs was extracted using RNeasy Micro Kit. The RNA concentration and integrity were determined using Agilent Bioanalyzer (Agilent Technologies, following manufacturer's instructions). Libraries were prepared at the Genomics Unit of Barcelona Biomedical Research Park (PRBB) (Barcelona, Spain) using standard protocols, and cDNA was sequenced using lllumina® HiSeq platform (HiSeq® 2500 Sequencing System, following manufacturer's instructions), obtaining ~25-30million 50-bp single-end reads per sample. Adapter sequences were trimmed with Trim Galore. Sequences were filtered by quality (Q > 30) and length (> 20 bp). Filtered reads were mapped against the latest release of the human reference genome (hg38) using default parameters of TopHat (v.2.1.1) (Kim etal., 2013), and expressed transcripts were then assembled. High-quality alignments were fed to HTSeq (v.0.9.1) (Anders etal., 2015) to estimate the normalized counts of each expressed gene. Differentially expressed genes between different conditions were explored using DESeq2 R package (v.1.20.0) (Love etal., 2014) and adjusted P-values for multiple comparisons were calculated applying the Benjamini-Hochberg correction (FDR). Plots were done in R. Expression heatmaps were generating using the heatmaply and pheatmap packages in R (Galili et al., 2018). Gene Set Enrichment Analysis (GSEA) was performed with described gene sets using gene set permutations (n = 1000) for the assessment of significance and signal-to-noise metric for ranking genes.
Description of the patient gene expression data sets
Transcriptomic and available clinical data datasets from colorectalcancer were downloaded from the open- access resource CANCERTOOL. For CRC there were used the Marisa (GSE39582) data set (Marisa etal., 2013) which included expression and clinical data for 566 patients with CRC and 19 non-tumoral colorectal mucosa, the Jorissen (GSE14333) data set (Jorissen et al., 2009) and the TCGA data set (The Cancer Genome Atlas Program - National Cancer Institute, TCGA Portal) with expression and clinical data of 226 and 329 CRC patients, respectively. The TCGAbiolinks (Colaprico etal., 2015) package in R was used to download the mutation annotation format (MAF) files for the TP53 mutation of the CRC TCGA dataset.
Signature definition
To generate the fetal intestinal stem cell signatures were selected genes with log2 Fold Change (FC) Treated vs Control > 0 and Fetal vs Adult > 0 (Fetal vs Adult as in Mustata et al., 2013) in the case of the upregulated- felSC and log2FC Treated vs Control < 0 and Fetal vs Adult < 0 in the case of the downregulated-felSC. Next it was used the Marisa data set to perform expression correlation matrices for the selected expression gene pairs using the corrplot package. Correlations were considered as statistically significant when the Pearson correlation coefficient corresponded to a p value below 0.05. Clusters of genes were selected when the absolute value for the Pearson correlation coefficient was above 0.1. To refine the feISC signatures, subset of genes with the highest correlation scores were selected.
Association of the signatures with clinical outcome
Association of the signatures expression with relapse was assessed in the cancer transcriptomic data sets using a Kaplan-Meier estimates and Cox proportional hazard models. Patients were classified by several ways. First, to perform unsupervised hierarchical clusters of the level of expression of the different subsets of fetal genes, the stats package (R Core Team 2020) with Euclidean distances measures was used. This allowed classification of groups of patients according to their combined expression levels of the genes of study. Second, patients were classified according to the mean ratio of gene expression of the signatures. Finally, in order to group patients within the three cohorts together, a single-sample gene set enrichment analysis (ssGSEA, Subramanian et al., 2005) was performed. This allowed classified patients with high or low values of an enrichment score, which represents the degree to which the genes in a particular gene set are coordinately up- or down-regulated within a sample.
Once patients were classified according to their combined expression of determined fetal genes, a standard log-rank test was applied to assess significance between groups. This test was selected because it assumed the randomness of the possible censorship. All the survival analyses and graphs were performed with R using the survival package and a p-value<0.05 was considered statistically significant. The hazard ratio (HR) was used as an estimation of the risk of relapse at a determined time. Confidence intervals of each HR within the 28up=high/8down=low-, 8up=high/8down=low-, 5up=high/3down=low- and 5up=high/4down=low-felSC signature, previously classifying patients according to an unsupervised hierarchical clusterization, is represented in Table 10 (see below).
Reversal of the signature with chemotherapy combined with Verteporfin®:
The CRC cell line LS174T was treated with sublethal doses of 5FU+irinotecan for 72h, alone or in combination with the YAP1 inhibitor verterporfin®, at a concentration of 5mM. CRC cell line LS 174T ( TP53 WT) was obtained from ATCC, was grown in Dulbecco's modified Eagle's medium (Invitrogen) plus 10% fetal bovine serum (Biological Industries) and was maintained in a 5% CO2 incubator at 37°C. Cells were lysed for 20 min on ice in 300 pL of PBS plus 0.5% Triton X-100, 1 mM EDTA, 100 mM NA-orthovanadate, 0.2 mM phenyl-methylsulfonyl fluoride, and complete protease and phosphatase inhibitor cocktails. Lysates were analysed by western blotting using standard SDS-polyacrylamide gel electrophoresis (SDS-PAGE) techniques. In brief, protein samples were boiled in Laemmli buffer, run in polyacrylamide gels, and transferred onto polyvinylidene difluoride (PVDF) membranes. The membranes were incubated with the appropriate primary antibodies overnight at 4°C, washed and incubated with specific secondary horseradish peroxidase-linked antibodies. Peroxidase activity was visualized using the enhanced chemiluminescence reagent and autoradiography films.
Quantification and statistical analysis
Statistical parameters, including number of events quantified, standard deviation and statistical significance, are reported in the figures and in the figure legends. Statistical analysis was performed using GraphPad Prism 6 software, and P< 0.05 was considered significant. Two-sided Student's f-test was used to compare differences between two groups. Each experiment was at least twice. Combinations of 5-FU and Irinotecan treatment had been checked for an appropriate IC20 and IC30 effect in every experiment, by cell viability assay. Bioinformatic analysis were performed as indicated above. For statistical analysis of the Kaplan-Meier estimates Cox proportional hazards models was used.
Example 1. Low-dose CT treatment of colorectal cancer PDOs induced a non-senescent quiescent phenotype in the absence of sustained DNA damage.
Mutation status of certain genes including TP53 was assessed in the PDOs by sequenciation as explained in the material and method section (see table 7 for results), wherein PD05 and PDO66 were TP53 wild type (WT).
To investigate the mechanisms that impose therapy resistancy in cancer patients, CRC PDOs were treated with serial dilutions of the first-line CT agents 5-FU+lri. to define doses that reduced cell numbers about 20- 30% after 72 hours of treatment (hereafter referred as IC20 and IC30, for Inhibitory Concentration 20 and 30), which were specific for each PDO (see table 7). Microscopy analysis of PDOs indicated that IC20 and IC30 did not promote detectable cell death after 72 hours but imposed a dose-dependent growth arrest that persisted for at least 2 weeks after drug washout. Analysis of PD05 (p53 WT) demonstrated that growth inhibition was linked to a reduction in proliferation (as determined by ki67 staining) at 72 hours of treatment and 1 week after washout and lower number of cells in S phase with accumulation in G0/G1 and G2M, as measured by flow cytometry. In addition, accumulation of cells in G2/M after damaging treatment may indicate the presence of cells not undergoing cytokinesis (Lukin et al., 2015). By fluorescent in-situ hybridization (FISH) and DAPI staining combined with Immunofluorescence (IF) of the membrane marker EPHB2, it was demonstrated the absence of polyploid or multinucleated cells, respectively, following IC30 treatment. Evaluation of senescence-associated (SA)- -Galactosidase activity by immunohystochemistry (IHC) and flow cytometry indicated that cells treated at IC20-IC30 failed to display a robust senescent phenotype, which was reliably detected in the IC60-treated cells.
Further supporting that IC20 and IC30-treated cells were not senescent, addition of the senolytic agent dasatinib (Xu etal., 2018) did not potentiate the growth inhibition imposed by IC20-305-FU+lri but enhanced the deleterious effect of IC605-FU+lri treatment. In addition, there were not detected apoptotic cells after IC30 treatment of PD05 as determined by active-Caspase3 and Annexin V staining. By comet assay and WB analysis of yH2A.X, it was demonstrated that PD05 cells treated with CT at different doses displayed increasing amounts of DNA damage starting at 1-3 hours and sustained up to 24 hours. Importantly, it was noticed the absence of DNA damage after 72 hours in IC20 and IC30-treated PDOs that was still detected in cells treated at IC60. In contrast, PD04 and PD08 cells carrying mutated p53 exhibited high amounts of DNA damage following IC20 and IC305Fu+iri treatment that persisted for at least 72 hours. These results were in agreement with the higher growth inhibition of p53 mutant PDOs after CT washout.
Together these results indicated that sublethal doses CT imposed a non-senescent and non-proliferating phenotype to cancer cells, hereafter referred as therapy-induced quiescent-like (TQL), in the absence of persistent DNA damage.
Example 2. The TQL phenotype was associated with acquisition of a fetal intestinal stem cell (feISC) signature.
To uncover transcriptional changes associated with the acquisition of the TQL phenotype, it was performed RNA sequencing (RNAseq) of control, IC20- and IC30- treated PD05 cells and differentially expressed genes (DEGs) between conditions were assessed. These data showed an almost perfect correlation of gene expression changes between pairwise comparisons (IC20 vs. untreated and IC30 vs. untreated) (p<2.2e-16, R=0.974).
Gene Set Enrichment Analysis (GSEA) uncovered p53 as the highest enriched pathway in TQL cells. By IHC and WB analysis of PDQ5, it was detected increased levels of p53 and its downstream target CDKN1 A (p21) in IC20 and IC30-treated cells starting at 1-3 hours and maintained after 72 hours (Fig. 1A). A validation of CT-induced activation of several putative p53 targets was done by qPCR (Fig. 1 B).
GSEA analysis also detected association with the NF-KB, apoptosis and interferon gamma (IFNy) pathways (p53 pathway, TNFA siganling via NFKB, coagulation, myogenesis, epithelial-mesenchymal transition, Kras signalling Down (DN), apoptosis, Kras signalling up and Interferon gamma response pathways in descending order of enrichment score (normalized enrichment score).
Unexpectedly, transcriptional changes associated with IC20-30 treatment were negatively correlated with the ISC signature in the GSEA. Flowever, it was not detected a general down-regulation of canonical ISC genes but a mixed pattern of genes unregulated and down-regulated in a dose-dependent manner (higher effects in IC30 than in IC20). Genes up-regulated in CT-treated PDO cells included LY6D and YAP1, with the canonical ISC markers LGR5 and EPHB2 severely down-regulated.
To deeper examined the intestinal stem cell pattern of the TQL cells, it was found a significant direct correlation between genes significantly transcriptionally modified by CT treatment and genes up- or down- regulated in fetal intestine-derived organoids compared with adult-derived ones (Fetal vs Adult of Mustata et al., 2013) (Figure 2A). Genes with log2FC higher than zero and genes with log2FC lower than zero within both comparisons were selected as upregulated and downregulated genes, respectively (see table 1 included at the end of the example section wherein all genes are included and table 2 and table 3 included also below, disclosing the upregulated and downregulated genes, respectively).
Example 3. The feISC signature shows a coordinate expression in human CRC and is dependent of functional p53.
Using CANCERTOOL (Cortazar et al., 2018) it was performed computational pan-cancer analyses of several cancer datasets using the genes disclosed in table 1 included below. Analysis of CRC Marisa dataset (Marisa et al, 2013) (NCBI identifier GSE39582) ("Marisa”) demonstrated that genes included in the feISC signature of table 1 were co-expressed since they were displayed as clusters with coordinate expression (with either positive or negative correlation) (including the genes of table 2 as upregulated and the genes of table 3 downregulated (disclosing the upregulated and downregulated genes, respectively) (following the method described in the "signature definition” in method section above). Genes with highest positive or negative correlation that were differentially expressed between CT treated and control PDOs and fetal compared with adult intestinal stem cells were integrated in a new cluster containing 28 genes that were significantly upregulated ("28up”) (included in table 2, that is, genes of table 4) and 8 down-regulated ("8down”) (included in table 3, that is, the genes of table 5) in CT-treated PDOs and feISC, called "28up/8down” signature (see Fig.2A black dots). The genes included in the 28up/8down signature were the following: "28up” were TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2 and RHOD genes (see table 4 below); and the "8down” were MYB, AGMAT, CDX1, H00K1,
PDSS1, HUNK, KCNK5 and SLC27A2 genes (see table 5 below).
This 28up/8down-felSC cluster of genes was similarly present in Marisa, Jorissen (Jorissen et al., 2009) (GSE14333) and TCGA (not depicted) CRC cohorts. It was confirmed CT-induced modulation of randomly selected 28up/8down-felSC genes by qPCR (Fig. 2B) and WB analysis (Fig. 2C) of in wfro-treated PD05 cells.
Activation of 28up-felSC genes following CT treatments was similarly observed in the p53 wild type PD066 (Fig. 2D) and no activation of this signature was observed in the p53 mutant PD04 cells (Fig. 2E).
It was also detected high levels of TUBB6, CD99L2 and MRAS proteins (contained in the 28up-felSC signature) by IHC analysis of I C20/30-deri ved tumors growing in nude mice. Importantly, 28up-felSC and 8down-felSC signatures were up-regulated and down-regulated, respectively, in CRC compared with colonic normal tissue, with higher significance in p53 WT tumors.
To study the possibility that coordinate induction of 28up-felSC genes by CT was p53 dependent, it was designed a CRISPR-Cas9 strategy to generate PD05 cells with partial deletion of p53. There were obtained several PD05 pools with variable degree of p53 depletion as confirmed by WB analysis (Fig. 2F). RT-qPCR analysis of PD05 KO#3 revealed impaired activation of randomly selected 28up-felSC genes after 5FU+iri (IC20) treatment compared with control cells (Fig. 2G) (see table 8 for information regarding the primers used). Using a panel of CRC cell lines, it was confirmed that activation of genes in the 28up-felSC signature by CT was higher in the presence of functional p53 (Fig.2H). However, by ChIP-sequencing (ChIP-seq) assay of 5FU+iri (IC20) treated-PD05 cells, it was only detected p53 binding at the promoter of PLK2, PHLDA3 and GSN genes, consistent with the fact that only 5 of the 28up-felSC genes had been previously identified as p53 targets.
It was determined whether tumors carrying the 28up+8down-felSC signature were restricted to a specific molecular cancer subtype. 74% of tumors with the 28up+8down-felSC signature were categorized as CSM4, based on the classification by Guinney and collaborators (Guinney et al., 2015), which was characterized by upregulation of epithelial to mesenchymal transition gene signatures, TGF signaling, stromal infiltration and poorer patient prognosis. In contrast, 28up-low+8down-high tumors were primarily ascribed to the more canonical Wnt and Myc-driven CMS2 subtype. It was next studied whether the feISC signature identified in untreated tumors was expressed in the epithelial cancer cells or primarily contributed by the stromal component of tumors. Analysis of single cells RNAseq data from Lee and collaborators (Lee etal, 2020) demonstrated that feISC genes were expressed in the epithelial component of untreated tumors, particularly in state 1, 5 and 6 that were associated with secretory and migratory pathways. Together these results indicated that acquisition of the TQL phenotype was linked with the expression of specific fetal ISC signature that was differentially expressed in cancer cells and dependent on the presence of a functional p53 pathway. This feISC signature was expressed in a coordinate manner in untreated human CRC tumors in the CMS4 subtype and tumors in the secretory and migratory epithelial states 1 , 5 and 6 from Guinney and collaborators.
Example 4. TQL cancer cells displayed in vitro and in vivo tumor initiation capacity Whether TQL cells preserved the tumor initiation capacity of untreated PDOs was studied. There were seeded 300 single cells from untreated or PDO cells treated for 72 hours in 3D cultures as indicated in the material and method section. It was found that CT-treated and untreated cells displayed comparable tumor initiation capacity (TIC) as indicated by the equal number of PDOs formed, although CT-treatment resulted in dose- dependent reduction of PDO diameter consistent with their low proliferation rates. In contrast, IC20- 5Fu+iri pre-treatment of p53 mutant PD04 and PD08 cells resulted in TIC abrogation, which was in agreement with the massive accumulation of DNA damage detected in comer assays. To compare the TIC in vitro of the general population and specifically the quiescent cells, it was generated a p53 WT PD05 carrying a doxycycline-inducible histone-GFP reporter that has been previously demonstrated to label the quiescent tumor population after doxycycline withdrawal (Puig et al., 2018). Upon 6 days of doxycycline treatment, PD05 cells were treated with 5-FU+lri. for 72h and, after 2 weeks of doxycycline washout, cells were analyzed by flow cytometry and GFPhigh and GFP|0W populations were sorted. Sorted GPFhigh, which represented the quiescent population of CT-treated cells, displayed identical capacity for organoid generation as GFPhigh plus GFP|0W cells indicating that TIC activity was retained in the TQL population, To determine the tumorigenic capacity of IC20 and IC30-treated PDOs in vivo, there were inoculated comparable numbers of untreated, IC20 and IC30-treated PDOs in the cecum of nude mice (2, 4 and 5 mice, respectively). Tumor growth was evaluated by palpation of the mice cecum weekly. Untreated and CT-treated PDOs all generated tumors in the site of inoculation that maintained the morphology of in vitro growing PDOs, with IC20 and IC30-treated being much smaller than those arising from untreated controls. Interestingly, IC20 and IC30-treated PDOs displayed a superior ability to growth as colonic and peritoneal implants when compared with tumors growing in the site of inoculation. This pattern was also observed in animals that were treated with 5-FU+lri for 3 weeks after tumor detection. IHC analysis of the proliferation marker ki67 indicated that tumors generated from untreated PDOs contained 60-80% of proliferating cells, whereas tumors derived from IC20 and IC30-treated PDOs showed a mixed pattern of quiescent (ki67 negative) and proliferative (ki67 positive) areas. On the other hand, 40,000 single PD05 cells (untreated, IC20 or IC30) expressing a luciferase reporter were injected intracardiac to NSG mice. Mice were analysed weekly for metastatic growth using the IVIS animal imaging system. PD05 treated with 5-FU+lri displayed a slightly superior metastatic capacity than untreated cells. Specifically, 4 of 8 mice transplanted with untreated PD05 cells contained metastatic lesions at week 15 after transplantation. Importantly, 4 of 6 mice transplanted with IC20-treated cells and 5 of 6 mice with IC30-treated cells showed visible implants 15 weeks after injection.
These results indicated that p53 WT CRC cells treated with low doses of 5-FU+lri. showed reduced capacity to grow in vitro and in the primary tumors, but displayed comparable TIC as untreated cells and higher metastatic activity in vivo.
Example 5. The CT induced feISC signature was predictive of poor patient prognosis, with higher statistical power in p53 WT tumors. The possibility that the feISC signature present in TQL cells was associated with cancer patient's outcome was studied. It was analyzed the predictive capacity of 28up/8down-felSC gene signature in the Marisa (Marisa etal., 2013), Jorissen (Jorissen etal., 2009) and TCGA (TCGA Portal) CRC data sets (following the method described for the "Association of the signatures with clinical outcome” in the material and method section above). Allowing unsupervised hierarchical clustering of the global 28up+8down-felSC signature was sufficient to demarcate 4 subsets of patients in the Marisa data set, 3 subsets of patients in the TCGA data set and 2 subsets of patients in the Jorissen data set, with the group with highest 28up and lowest 8down-felSC levels displaying the poorest disease-free-survival (Fig. 3). A more detailed analysis of the Marisa data set demonstrated that this signature was significantly associated with tumor relapse in patients at stages II (p=0.041) (Fig. 4A) and ll+lll (0.0033) (Fig. 4B) and imposed a trend towards poor prognosis at stage IV. In this line, this signature imposed a trend towards poor prognosis at stage I of TCGA CRC patients (Fig. 12C)
Since the presence of functional p53 defined feISC conversion and TIC maintenance (examples 3 and 4), the possibility that P53 status determined the prognosis value of 28up+8down-felSC signature in CRC was explored. Stratification of Marisa and TCGA patients according to P53 status did not have prognosis value by itself, but determined the prognosis value of 28up+8down-felSC signature, being significantly in P53WT (Fig. 5A and Fig. 5B). Because 28up+8down-felSC tumors were mainly included in the worst prognosis CMS4, it was tested whether this feISC signature represented an independent prognosis factor inside this molecular subtype. The results indicated that the 28up+8down-felSC signature increased the risk of relapse in patients within the CMS4 group (Fig. 6).
The Pearson correlation score for each gene of the 28up/8down-felSC gene signature, considering the 3 CRC datasets analysed, can be seen in table 9 below.
It was explored the possibility of identifying a simplified signature derived from the 28up/8down-felSC with comparable prognosis value in CRC. By manual inspection of the highest positive correlated genes in the Marisa cohort, uncovered an 8up/8down-felSC signature that shared coordinate expression in the Jorissen and TCGA cohorts that stratified patients in a similar manner as 28up/8down-felSC and significantly correlated with tumor relapse in all tested CRC cohorts (Fig. 7) (Marisa, p=0.00091; Jorisen, p=0.0027;
TCGA, p=0.0077). In addition, the 8up/8down-felSC signature was sufficient to predict disease relapse from stage I (Fig. 12D), stage II (Fig. 8A) and stage III (Fig. 8B) CRC patients.
The 8up/8down-felSC signature included TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, C0L18A1, SERPINH1, TPM2 genes as the 8up genes, and MYB, AGMAT, CDX1, H00K1, PDSS1, HUNK, KCNK5 and SLC27A2 as the 8down genes.
In order to find an even more simplified signature, the minimal signature with prognosis value, genes were selected by two ways. First, genes were scored by their coordinate expression taking into account the 3 CRC datasets analysed. Then it was evaluated the prognosis value by adding a value of single genes to the simplest signature composed by the highest scored 28up plus the highest scored 8down-felSC. This method uncovered a more simplified signature (see Table 9), named as "5up+3down” signature, which included 5 upregulated genes TIMP2, TSPAN4, TUBB6, MRAS, and ARL4C, and 3 down regulated genes MYB, AGMAT and CDX1. Second, in each CRC data set, genes were selected by two conditions: first by a correlation score higher than 0.8 (or if not, higher than the maximum of its table) and second, statistically significant, this is a correlation lower than a significant level of 5% .Then it was evaluated the prognosis value by adding a value of single genes to the simplest signature composed by genes that appeared in at least two of the three cohorts analyzed or that comprised the "5up+3down” signature. This method uncovered a simplified signature, named as "5up+4down” signature which included the same 5 upregulated genes, and 4 down regulated genes that were MYB, AGMAT, CDX1 and HOOK1, whose levels of expression in the PD05 were up and down, respectively (RT-qPCR analysis of selected fetal genes from control and IC20-treated PD05 cells in Figure 9A). These 5up/3down and 5up/4down signatures were sufficient to predict disease relapse in all tested CRC datasets (Fig. 9B and 9C), including patients carrying tumors at stage I (Fig. 12A and 12B), stage II (Fig. 10A and 10C) and stage ll-lll (Fig.lOB and 10D). The prognosis value of the above signatures was also determined using all patients of the combined cohorts (Fig. 14). Moreover, other simplified signatures with comparable prognosis value to the 28up/8down were found by the inventors, namely: rB: "TIMP2" and "TSPAN4" as up-regulated genes and "MYB" and "AGMAT" as down-regulated genes. rH: "TIMP2" and "TSPAN4" as up-regulated genes and "MYB" as down-regulated gene, rl: "TIMP2" as up-regulated gene and "MYB" and "AGMAT" as down-regulated genes. rC: "TUBB6" and "TIMP2" as up-regulated genes and "MYB" and "HOOK" as down-regulated genes. rD: "TUBB6", "TIMP2" and "TSPAN4" as up-regulated genes and "MYB" and "HOOK" as down-regulated genes. rE: "TUBB6" and "TIMP2" as up-regulated genes and "MYB", "HOOK" and "AGMAT" as down-regulated genes. rF: "TUBB6", "TIMP2" and "TSPAN4" as up-regulated genes and "MYB", "HOOK" and "AGMAT" as down- regulated genes. rJ: "TUBB6" and "TIMP2" as up-regulated genes and "MYB" as down-regulated gene. rK: "TIMP2" as up-regulated gene and "MYB" and "H00K1" as down-regulated genes. rL: "TIMP2, "TUBB6" and "TSPAN4" as up-regulated genes and "CDX1" as down-regulated gene. rM: "TIMP2" and "TSPAN4" as up-regulated genes and "CDX1" as down-regulated gene.
Each one of these reduced signatures was sufficient to predict disease relapse in all tested CRC datasets (Figs. 13 and 14).
In order to obtain a ratio useful in the prediction, the arithmetic mean of the 28up genes divided by the arithmetic mean of the 8down genes was analysed, either for the group with highest 28up and lowest 8down- felSC levels (poorest outcome), as well as for the group with lowest 28up and highest 8down-felSC levels, in the Marisa dataset. This gave rise to a ratio of 1.22 within the patients with the poorest outcome. It was performed a series of supervised analysis for TCGA, Jorissen and Marisa dataset for the purpose of finding the optimized ratios. This was done by generating Kaplan-Meier curves representing the disease-free survival of patient groups classified with different ratios and taking into account the p-value and Hazard-Ratio (HR) statistics results as indicators of a promising ratio. Thus, clustered patients according to a ratio higher or equal to 1.01 and lower or equal to 0.99 resulted in significant differences (Marisa, p=0.03, HR=1.41; Jorissen, p=1e-05, HR=3.67; TCGA, p=0.03, HR=1.93). As an example for other ratios, clustered patients according to a ratio higher or equal to 1.10 and lower or equal to 0.90 resulted in significant differences in Marisa (p=0.005; HR=1.95) and Jorissen (p=1e-04; HR=5.25). This also applied to the reduced signatures (Fig. 15).
The multivariate analysis using Cox Proportional Hazards Model of the feISC signature for each dataset can be seen in Table 10. In order to assess the dependency of different tumor variables (as tumor stage or TP53 mutational status) in the prediction of cancer relapse, as well as the power of the signatures in means of the hazard ratio, the association of the signatures with recurrence-disease free survival was analyzed. It is of notice that the analysis of the subgroups of patients with the signatures within the different variables was statistically significant and had a high hazard ratio (higher than 1), in spite of the number of patients included. This was indicative of the effectiveness of the signatures to predict relapse. For each cluster of patients classified either by the 28up/down- or 8up/8down- or 5up/3down-felSC signature with the poorest prognosis it was determined i) the number of patients within the cluster, ii) the p. value and iii) the hazard-ratio and it's 95% interval confidence.
These results demonstrated the prognosis value in CRC of the 28up/8down-felSC signature, of the initially identified in the analysis of TQL cells, and also the prognosis value in CRC of its derivative 8up/8down-felSC and 5up+3down signature. The results indicated that loss of adult ISC identity favoured tumor progression.
Together these results indicated that low CT doses induced a TQL phenotype to cancer cells that was associated with acquisition of a feISC signature that predicted poor prognosis in human CRC. Moreover, the predictive value of this particular signature was significantly enhanced by the presence of functional p53 in the tumor cells. Remarkably, it was shown that the sublethal CT-induced feISC signature described in above examples 1-4 was already present in a subset of untreated tumors at diagnosis in several CRC cohorts. In conclusion, these findings improved prediction of outcome or the risk of recurrence or progression in cancer and in particular in CRC.
Example 6. Acquisition of feISC by CT treatment was linked to and dependent on YAP1 activation and the feISC signature was reversed by using the YAP1 inhibitor Verteporfin®
An in vitro experiment using PD05 cells (Fig. 11 A) and a various CRC cell lines (Fig. 11 B) showed increased YAP1 expression after 5-FU+lri treatment, that was restricted to cells carrying WT P53. Nuclear (active) YAP1 accumulated in the IC20- and IC30- derived PD05 tumors at 2 months after implantation in mice. By IHC analysis of ki67 in 62 paired human CRC samples collected at diagnosis (biopsy) and after DNA damaging-based neoadyuvant treatment (surgery) the proliferation status of the tumors was determined. Whereas some tumors exhibited similar proliferation rates after treatment, as determined by Ki67 staining (type 1), a large subset of tumors displayed reduced proliferation with no morphological evidences of senescence (type 2), such as enlarged nuclei or expression of the senescence marker p16 which were detected in scarce tumors at surgery (type 3). No differences were detected in patient prognosis when comparing type 1 and type 2 tumors that were readily observed in patient carrying type 3 tumors (no events of relapse in the follow up period). Interestingly, nuclear YAP1, which was already detected in few epithelial cells of untreated tumors, was massively increased in neoadjuvant treated tumors independently of the proliferation status associated with expression of the feISC markers S100A4 and SERPINH1. These results suggested that YAP1 activation and fetal conversion were a consequence of sublethal CT treatment.
To study whether YAP1 activity was required for transcriptional induction of feISC genes by CT, PD05 cells were incubated with the YAP1 inhibitor verteporfin® (Fig. 11C), which precluded the induction of all tested feISC genes following IC205FU+irinotecan treatment. Similarly, treatment of the colorectal p53 WT cell line (cell line LS174T) with IC205FU+irinotecan for 72h led to an increase in YAP1, SERPINH1 and TSPAN4 protein levels, which was abrogated by the verterporfin® (Fig. 11D). Low CT doses led to nuclear YAP1 accumulation that was abrogated by incubation with verteporfin®. Verteporfin® also led to a reduction in protein levels of YAP1 and the feISC markers SERPINH1 and TSPAN4 (Fig. 11 D). Importantly, verteporfin® alone or in combination with low doses of CT promoted tumor cell death specifically in the P53 WT PD05. In contrast, PD08 carrying mutant P53 showed higher resistance to YAP1 inhibition.
These results demonstrated that combination of CT plus YAP1 inhibitors can represent a suitable therapeutic strategy for eradicating p53 WT tumors carrying the 28up+8down signature. Tables 1- 9 included in the present invention:
Table 1
ID: Entrez ID; St., Status; D. Down. Identifiers at date 25.11.2020.
Table 2
ID: Entrez ID; St., Status.
Table 3
ID: Entrez ID; St., Status.
Table 4: Upregulated genes: Table 5: Down regulated genes:
Table 6: Expression products of the genes of tables 4 and 5: mRNA Ref SEQ and protein RefSeq were the reference sequence of GenBank; HGNC, HUGO Gene Nomenclature Committee at 25 November 2020.
Table 7: Patient-derived organoids used. The mutations and the corresponding chemotherapy concentrations that reduce a 20 and 30% of the cell growth (IC20 and IC30, respectively) are indicated for each PDO.
Table 8: List of oligonucleotides for RT-qPCR and ChIP-qPCR and sgRNA for CIRSPR/Cas9 knockout used.
Table 9: Pearson correlation punctuation score for the genes included in the 28up/8down firm.
Table 10 Cox proportional hazards analysis of the feISC signature. Association of the signature with recurrence-disease free survival.
Clauses
1. An in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), the method comprising the step of: a. determining in an isolated sample of a subject the level of expression of
(a1) at least one gene selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4,
GSN, CXCL16, CD99L2, RHOD (genes of table 4) and any combination thereof; and (a2) at least one gene selected from the group consisting of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5, SLC27A2 (genes of table 5) and any combination thereof. 2. The in vitro method for the prediction of the outcome according to claim 1, which further comprises the step: b) determining a ratio between the level of expression of the genes determined in step (a1) and the genes determined in step (a2); wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01 and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99.
3. The in vitro method for the prediction of the outcome according to claim 2, wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01 , 1.05, 1.10 or 1.2; and the subject is considered as having good outcome if the ratio obtained in step
(b) is lower than or equal to 0.99, 0.95 or 0.90.
4. The in vitro method for the prediction of the outcome according to any one of claims 1 to 3, wherein step (a) comprises determining in an isolated sample of a subject the level of expression of (a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes; and
(a2) at least each one of MYB, AGMAT and CDX1 genes
5. The in vitro method for the prediction of the outcome according to any one of claims 1 to 3, wherein step (a) comprises determining in an isolated sample of a subject the level of expression of (a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and
TPM2 genes; and
(a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes.
6. The in vitro method for the prediction of the outcome according to any one of claims 1 to 3, wherein step (a) comprises determining in an isolated sample of a subject the level of expression of
(a1) each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD genes; and (a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes. 7. The in vitro method for the prediction of the outcome according to any one of claims 1 to 6, wherein the method further comprises identifying the mutation status of TP53 gene, wherein the subject is considered as having bad outcome when the TP53 gene is the TP53 wild-type gene or, alternatively, when the TP53 gene is a non-inactivating mutated TP53.
8. The in vitro method for the prediction of the outcome according to any one of claims 1 to 7 wherein the subject has received anti-cancer chemotherapy.
9. An in vitro method to determine the efficacy of an anti-cancer chemotherapy in a subject suffering colorectal cancer (CRC) comprising the steps of:
(a) determining in an isolated sample of a subject before and after starting the anti-cancer chemotherapy the level of expression of
(a1) at least one gene selected from the group consisting of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD (genes of table 4) and any combination thereof; and
(a2) at least one gene selected from the group consisting of: MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 (genes of table 5) and any combination thereof; or, alternatively,
(a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes; and (a2) at least each one of MYB, AGMAT and CDX1 genes; or, alternatively,
(a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes; and
(a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; or, alternatively,
(a1) each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD genes; and (a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; and b) determining a ratio between the level of expression of the gene(s) determined in step (a1) and the gene(s) determined in step (a2) before and after starting the anti-cancer chemotherapy, wherein, if the ratio of gene expression after starting the anti-cancer chemotherapy is higher than or equal to the ratio obtained before starting the anti-cancer chemotherapy this is indicative of the inefficiency of the anti-cancer chemotherapy.
10. The in vitro method to determine the efficacy of an anti-cancer chemotherapy in a colorectal cancer patient according to claim 9, wherein the method further comprises identifying the TP53 gene mutational status, wherein when TP53 wild-type is determined or, alternatively, when a non inactivating mutated TP53 is determined, this is indicative of the inefficiency of the anti-cancer chemotherapy. The in vitro method for the prediction of the outcome according to claim 8 or the in vitro method to determine the efficacy of an anti-cancer chemotherapy in a colorectal cancer patient according to any one of claims 9 or 10 wherein the anti-cancer chemotherapy is selected from the group consisting of fluoropirimidine, oxaliplatin, irinotecan and any combination thereof; alternatively, it is combined with an antiangiogenic drug and/or EGFR inhibitor. An in vitro method for deciding or recommending a medical regime to a subject suffering colorectal cancer (CRC) the method comprising:
(a) predicting the outcome of the subject suffering colorectal cancer by the method as defined in any one of claims 1 to 8 or 11, or, alternatively, determining the efficacy of an anti-cancer chemotherapy as defined in any one of claims 9 to 11 , and
(b) recommending a therapeutic medical regime if the subject is predicted to have bad outcome, or, alternatively, recommending an alternative medical regime if the anti-cancer chemotherapy is ineffective. The in vitro method for the prediction of the outcome according to any one of claims 1 to 8 or 11, or the in vitro method to determine the efficacy of an anti-cancer chemotherapy according to any one of claims 9 to 11 , or an in vitro method for deciding or recommending a medical regime according to claim 12, wherein the subject is suffering colorectal cancer at stages II or III. Use of a kit for predicting the outcome of a subject suffering colorectal cancer as defined in any one of claims 1 to 8 or 11 or 13, or for determining the efficacy of an anti-cancer chemotherapy in a subject suffering colorectal cancer as defined in any one of claims 9 to 11 or 13, for deciding or recommending a medical regime to subject suffering colorectal cancer as defined in any one of claims 12-13, the kit comprising means for determining the level of expression of at least one of the genes in table 4 and at least one of the genes in table 5; or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes, and of each one of MYB, AGMAT and CDX1 genes; or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and
TPM2 genes, and of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; or, alternatively, of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C,
LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD genes, and of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes. A combined use of an expression product of each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C genes, and of an expression product of each one of MYB, AGMAT and CDX1 genes; or, alternatively, a combined use of an expression product of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2 genes, and of an expression product of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; or, alternatively, a combined use of an expression product of each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1,
PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD genes, and of an expression product of each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2 genes; as a marker of prediction of progression of colorectal cancer or of determining the efficacy of an anti-cancer chemotherapy in a subject suffering colorectal cancer or of deciding or recommending a medical regime in a subject suffering colorectal cancer.
Citation List
Non Patent Literature
Brenner H. etal. (2014) Colorectal cancer. The Lancet, doi.org/10.1016/S0140-6736(13)61649-9.
He S. and Sharpless N. E. (2017) Senescence in Health and Disease. Cell. doi.org/10.1016/j.cell.2017.05.015.
Saleh T. et al. (2019). Tumor cell escape from therapy-induced senescence as a model of disease recurrence after dormancy. Cancer Research, doi.org/10.1158/0008-5472.CAN-18-3437.
Livak and Schmittgen (2001) Methods, vol. 25, issue 4, p.402-8.
Sato, T. etal. (2011). Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett's epithelium. Gastroenterology. doi.org/10.1053/j.gastro.2011.07.050.
Fernandez-Barral, A., etal., (2020). Vitamin D differentially regulates colon stem cells in patient-derived normal and tumor organoids. The FEBS Journal, doi.org/10.1111/febs.14998.
Celia-Terrasa T and King Y. (2018). Metastatic niche functions and therapeutic opportunities. Nature Cell Biology, doi: 10.1038/s41556-018-0145-9. Stewart, PE., etal., (2003). Lentivirus-delivered stable gene silencing by RNAi in primary cells, doi:
10.1261/rna.2192803.
Sanjana, NE., etal., (2014). Improved vectors and genome wide libraries for CRISPR screening, doi: 10.1038/nmeth.3047. Schneider, CA., etal., (2012). NIH Imgae to ImageJ: 25 years of image analysis. Nature Methods, doi: 10.1038/nmeth.2089.
Kim, D., etal. (2013). TopHat2: Accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biology, doi.org/10.1186/gb-2013-14-4-r36.
Anders, S., etal. (2015). HTSeq-A Python framework to work with high-throughput sequencing data. Bioinformatics, doi.org/10.1093/bioinformatics/btu638. Mulero, M., etal. (2013). Chromatin-bound IkBa regulates a subset of polycomb target genes in differentiation and cancer. Cancer Cell, 24(2). doi.org/10.1016/j.ccr.2013.06.003.
Krueger, B., etal. (2012). Different evolutionary modifications as a guide to rewire two-component systems. Bioinformatics and Biology Insights. doi.org/10.4137/BBI.S9356.
Langmead, B., & Salzberg, S. L. (2012). Fast gapped-read alignment with Bowtie 2. Nature Methods. doi.org/10.1038/nmeth.1923.
Zhang, Y., etal. (2008). Model-based analysis of Chi P-Seq (MACS). Genome Biology, doi.org/10.1186/gb- 2008-9-9-M37.
Robinson, JT., etal. (2011). Integrative Genomics Viewer, doi: 10.1038/nbt.1754.
Love, M. I., etal. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, doi.org/10.1186/s13059-014-0550-8.
Galili, T., etal. (2018). Heatmaply: An R package for creating interactive cluster heatmaps for online publishing. Bioinformatics, doi.org/10.1093/bioinformatics/btx657. Marisa, L., etal. (2013). Gene Expression Classification of Colon Cancer into Molecular Subtypes:
Characterization, Validation, and Prognostic Value. PLoS Medicine, doi.org/10.1371/journal.pmed.1001453.
Jorissen, R. N., etal. (2009). Metastasis-associated gene expression changes predict poor outcomes in patients with Dukes stage B and C colorectal cancer. Clinical Cancer Research, doi.org/10.1158/1078- 0432. CCR-09-1431.
Colaprico, A., etal. (2015). TCGAbiolinks: a R/Bioconductor package for integrative analysis of TCGA data, doi: 10.1093/nar/gkv1507. Mustata, R. C., etal. (2013). Identification of Lgr5-lndependent Spheroid-Generating Progenitors of the Mouse Fetal Intestinal Epithelium. Cell Reports. doi.org/10.1016/j.celrep.2013.09.005. Lukin, D. J., etal. (2015). p53 promotes cell survival due to the reversibility of its cell-cycle checkpoints. Molecular Cancer Research, doi.org/10.1158/1541-7786. MCR-14-0177. Xu, M., etal. (2018). Senolytics improve physical function and increase lifespan in old age. Nature Medicine. doi.org/10.1038/s41591-018-0092-9.
Cortazar, A. R., etal. (2018). Cancertool: A visualization and representation interface to exploit cancer datasets. Cancer Research, doi.org/10.1158/0008-5472.CAN-18-1669.
Guinney, J., etal. (2015). Nature Medicine. The consensus molecular subtypes of colorectal cancer. doi.org/10.1038/nm.3967.
Lee, H. O., etal. (2020). Lineage-dependent gene expression programs influence the immune landscape of colorectal cancer. Nature Genetics, doi.org/10.1038/s41588-020-0636-z.
Puig, I., etal. (2018). TET2 controls chemoresistant slow-cycling cancer cell survival and tumor recurrence. Journal of Clinical Investigation. doi.org/10.1172/JCI96393. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. PNAS. 2005; 102(43): 15545-15550

Claims

Claims
1. An in vitro method for the prediction of the outcome in a subject suffering colorectal cancer (CRC), the method comprising the step of: a. determining in an isolated sample of a subject the level of expression of the following genes:
(a1) at least TSPAN4 and one gene selected from TIMP2 and TUBB6, and
(a2) at least one gene selected from the group consisting of MYB,CDX1, HOOK1, and any combination thereof, and b. comparing the level of the expression of each gene with a corresponding reference value, wherein the subject is considered as having bad outcome if the level of the expression of each one of the genes determined in (a1) is higher than the corresponding reference value and wherein the level of the expression of each one of the genes determined in (a2) is lower with respect to the corresponding reference value.
2. The in vitro method for the prediction of the outcome according to the preceding claim, wherein step (b) further comprises determining a ratio between the level of expression of the genes determined in step (a1) as compared to their reference values and the genes determined in step (a2) as compared to their reference values, wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.01 and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.99.
3. The in vitro method for the prediction of the outcome according to the preceding claim, wherein the subject is considered as having bad outcome if the ratio obtained in step (b) is higher than or equal to 1.05, 1.10 or 1.2; and the subject is considered as having good outcome if the ratio obtained in step (b) is lower than or equal to 0.95 or 0.90.
4. The in vitro method for the prediction of the outcome according to the preceding claim, wherein the prediction of bad outcome is directly proportional to the increase of the ratio obtained in step (b).
5. The in vitro method for the prediction of the outcome according to any one of the preceding claims, wherein the reference value is obtained from a group of CRC tissue samples.
6. The in vitro method for the prediction of the outcome according to any one of the preceding claims, wherein step (a) comprises determining the level of expression of the following genes:
(a1) at least each one of TIMP2 and TSPAN4, and (a2) at least MYB.
7. The in vitro method for the prediction of the outcome according to any one of the preceding claims, wherein step (a) comprises determining the level of expression of the following genes:
(a1) at least each one of TIMP2, TUBB6, and TSPAN4, and (a2) at least each one of MYB and HOOK1.
8. The in vitro method for the prediction of the outcome according to any one of the preceding claims, wherein step (a) comprises determining the level of expression of the following genes:
(a1) at least each one of TIMP2, TUBB6, and TSPAN4 and (a2) at least each one of MYB, HOOK1 and AGMAT.
9. The in vitro method for the prediction of the outcome according to any one of the preceding claims , wherein step (a) comprises determining the level of expression of the following genes:
(a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS and ARL4C; and (a2) at least each one of MYB, AGMAT, HOOK1 and CDX1.
10. The in vitro method for the prediction of the outcome according to any one of the preceding claims, wherein step (a) comprises determining in an isolated sample of a subject the level of expression of the following genes:
(a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2; and
(a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2.
11. The in vitro method for the prediction of the outcome according to any one of the preceding claims, wherein step (a) comprises determining in an isolated sample of a subject the level of expression of the following genes:
(a1) each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD; and
(a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2.
12. The in vitro method for the prediction of the outcome according to any one of the preceding claims, wherein the method further comprises identifying the mutation status of TP53 gene, wherein the subject is considered as having bad outcome when the TP53 gene is the TP53 wild-type gene or, alternatively, when the TP53 gene is a non-inactivating mutated TP53.
13. The in vitro method for the prediction of the outcome according to any one of the preceding claims, wherein the subject has received anti-cancer chemotherapy.
14. An in vitro method to determine the efficacy of an anti-cancer chemotherapy in a subject suffering colorectal cancer (CRC) comprising the steps of: a. determining in an isolated sample of a subject the level of expression of the following genes:
(a1) at least TSPAN4 and one gene selected from TIMP2 and TUBB6, and
(a2) at least one gene selected from the group consisting of MYB, CDX1, HOOK1, and any combination thereof, and b. comparing the level of the expression of each gene before with after starting the anti-cancer chemotherapy, wherein, if the level of expression of each one of the genes determined in (a1) after starting the anti cancer chemotherapy is higher than or equal to the level of expression obtained before starting the anti-cancer chemotherapy, this is indicative of the inefficiency of the anti-cancer chemotherapy.
15. The in vitro method to determine the efficacy of an anti-cancer chemotherapy in a colorectal cancer patient according to claim 14, wherein step (b) further comprises determining a ratio between the level of expression of the genes determined in step (a1) after starting the anti-cancer chemotherapy as compared to their level of expression before the anti-cancer therapy and the genes determined in step (a2) after starting the anti-cancer chemotherapy as compared to their level of expression before the anti-cancer therapy, wherein anti-cancer chemotherapy is considered to be ineffective if the ratio is higher than or equal to 1.01.
16. The in vitro method to determine the efficacy of an anti-cancer chemotherapy in a colorectal cancer patient according to any one of claims 14-15, wherein step (a) comprises determining the level of expression of the following genes:
(a1) at least each one of TIMP2 and TSPAN4, and (a2) at least MYB.
17. The in vitro method to determine the efficacy of an anti-cancer chemotherapy in a colorectal cancer patient according to any one of claims 14-16, wherein step (a) comprises determining the level of expression of the following genes:
(a1) at least each one of TIMP2, TUBB6, and TSPAN4, and (a2) at least each one of MYB and HOOK1.
18. The in vitro method to determine the efficacy of an anti-cancer chemotherapy in a colorectal cancer patient according to any one of claims 14-17, wherein step (a) comprises determining the level of expression of the following genes:
(a1) at least each one of TIMP2, TUBB6, and TSPAN4 and (a2) at least each one of MYB, HOOK1 and AGMAT.
19. The in vitro method to determine the efficacy of an anti-cancer chemotherapy in a colorectal cancer patient according to any one of claims 14-18, wherein step (a) comprises determining the level of expression of the following genes:
(a1) at least each one of TIMP2, TSPAN4, TUBB6, MR AS and ARL4C; and (a2) at least each one of MYB, AGMAT, HOOK1 and CDX1.
20. The in vitro method to determine the efficacy of an anti-cancer chemotherapy in a colorectal cancer patient according to any one of claims 14-19, wherein step (a) comprises determining the level of expression of the following genes:
(a1) at least each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2; and (a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2.
21. The in vitro method to determine the efficacy of an anti-cancer chemotherapy in a colorectal cancer patient according to any one of claims 14-20, wherein step (a) comprises determining the level of expression of the following genes: (a1) each one of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2,
ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD; and
(a2) each one of MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2.
22. The in vitro method to determine the efficacy of an anti-cancer chemotherapy in a colorectal cancer patient according to any one of claims 14-21, wherein the method further comprises identifying the TP53 gene mutational status, wherein when TP53 wild-type is determined or, alternatively, when a non inactivating mutated TP53 is determined, this is indicative of the inefficiency of the anti-cancer chemotherapy.
23. The in vitro method for the prediction of the outcome according to any one of claims 1-13 or the in vitro method to determine the efficacy of an anti-cancer chemotherapy in a colorectal cancer patient according to any one of claims 14-22, wherein the anti-cancer chemotherapy is selected from the group consisting of fluoropyrimidine, oxaliplatin, irinotecan, and any combination thereof, and/or, optionally, it is combined with an antiangiogenic drug and/or EGFR inhibitor.
24. An in vitro method for deciding or recommending a medical regime to a subject suffering colorectal cancer (CRC) the method comprising:
(c) predicting the outcome of the subject suffering colorectal cancer by the method as defined in any one of claims 1-13 or 23, or, alternatively, determining the efficacy of an anti-cancer chemotherapy as defined in any one of claims 14-23, and
(d) recommending a therapeutic medical regime if the subject is predicted to have bad outcome, or, alternatively, recommending an alternative medical regime if the anti-cancer chemotherapy is ineffective.
25. The in vitro method for the prediction of the outcome according to any one of claims 1-13 or 23, or the in vitro method to determine the efficacy of an anti-cancer chemotherapy according to any one of claims 14- 23, or an in vitro method for deciding or recommending a medical regime according to claim 24, wherein the subject is suffering colorectal cancer at stages I, II or III.
26. The in vitro method for the prediction of the outcome according to any one of claims 1-13, 23 or 25, or the in vitro method to determine the efficacy of an anti-cancer chemotherapy according to any one of claims 14-23 or 25, or an in vitro method for deciding or recommending a medical regime according to any one of claims 24-25, wherein the biological sample is CRC tumoral tissue.
27. Use of a kit for predicting the outcome of a subject suffering colorectal cancer as defined in any one of claims 1-13, 23 or 25-26, or for determining the efficacy of an anti-cancer chemotherapy in a subject suffering colorectal cancer as defined in any one of claims 14-23 or 25-26, or for deciding or recommending a medical regime to subject suffering colorectal cancer as defined in any one of claims 24- 26, the kit comprising means for determining the level of expression of: (a1) TSPAN4 and one gene selected from TIMP2 and TUBB6; and (a2) one gene selected from the group consisting of MYB, CDX1, HOOK1, and any combination thereof.
28. The use of a kit according to claim 27, wherein the kit comprises means for determining the level of expression of TIMP2, TSPAN4, and MYB.
29. The use of a kit according to any one of claims 27-28, wherein the kit comprises means for determining the level of expression of TIMP2, TUBB6, TSPAN4, MYB, and HOOK1.
30. The use of a kit according to any one of claims 27-29, wherein the kit comprises means for determining the level of expression of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, MYB, AGMAT, HOOK1 and CDX1.
31. The use of a kit according to any one of claims 27-30, wherein the kit comprises means for determining the level of expression of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1, TPM2, MYB,
AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5, and SLC27A2.
32. The use of a kit according to any one of claims 27-31, wherein the kit comprises means for determining the level of expression of TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, RHOD, MYB, AGMAT, CDX1, HOOK1, PDSS1,
HUNK, KCNK5 and SLC27A2.
33. A combined use of an expression product of (a1) TSPAN4 and one gene selected from TIMP2 and TUBB6; and an expression product of (a2) one gene selected from the group consisting of MYB, CDX1, HOOK1, and any combination thereof, as a marker of prediction of progression of colorectal cancer or of determining the efficacy of an anti-cancer chemotherapy in a subject suffering colorectal cancer or of deciding or recommending a medical regime in a subject suffering colorectal cancer.
34. The combined use according to claim 33, that comprises use of an expression product of (a1) TIMP2 and TSPAN4 and an expression product of (a2) MYB.
35. The combined use according to any one of claims 33-34, that comprises use of an expression product of (a1) TIMP2, TUBB6, and TSPAN4 and an expression product of (a2) MYB and HOOK1.
36. The combined use according to any one of claims 33-35, that comprises use of an expression product of (a1) TIMP2, TSPAN4, TUBB6, MRAS and ARL4C, and an expression product of (a2) MYB, AGMAT, HOOK1 and CDX1.
37. The combined use according to any one of claims 33-36, that comprises use of an expression product of (a1) TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, COL18A1, SERPINH1 and TPM2, and an expression product of (a2) MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2.
38. The combined use according to any one of claims 33-37, that comprises use of an expression product of
(a1) TIMP2, TSPAN4, TUBB6, MRAS, ARL4C, LAPTM5, COL18A1, SERPINH1, CRIP2, ICAM1, VAMP5, TPM2, PLAUR, S100A4, GPC1, ANXA1, PHLDA3, CLU, PLK2, KIFC3, IL1RN, GLIPR1, WTIP, ABHD4, GSN, CXCL16, CD99L2, and RHOD, and an expression product of (a2) MYB, AGMAT, CDX1, HOOK1, PDSS1, HUNK, KCNK5 and SLC27A2.
EP22713432.7A 2021-03-31 2022-03-30 Genomic predictor of outcome in cancer Pending EP4314344A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP21382269 2021-03-31
PCT/EP2022/058503 WO2022207760A1 (en) 2021-03-31 2022-03-30 Genomic predictor of outcome in cancer

Publications (1)

Publication Number Publication Date
EP4314344A1 true EP4314344A1 (en) 2024-02-07

Family

ID=75529930

Family Applications (1)

Application Number Title Priority Date Filing Date
EP22713432.7A Pending EP4314344A1 (en) 2021-03-31 2022-03-30 Genomic predictor of outcome in cancer

Country Status (2)

Country Link
EP (1) EP4314344A1 (en)
WO (1) WO2022207760A1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115572769B (en) * 2022-12-07 2023-03-14 中国人民解放军军事科学院军事医学研究院 Gene marker combination for benign prognosis prediction of liver cancer patient

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012087144A2 (en) * 2010-12-23 2012-06-28 Agendia N.V. Methods and means for molecular classification of colorectal cancers
WO2015017537A2 (en) * 2013-07-30 2015-02-05 H. Lee Moffitt Cancer Center And Research Institute, Inc. Colorectal cancer recurrence gene expression signature

Also Published As

Publication number Publication date
WO2022207760A1 (en) 2022-10-06

Similar Documents

Publication Publication Date Title
Ascierto et al. Transcriptional mechanisms of resistance to anti–PD-1 therapy
AU2005249492B2 (en) Methods for prediction of clinical outcome to epidermal growth factor receptor inhibitors by cancer patients
Gangemi et al. Mda-9/syntenin is expressed in uveal melanoma and correlates with metastatic progression
US20150292030A1 (en) Methods of characterizing and treating molecular subset of muscle-invasive bladder cancer
US20190127805A1 (en) Gene signatures for cancer detection and treatment
Rabjerg et al. Molecular characterization of clear cell renal cell carcinoma identifies CSNK 2A1, SPP 1 and DEFB 1 as promising novel prognostic markers
US20110189670A1 (en) Circulating Tumor and Tumor Stem Cell Detection Using Genomic Specific Probes
EP3428647A1 (en) Expression signature for glioma diagnosis and/or prognosis in a subject
Schulze et al. RELN signaling modulates glioblastoma growth and substrate‐dependent migration
Birks et al. Claudin 6 is a positive marker for atypical teratoid/rhabdoid tumors
US20230113705A1 (en) Methods for diagnosing, prognosing and managing treatment of breast cancer
US11851712B2 (en) Replication stress response biomarkers for immunotherapy response
Dong et al. Identification and validation of L Antigen Family Member 3 as an immune-related biomarker associated with the progression of papillary thyroid cancer
WO2014135655A1 (en) Compositions and methods for treating muscle-invasive bladder cancer
Zhao et al. TWIST2: A new candidate tumor suppressor in prostate cancer
Liu et al. USP51/ZEB1/ACTA2 axis promotes mesenchymal phenotype in gastric cancer and is associated with low cohesion characteristics
EP4314344A1 (en) Genomic predictor of outcome in cancer
US20110091482A1 (en) Expression of kir in human cancer cells as a biomarker for immuno-escape and cancer metastasis
US10676792B2 (en) Prognostic and diagnostic methods for colorectal cancer
Wei et al. Prognostic value and immunological role of FOXM1 in human solid tumors
Huang et al. ARPC2: A Pan-Cancer prognostic and immunological biomarker that promotes hepatocellular carcinoma cell proliferation and invasion
Sáez et al. Development of a real-time reverse transcription polymerase chain reaction assay for c-myc expression that allows the identification of a subset of c-myc+ diffuse large B-cell lymphoma
WO2021063972A1 (en) Cthrc1 as biomarker for a tgfbeta-activated tumor microenvironment
Li et al. Krüppel-Like Factor 2 Is a Gastric Cancer Suppressor and Prognostic Biomarker
KR102431271B1 (en) Biomarker predictive of responsiveness to an anticancer agent and use thereof

Legal Events

Date Code Title Description
STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: UNKNOWN

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE

PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE

17P Request for examination filed

Effective date: 20231031

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR