WO2018189215A1 - Method for predicting the survival time of a patient suffering from hepatocellular carcinoma - Google Patents

Method for predicting the survival time of a patient suffering from hepatocellular carcinoma Download PDF

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Publication number
WO2018189215A1
WO2018189215A1 PCT/EP2018/059229 EP2018059229W WO2018189215A1 WO 2018189215 A1 WO2018189215 A1 WO 2018189215A1 EP 2018059229 W EP2018059229 W EP 2018059229W WO 2018189215 A1 WO2018189215 A1 WO 2018189215A1
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Prior art keywords
hcc
hccs
expression level
genes
patient
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PCT/EP2018/059229
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French (fr)
Inventor
Orlando Musso
Florian ROHART
Kim-Anh LE CAO
Romain DESERT
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INSERM (Institut National de la Santé et de la Recherche Médicale)
Université De Rennes 1
The University Of Queensland
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Publication of WO2018189215A1 publication Critical patent/WO2018189215A1/en

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    • 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
    • C12Q2600/118—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 a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma (HCC) comprising: i) determining, in a sample obtained from the patient, the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7; ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression levels determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • HCC hepatocellular carcinoma
  • HCC Hepatocellular carcinoma
  • HCCs Treatment allocation for early-stage HCCs might be improved by identifying homogeneous molecular subclasses with predictable outcomes.
  • (2, 3) The molecular landscape of HCCs is emerging as a result of global gene expression analyses and the discovery of crucial driver tumor mutations.
  • (1, 2) At present, HCCs are split into two molecular classes, each representing 50% of tumors: proliferative and nonproliferative HCCs.
  • Proliferative HCCs include two subclasses enriched in WNT/TGFB signals and stem/progenitor cell markers, respectively.(l, 2) Among non-proliferative HCCs, half of the tumors form a homogeneous subclass with a high rate of activating ⁇ -catenin (CTNNBl) exon 3 mutations. (2, 4-6) These tumors are well-differentiated, (2, 4-8) but patient survival rates do not differ from HCCs carrying wild-type CTNNBl. The rest of nonproliferative HCCs carry wild-type CTNNB1,(5) but no evidence to date allowed them to qualify as a homogeneous HCC subclass.
  • CTNNBl ⁇ -catenin
  • the inventors established 1) a first signature consisting of 5 genes which is suitable for predicting ⁇ -catenin mutations and 2) a second signature of at least 6 genes which is also suitable for predicting the survival time of a patient suffering from a specific subclass of HCC (Periportal-type HCCs).
  • the present invention relates to a method for predicting the survival time of a patient suffering from hepatocellular carcinoma (HCC) comprising: i) determining, in a sample obtained from the patient, the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7; ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression levels determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • HCC hepatocellular carcinoma
  • a first aspect of the invention relates to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma (HCC) comprising: i) determining, in a sample obtained from the patient, the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7; ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression levels determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • HCC hepatocellular carcinoma
  • the invention relates to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma (HCC) comprising: i) determining, in a sample obtained from the patient, the expression level of the genes selected in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7; ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression levels determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • HCC hepatocellular carcinoma
  • the measurement of the expression level of at least one gene in the group consisting of OTC and SLC27A5 may be added to the method for predicting the survival time of a patient suffering from a hepatocellular carcinoma.
  • the invention relates to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and OTC ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • the invention relates to to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and OTC ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • the invention relates to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • the invention in another aspect, relates to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7, OTC and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • Another aspect of the invention relates to a method for predicting the overall survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • Another aspect of the invention relates to a method for predicting the overall survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and OTC ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • Another aspect of the invention relates to a method for predicting the overall survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • Another aspect of the invention relates to a method for predicting the overall survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7, OTC and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • Another aspect of the invention relates to a method for predicting the disease-free- survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • Another aspect of the invention relates to a method for predicting the disease-free- survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and OTC ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • Another aspect of the invention relates to a method for predicting the disease-free- survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • Another aspect of the invention relates to a method for predicting the disease-free- survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7, OTC and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
  • a second aspect of the invention relates to a method for predicting at least a mutation of the CTNNB1 gene in a patient suffering from hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in HAL, VNN1, ODAM, GLUL and LGR5; ii) computing a CTNNB1 mutation score conceived by the inventors thanks to these expression levels of the genes and; iii) comparing said CTNNBl mutation score determined at step ii) with its predetermined reference value to determine if there is at least a mutation on the CTNNBl gene or no mutation on the CTNNBl gene.
  • the invention relates to a method for predicting at least a mutation of the CTNNBl gene in a patient suffering from hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in HAL, VNN1, ODAM, GLUL and LGR5; ii) computing a CTNNBl mutation score conceived by the inventors, as follows:
  • Identifying a CTNNBl mutation in a hepatocellular carcinoma indicates that the patient suffering from this cancer will have a Perivenous-type HCC. Identifying this subclass of HCC is clinically relevant because: (i) this subclass of liver cancer is characterized by activation of the ⁇ -catenin signalling pathway that could be treated by specific inhibitors of this pathway (see for example the patent applications WO2011088127, US7803783 or WO2004032838); (ii) overall survival and disease-free survival rates of patients suffering from HCCs carrying CTNNBl mutations will probably be less favourable than those of patients suffering from Periportal-type HCCs, but more favourable than those of patients suffering from STEM-type HCCs.
  • OS Overall survival
  • DFS Disease-free survival
  • the term "Good Prognosis” denotes a significantly more favourable probability of survival after patient treatment in the group of patients defined as “good prognosis” compared with the group of patients defined as “bad prognosis”.
  • sample denotes, blood, peripheral-blood, serum, plasma, and liver tissues obtained by HCC biopsy, HCC resection or liver resection specimens.
  • patient refers to an individual who is being managed for liver disease and who is susceptible to develop an HCC at any stage of this disease.
  • HCCs can be proliferative and non- proliferative HCCs.
  • Proliferative HCCs include two subclasses enriched in WNT/TGFB signals and stem/progenitor cell markers, respectively.
  • Non-proliferative HCCs can be periportal or perivenous HCCs, as defined by the inventors.
  • HCC can be a "ECM-type HCC” (for Cancer Extracellular Matrix) or an or a STEM-type HCCs (see for example Hoshida , cancer research 2009).
  • AGXT refers to the gene of "Alanine-Glyoxylate
  • FETUB refers to the gene of "Fetuin B”. The sequence of said gene can be found under the Ensembl accession number ENSG00000090512.
  • GLS2 refers to the gene of "Glutaminase 2".
  • the sequence of said gene can be found under the Ensembl accession number ENSG00000135423.
  • GNMT refers to the gene of "Glycine N-methyltransferase”. The sequence of said gene can be found under the Ensembl accession number ENSG00000124713.
  • SLC 10A 1 refers to the gene of "Solute Carrier Family 10
  • the sequence of said gene can be found under the Ensembl accession number ENSG00000100652.
  • SLC22A7 refers to the gene of "Solute carrier family 22 member 7".
  • the sequence of said gene can be found under the Ensembl accession number ENSG00000137204.
  • OTC refers to the gene of "Ornithine Carbamoyltransferase". The sequence of said gene can be found under the Ensembl accession number ENSG00000036473.
  • SLC27A5 refers to the gene of "Solute Carrier Family 27 Member 5 Canal
  • the sequence of said gene can be found under the Ensembl accession number ENSG00000083807.
  • HAL refers to the gene of "Histidine ammonia-lyase”. The sequence of said gene can be found under the Ensembl accession number ENSG00000084110.
  • VNN1 refers to the gene of "Vanin 1".
  • the sequence of said gene can be found under the Ensembl accession number ENSG00000112299.
  • ODAM refers to the gene of "Odontogenic ameloblast- associated protein".
  • the sequence of said gene can be found under the Ensembl accession number ENSG00000109205.
  • GLUL refers to the gene of "Glutamine synthetase”. The sequence of said gene can be found under the Ensembl accession number ENSG00000135821.
  • LGR5 refers to the gene of "Leucine-rich repeat-containing G-protein coupled receptor 5".
  • the sequence of said gene can be found under the Ensembl accession number ENSG00000139292.
  • CNNB1 or " ⁇ -catenin gene” refers to the gene which encode for the protein ⁇ -catenin.
  • the sequence of said gene can be found under the Ensembl accession number ENSG00000168036.
  • Measuring the expression level of the genes listed above can be done by measuring the gene expression level of these genes and can be performed by a variety of techniques well known in the art.
  • the expression level of a gene may be determined by determining the quantity of mRNA.
  • Methods for determining the quantity of mRNA are well known in the art.
  • the nucleic acid contained in the samples e.g., cell or tissue prepared from the patient
  • the extracted mRNA is then detected by hybridization (e. g., Northern blot analysis, in situ hybridization) and/or amplification (e.g., RT-PCR).
  • LCR ligase chain reaction
  • TMA transcription- mediated amplification
  • SDA strand displacement amplification
  • NASBA nucleic acid sequence based amplification
  • Nucleic acids having at least 10 nucleotides and exhibiting sequence complementarity or homology to the mRNA of interest herein find utility as hybridization probes or amplification primers. It is understood that such nucleic acids need not be identical, but are typically at least about 80% identical to the homologous region of comparable size, more preferably 85% identical and even more preferably 90-95% identical. In certain embodiments, it will be advantageous to use nucleic acids in combination with appropriate means, such as a detectable label, for detecting hybridization.
  • the nucleic acid probes include one or more labels, for example to permit detection of a target nucleic acid molecule using the disclosed probes.
  • a nucleic acid probe includes a label (e.g., a detectable label).
  • a "detectable label” is a molecule or material that can be used to produce a detectable signal that indicates the presence or concentration of the probe (particularly the bound or hybridized probe) in a sample.
  • a labeled nucleic acid molecule provides an indicator of the presence or concentration of a target nucleic acid sequence (e.g., genomic target nucleic acid sequence) (to which the labeled uniquely specific nucleic acid molecule is bound or hybridized) in a sample.
  • a label associated with one or more nucleic acid molecules can be detected either directly or indirectly.
  • a label can be detected by any known or yet to be discovered mechanism including absorption, emission and/ or scattering of a photon (including radio frequency, microwave frequency, infrared frequency, visible frequency and ultra-violet frequency photons).
  • Detectable labels include colored, fluorescent, phosphorescent and luminescent molecules and materials, catalysts (such as enzymes) that convert one substance into another substance to provide a detectable difference (such as by converting a colorless substance into a colored substance or vice versa, or by producing a precipitate or increasing sample turbidity), haptens that can be detected by antibody binding interactions, and paramagnetic and magnetic molecules or materials.
  • detectable labels include fluorescent molecules (or fluorochromes).
  • fluorescent molecules or fluorochromes
  • Numerous fluorochromes are known to those of skill in the art, and can be selected, for example from Life Technologies (formerly Invitrogen), e.g., see, The Handbook— A Guide to Fluorescent Probes and Labeling Technologies).
  • fluorophores that can be attached (for example, chemically conjugated) to a nucleic acid molecule (such as a uniquely specific binding region) are provided in U.S. Pat. No.
  • fluorophores include thiol-reactive europium chelates which emit at approximately 617 mn (Heyduk and Heyduk, Analyt. Biochem. 248:216-27, 1997; J. Biol. Chem. 274:3315-22, 1999), as well as GFP, LissamineTM, diethylaminocoumarin, fluorescein chlorotriazinyl, naphthofluorescein, 4,7-dichlororhodamine and xanthene (as described in U.S. Pat. No. 5,800,996 to Lee et al.) and derivatives thereof.
  • fluorophores known to those skilled in the art can also be used, for example those available from Life Technologies (Invitrogen; Molecular Probes (Eugene, Oreg.)) and including the ALEXA FLUOR® series of dyes (for example, as described in U.S. Pat. Nos. 5,696,157, 6, 130, 101 and 6,716,979), the BODIPY series of dyes (dipyrrometheneboron difluoride dyes, for example as described in U.S. Pat. Nos.
  • a fluorescent label can be a fluorescent nanoparticle, such as a semiconductor nanocrystal, e.g., a QUANTUM DOTTM (obtained, for example, from Life Technologies (QuantumDot Corp, Invitrogen Nanocrystal Technologies, Eugene, Oreg.); see also, U.S. Pat. Nos. 6,815,064; 6,682,596; and 6,649, 138).
  • Semiconductor nanocrystals are microscopic particles having size-dependent optical and/or electrical properties.
  • Semiconductor nanocrystals that can he coupled to a variety of biological molecules (including dNTPs and/or nucleic acids) or substrates by techniques described in, for example, Bruchez et al., Science 281 :20132016, 1998; Chan et al., Science 281:2016-2018, 1998; and U.S. Pat. No. 6,274,323. Formation of semiconductor nanocrystals of various compositions are disclosed in, e.g., U.S. Pat. Nos.
  • semiconductor nanocrystals can he produced that emit light of different colors hased on their composition, size or size and composition.
  • quantum dots that emit light at different wavelengths based on size (565 mn, 655 mn, 705 mn, or 800 mn emission wavelengths), which are suitable as fluorescent labels in the probes disclosed herein are available from Life Technologies (Carlshad, Calif.).
  • Additional labels include, for example, radioisotopes (such as 3 H), metal chelates such as DOTA and DPTA chelates of radioactive or paramagnetic metal ions like Gd3+, and liposomes.
  • Detectable labels that can he used with nucleic acid molecules also include enzymes, for example horseradish peroxidase, alkaline phosphatase, acid phosphatase, glucose oxidase, beta-galactosidase, beta-glucuronidase, or beta-lactamase.
  • enzymes for example horseradish peroxidase, alkaline phosphatase, acid phosphatase, glucose oxidase, beta-galactosidase, beta-glucuronidase, or beta-lactamase.
  • an enzyme can he used in a metallographic detection scheme.
  • SISH silver in situ hyhridization
  • Metallographic detection methods include using an enzyme, such as alkaline phosphatase, in combination with a water-soluble metal ion and a redox-inactive substrate of the enzyme. The substrate is converted to a redox-active agent by the enzyme, and the redoxactive agent reduces the metal ion, causing it to form a detectable precipitate.
  • Metallographic detection methods also include using an oxido-reductase enzyme (such as horseradish peroxidase) along with a water soluble metal ion, an oxidizing agent and a reducing agent, again to form a detectable precipitate.
  • an oxido-reductase enzyme such as horseradish peroxidase
  • Probes made using the disclosed methods can be used for nucleic acid detection, such as ISH procedures (for example, fluorescence in situ hybridization (FISH), chromo genie in situ hybridization (CISH) and silver in situ hybridization (SISH)) or comparative genomic hybridization (CGH).
  • ISH procedures for example, fluorescence in situ hybridization (FISH), chromo genie in situ hybridization (CISH) and silver in situ hybridization (SISH)
  • CGH comparative genomic hybridization
  • ISH In situ hybridization
  • a sample containing target nucleic acid sequence e.g., genomic target nucleic acid sequence
  • a metaphase or interphase chromosome preparation such as a cell or tissue sample mounted on a slide
  • a labeled probe specifically hybridizable or specific for the target nucleic acid sequence (e.g., genomic target nucleic acid sequence).
  • the slides are optionally pretreated, e.g., to remove paraffin or other materials that can interfere with uniform hybridization.
  • the sample and the probe are both treated, for example by heating to denature the double stranded nucleic acids.
  • the probe (formulated in a suitable hybridization buffer) and the sample are combined, under conditions and for sufficient time to permit hybridization to occur (typically to reach equilibrium).
  • the chromosome preparation is washed to remove excess probe, and detection of specific labeling of the chromosome target is performed using standard techniques.
  • a biotinylated probe can be detected using fluorescein-labeled avidin or avidin- alkaline phosphatase.
  • fluorochrome detection the fluorochrome can be detected directly, or the samples can be incubated, for example, with fluorescein isothiocyanate (FITC)- conjugated avidin.
  • FITC fluorescein isothiocyanate
  • FrfC signal can be effected, if necessary, by incubation with biotin-conjugated goat antiavidin antibodies, washing and a second incubation with FITC- conjugated avidin.
  • samples can be incubated, for example, with streptavidin, washed, incubated with biotin-conjugated alkaline phosphatase, washed again and pre-equilibrated (e.g., in alkaline phosphatase (AP) buffer).
  • AP alkaline phosphatase
  • Numerous reagents and detection schemes can be employed in conjunction with FISH, CISH, and SISH procedures to improve sensitivity, resolution, or other desirable properties.
  • probes labeled with fluorophores including fluorescent dyes and QUANTUM DOTS®
  • fluorophores including fluorescent dyes and QUANTUM DOTS®
  • the probe can be labeled with a nonfluorescent molecule, such as a hapten (such as the following non- limiting examples: biotin, digoxigenin, DNP, and various oxazoles, pyrrazoles, thiazoles, nitroaryls, benzofurazans, triterpenes, ureas, thioureas, rotenones, coumarin, courmarin-based compounds, Podophyllotoxin, Podophyllotoxin-based compounds, and combinations thereof), ligand or other indirectly detectable moiety.
  • a hapten such as the following non- limiting examples: biotin, digoxigenin, DNP, and various oxazoles, pyrrazoles, thiazoles, nitroaryls, benzofurazans, triterpenes, ureas, thioureas, rotenones, coumarin, courmarin-based compounds, Podophyllotoxin,
  • Probes labeled with such non-fluorescent molecules (and the target nucleic acid sequences to which they bind) can then be detected by contacting the sample (e.g., the cell or tissue sample to which the probe is bound) with a labeled detection reagent, such as an antibody (or receptor, or other specific binding partner) specific for the chosen hapten or ligand.
  • a labeled detection reagent such as an antibody (or receptor, or other specific binding partner) specific for the chosen hapten or ligand.
  • the detection reagent can be labeled with a fluorophore (e.g., QUANTUM DOT®) or with another indirectly detectable moiety, or can be contacted with one or more additional specific binding agents (e.g., secondary or specific antibodies), which can be labeled with a fluorophore.
  • the probe, or specific binding agent (such as an antibody, e.g., a primary antibody, receptor or other binding agent) is labeled with an enzyme that is capable of converting a fluorogenic or chromogenic composition into a detectable fluorescent, colored or otherwise detectable signal (e.g., as in deposition of detectable metal particles in SISH).
  • the enzyme can be attached directly or indirectly via a linker to the relevant probe or detection reagent. Examples of suitable reagents (e.g., binding reagents) and chemistries (e.g., linker and attachment chemistries) are described in U.S. Patent Application Publication Nos. 2006/0246524; 2006/0246523, and 2007/ 01 17153.
  • multiplex detection schemes can he produced to facilitate detection of multiple target nucleic acid sequences (e.g., genomic target nucleic acid sequences) in a single assay (e.g., on a single cell or tissue sample or on more than one cell or tissue sample).
  • a first probe that corresponds to a first target sequence can he labelled with a first hapten, such as biotin, while a second probe that corresponds to a second target sequence can be labelled with a second hapten, such as DNP.
  • the bound probes can he detected by contacting the sample with a first specific binding agent (in this case avidin labelled with a first fluorophore, for example, a first spectrally distinct QUANTUM DOT®, e.g., that emits at 585 mn) and a second specific binding agent (in this case an anti-DNP antibody, or antibody fragment, labelled with a second fluorophore (for example, a second spectrally distinct QUANTUM DOT®, e.g., that emits at 705 mn).
  • a first specific binding agent in this case avidin labelled with a first fluorophore, for example, a first spectrally distinct QUANTUM DOT®, e.g., that emits at 585 mn
  • a second specific binding agent in this case an anti-DNP antibody, or antibody fragment, labelled with a second fluorophore (for example, a second spectrally distinct QUANTUM DOT®,
  • Probes typically comprise single-stranded nucleic acids of between 10 to 1000 nucleotides in length, for instance of between 10 and 800, more preferably of between 15 and 700, typically of between 20 and 500.
  • Primers typically are shorter single- stranded nucleic acids, of between 10 to 25 nucleotides in length, designed to perfectly or almost perfectly match a nucleic acid of interest, to be amplified.
  • the probes and primers are "specific" to the nucleic acids they hybridize to, i.e. they preferably hybridize under high stringency hybridization conditions (corresponding to the highest melting temperature Tm, e.g., 50 % formamide, 5x or 6x SCC.
  • SCC is a 0.15 M NaCl, 0.015 M Na-citrate).
  • the nucleic acid primers or probes used in the above amplification and detection method may be assembled as a kit.
  • a kit includes consensus primers and molecular probes.
  • a preferred kit also includes the components necessary to determine if amplification has occurred.
  • the kit may also include, for example, PCR buffers and enzymes; positive control sequences, reaction control primers; and instructions for amplifying and detecting the specific sequences.
  • the methods of the invention comprise the steps of providing total RNAs extracted from cumulus cells and subjecting the RNAs to amplification and hybridization to specific probes, more particularly by means of a quantitative or semiquantitative RT-PCR.
  • the expression level is determined by DNA chip analysis.
  • DNA chip or nucleic acid microarray consists of different nucleic acid probes that are chemically attached to a substrate, which can be a microchip, a glass slide or a micro sphere- sized bead.
  • a microchip may be constituted of polymers, plastics, resins, polysaccharides, silica or silica-based materials, carbon, metals, inorganic glasses, or nitrocellulose.
  • Probes comprise nucleic acids such as cDNAs or oligonucleotides that may be about 10 to about 60 base pairs.
  • a sample from a test subject optionally first subjected to a reverse transcription, is labelled and contacted with the microarray in hybridization conditions, leading to the formation of complexes between target nucleic acids that are complementary to probe sequences attached to the microarray surface.
  • the labelled hybridized complexes are then detected and can be quantified or semi-quantified. Labelling may be achieved by various methods, e.g. by using radioactive or fluorescent labelling.
  • Many variants of the microarray hybridization technology are available to the man skilled in the art (see e.g. the review by Hoheisel, Nature Reviews, Genetics, 2006, 7:200-210).
  • the expression level is determined by metabolic imaging (see for example Yamashita T et al., Hepatology 2014, 60: 1674-1685 or Ueno A et al., Journal of hepatology 2014, 61: 1080-1087).
  • Expression level of a gene may be expressed as absolute expression level or normalized expression level.
  • expression levels are normalized by correcting the absolute expression level of a gene by comparing its expression to the expression of a gene that is not a relevant for determining the cancer stage of the patient, e.g., a housekeeping gene that is constitutively expressed.
  • Suitable genes for normalization include housekeeping genes such as the actin gene ACTB, ribosomal 18S gene, GUSB, PGK1, TFRC, GAPDH, GUSB, TBP and ABL1. This normalization allows the comparison of the expression level in one sample, e.g., a patient sample, to another sample, or between samples from different sources.
  • Predetermined reference values used for comparison may comprise "cut-off or "threshold" values that may be determined as described herein.
  • Each reference (“cut-off) value for the genes' expression may be predetermined by carrying out a method comprising the steps of
  • the expression level of the genes has been assessed for 100 HCC samples from 100 patients.
  • the 100 samples are ranked according to their expression level.
  • Sample 1 has the highest expression level and sample 100 has the lowest expression level.
  • a first grouping provides two subsets: on one side sample Nr 1 and on the other side the 99 other samples.
  • the next grouping provides on one side samples 1 and 2 and on the other side the 98 remaining samples etc., until the last grouping: on one side samples 1 to 99 and on the other side sample Nr 100.
  • Kaplan Meier curves are prepared for each of the 99 groups of two subsets. Also for each of the 99 groups, the p value between both subsets was calculated.
  • the reference value is selected such as the discrimination based on the criterion of the minimum p value is the strongest.
  • the expression level corresponding to the boundary between both subsets for which the p value is minimum is considered as the reference value. It should be noted that the reference value is not necessarily the median value of expression levels.
  • the reference value (cut-off value) may be used in the present method to discriminate HCC samples and therefore the corresponding patients.
  • Kaplan-Meier curves of percentage of survival as a function of time are commonly used to measure the fraction of patients living for a certain amount of time after treatment and are well known by the person skilled in the art.
  • Such predetermined reference values of expression level may be determined for any gene defined above.
  • Another aspect of the invention relates to a chemotherapeutic compound for use in the treatment of HCC in a patient with a bad prognosis as described above.
  • chemotherapeutic compounds may be selected in the group consisting in: fludarabine, gemcitabine, capecitabine, methotrexate, taxol, taxotere, mercaptopurine, thioguanine, hydroxyurea, cytarabine, cyclophosphamide, ifosfamide, nitrosoureas, platinum complexes such as cisplatin, carboplatin and oxaliplatin, mitomycin, dacarbazine, procarbizine, etoposide, teniposide, campathecins, bleomycin, doxorubicin, idarubicin, daunorubicin, dactinomycin, plicamycin, mitoxantrone, L-asparaginase, doxorubicin, epimbicm, 5-fluorouracil, taxanes such as docetaxel and paclitaxel, leucovorin,
  • additional anticancer agents may be selected from, but are not limited to, one or a combination of the following class of agents: alkylating agents, plant alkaloids, DNA topoisomerase inhibitors, anti-folates, pyrimidine analogs, purine analogs, DNA antimetabolites, taxanes, podophyllotoxin, hormonal therapies, retinoids, photosensitizers or photodynamic therapies, angiogenesis inhibitors, antimitotic agents, isoprenylation inhibitors, cell cycle inhibitors, actinomycins, bleomycins, anthracyclines, MDR inhibitors and Ca2+ ATPase inhibitors.
  • a more aggressive chemo therapeutic compound may be used to treat patient with bad prognosis.
  • This compound may be the sorafenib for example..
  • HCC patients with good prognosis may benefit from potentially curative therapies that include but may not be limited to tumor resection, local tumor ablation and liver transplantation.
  • therapies include but may not be limited to tumor resection, local tumor ablation and liver transplantation.
  • the choice among these alternatives will greatly depend on the functional reserve of the liver, tumor accessibility and localization in the liver, donor liver availability and the intrinsic aggressiveness of the tumor, which can be predicted using different methods to predict survival time in patients with HCC. (See for example: Sapisochin G, Bruix J. Liver transplantation for hepatocellular carcinoma: outcomes and novel surgical approaches. Nature reviews. Gastroenterology & hepatology 2017;14:203-217).
  • resection of the HCC in the patient with bad prognosis may be done to diminish tumor burden and to provide the best supportive care to the patient.
  • resection of the HCC in the patient with good prognosis may be done to avoid tumor progression while the patient is in the waiting list for liver transplantation.
  • resection of the HCC in the patient with good prognosis may be done to downstage the patient in such a way that they meet transplantation criteria.
  • local ablation of the HCC in the patient with good prognosis may be done to avoid tumor progression while the patient is in the waiting list for liver transplantation.
  • local ablation of the HCC in the patient with good prognosis may be done to downstage the patient in such a way that they meet transplantation criteria.
  • Tumor ablation techniques comprise, but are not limited to, techniques based on radiofrequency, microvawe, alcohol or acetic acid percutaneous injection.
  • a transplantation of a liver may be realized to treat the patient with good prognosis.
  • the transplantation has more chances to be successful than a transplantation in a patient with a bad prognosis.
  • the genes of the invention are in a particular interest to help clinicians to have the best therapeutic answer for the patient.
  • Another aspect of the invention relates to a therapeutic composition
  • a therapeutic composition comprising a chemotherapeutic compound for use in the treatment of HCC in a patient with a bad prognosis as described above.
  • Any therapeutic agent of the invention may be combined with pharmaceutically acceptable excipients, and optionally sustained-release matrices, such as biodegradable polymers, to form therapeutic compositions.
  • “Pharmaceutically” or “pharmaceutically acceptable” refers to molecular entities and compositions that do not produce an adverse, allergic or other untoward reaction when administered to a mammal, especially a human, as appropriate.
  • a pharmaceutically acceptable carrier or excipient refers to a non-toxic solid, semi-solid or liquid filler, diluent, encapsulating material or formulation auxiliary of any type.
  • compositions for example, the route of administration, the dosage and the regimen naturally depend upon the condition to be treated, the severity of the illness, the age, weight, and sex of the patient, etc.
  • compositions of the invention can be formulated for a topical, oral, intranasal, parenteral, intraocular, intravenous, intramuscular, intrathecal or subcutaneous administration and the like.
  • the pharmaceutical compositions contain vehicles which are pharmaceutically acceptable for a formulation capable of being injected (like lipiodol, gelfoam, ivalon).
  • vehicles which are pharmaceutically acceptable for a formulation capable of being injected (like lipiodol, gelfoam, ivalon).
  • These may be in particular isotonic, sterile, saline solutions (monosodium or disodium phosphate, sodium, potassium, calcium or magnesium chloride and the like or mixtures of such salts), or dry, especially freeze-dried compositions which upon addition, depending on the case, of sterilized water or physiological saline, permit the constitution of injectable solutions.
  • the doses used for the administration can be adapted as a function of various parameters, and in particular as a function of the mode of administration used, of the relevant pathology, or alternatively of the desired duration of treatment.
  • FIG. 1 Periportal-type HCCs show the most favorable clinical features and the highest early (2-year) disease-free and overall survival rates after resection.
  • A Clinical features of HCC subclasses in a 247-patient dataset(34).
  • B Kaplan-Meier plots of subclass- specific overall and disease-free survival; *P ⁇ 0.05, **P ⁇ 0.01, ***P ⁇ 0.001.
  • C Subclass- specific clinical features, CTNNB1 and TP53 mutation rates (full genome sequencing) in an external validation 210-HCC RNAseq dataset (TGCA-LIHC-US).
  • D Subclass -specific mPvNA expression levels of Periportal HCC signature genes in 1133 HCCs.
  • E Kaplan- Meier plots of overall and disease-free survival in HCC patients with and without the Periportal HCC signature in two datasets.
  • AFP serum alpha-fetoprotein
  • NA serum alpha-fetoprotein
  • BCLC Barcelona Clinic Liver Cancer
  • CLIP Cancer of the Liver Italian Program.
  • Probes detected over background in at least one HCC were quantile normalized (R package preprocessCore) and log2 intensity expression values for each probe set were calculated by Robust Multi-array Average Cross-platform and batch-dependent variances were corrected with COMBAT(l l) (R package sva) in the 1133-HCC metadata set and with YuGene(12) (R package YuGene) in the datasets used for CTNNB 1 mutation prediction.
  • a robust 5- gene score predicts CTNNB 1 mutations in large transcriptomic datasets As described in the Patients and Methods section, nine public transcriptomic datasets were integrated into a metadata set of 1133 HCCs and 9542 genes (data not sown). The 1133- HCC transcriptomic dataset was not annotated for CTNNB 1 mutational status; thus, we set up a robust pipeline to predict CTNNB 1 activating mutations (data not shown). The model achieved a prediction accuracy of 87% in the training set and 93% in the independent validation sets (data not shown).
  • HAL Histidine Ammonia-Lyase
  • VNN1 Vanin 1
  • nuclear ⁇ -catenin immuno staining was positively correlated with CTNNBl mutations, GLUL, ODAM and LGR5 and negatively with VNNl and HAL and (data not shown).
  • Tissue microarray-based immunohistochemistry in 20 HCCs carrying mutant versus 20 HCCs carrying wild-type CTNNBl revealed a clear-cut difference in GLUL expression between HCCs showing mutant versus wild-type CTNNBl at low power microscopic examination, whereas HAL and VNNl were globally higher in wild-type samples (data not shown).
  • ODAM protein expression was low in all samples (not shown), but detected in HCCs carrying mutant CTNNBl and expressing high GLUL (data not shown).
  • HAL HCC cell lines carrying wild- type CTNNBl, i.e., Huh7 or HepaRG, than in those carrying activating CTNNBl mutations, i.e., B16, BC2, HepG2 and Huh-6.
  • VNNl was expressed at much higher levels in HepaRG cells than in the cell lines carrying mutant CTNNBl.
  • Huh7 expressed VNNl at low levels.
  • ODAM was clearly expressed at higher levels in cell lines carrying mutant than in those carrying wild-type CTNNB 1.
  • the GSK3P inhibitor e-bromoindirubin-S -oxime (BIO), which activates ⁇ -catenin signaling,(17) strongly upregulated ⁇ -catenin-dependent transcriptional activity (data not shown).
  • BIO upregulated GLUL, LGR5 and ODAM (data not shown) and attenuated the increase in HNF4A, ALDOB, HAL and VNN1 mRNA expression over the 30 days required for differentiation of HepaRG progenitors to hepatocyte-like cells (data not shown).
  • HepaRG cells transfected with ⁇ -catenin targeting siRNA downregulated AXIN2 and ODAM and upregulated HAL and VNN1 mRNA expression (data not shown).
  • Predicted CTNNB1 mutations cluster within a homogeneous tumor subclass after analysis of transcriptomic data from 1343 HCCs
  • CTNNB1 was predicted to be mutated in 89% of HCCs (data not shown).
  • the red subclass showed the highest levels of GLUL, LGR5 and ODAM and the lowest levels of VNNl and HAL (data not shown).
  • Well-differentiated HCCs display a preserved metabolic liver zonation program.
  • ECM cancer extracellular matrix
  • HCC integrin cell-surface interactions
  • KRAS integrin cell-surface interactions
  • TGFB TGFB
  • IL6 the MMP14 network typical of invasive tumors.
  • the last HCC subclass was associated with high grade metastasis signatures, tumor aggressiveness with decreased patient survival,(23) the cancer stem cell program predicting metastasis and death(25) and upregulation of p53 mutation markers (data not shown). It was also enriched in signatures of cell cycle progression (MYC, RAC, AURKA, RBI and PDGFRB pathways), HCCs displaying stem cell features(26) and extrahepatic undifferentiated cancers of various origins, as well as cancer cell resistance to doxorubicin and vincristine. Thus, we called this subclass "STEM-type HCCs".
  • ECM- and STEM-type HCCs shared signatures of high tumor cell proliferation ⁇ ) and were associated with the Wnt/TGF- ⁇ (SI) HCC subclass, (5) indicating bad prognosis. (27) Also, they were both associated with early recurrence(28). Functional genomics findings were confirmed by gene ontology analysis of gene clusters (data not shown).
  • TCF4, ⁇ -catenin and HNF4A(20) governs the differential distribution of metabolic liver functions along the porto-central axis of the liver, which is known as "liver zonation".
  • HNF4A HNF4A-KO mice
  • Hnf4a-WT Hnf4a-WT mice
  • a first cluster was strongly upregulated in Hnf4a-KO mice and clearly enriched in genes upregulated in ECM/STEM HCCs.
  • a second cluster was downregulated in Hnf4a-KO mice and enriched in genes upregulated in Periportal-type HCCs. The rest of the genes (20%) were poorly affected by HNF4A.
  • Periportal-type HCCs show the most favorable clinical features and the highest early (2- year) disease-free and overall survival rates after resection
  • the Periportal-type is a well-differentiated, favorable-outcome HCC subclass carrying wild-type CTNNB1, displaying a periportal liver metabolic program and expressing HNF4A target genes.
  • the Peri venous-type is a well-differentiated HCC subclass carrying mutant CTNNB1, displaying a perivenous liver metabolic program and expressing ⁇ -catenin target genes.
  • STEM-type HCCs The overall survival of Perivenous-type HCCs was significantly more favorable than that of STEM-type HCCs in both the 247-HCC transcriptomic (Fig. IB) and in the 210-HCC RNAseq (data not shown) datasets.
  • a Periportal-type HCC gene signature we searched for genes meeting the following criteria: >2 fold change between the Periportal and the other HCC subclasses; high connectivity within the periportal gene network in HCCs (>0.30 correlation coefficient with >50% of the genes) and association with survival (p ⁇ 0.05 in >7/8 tests.
  • the resulting 8-gene Periportal-type HCC signature (Fig. ID) was associated with favorable overall and disease-free outcome in the 247-HCC transcriptomic (34) (Fig. IE) and in the 210-HCC RNAseq (Fig. IF) datasets.
  • Periportal-type HCCs showed the lowest early (2-year) recurrence and the highest overall survival rates after resection among all other HCCs taken together. Univariate and multivariate survival analysis revealed that the Periportal-type HCC signature was independently associated with low early recurrence after HCC resection.
  • the Periportal-type HCC signature was predominantly expressed in normal liver, as shown by analysis of their mRNA expression levels in 84 tissues, (35, 36) from the GSE1133 microarray dataset (data not shown).
  • the expression levels of the eight genes constituting the signature were highly correlated (data not shown). These genes were expressed at higher levels in Periportal-type HCCs than in the other HCC subclasses (Fig. ID).
  • the expression levels of these genes in 70 Periportal HCCs were closer to those detected in 232 non-tumor livers than in 167 non-Periportal HCCs. Two of these genes (AGXT and OTC) were not significantly different in non-tumor livers from Periportal HCCs (data not shown).
  • Example 2 Exploration of the impact of phenotypic diversity in the outcome of Peri venous-type HCCs.
  • HepaRG cells expressing mutated CTNNBl confirmed the specificity of the mutation markers GLUL, LGR5, HAL, VNN1 and ODAM (data not shown).
  • HCCs with mutated CTNNBl Discriminant analyses revealed the phenotypic diversity of HCCs with mutated CTNNBl, which ranged from well-differentiated tumors with hepatocyte-like features to HCCs expressing a stem/progenitor-like cell program. Thus, HCCs with mutated CTNNBl could develop substantial cancer stem/progenitor cell subpopulations overtime. Conclusions: Albeit non-proliferative, HCCs with mutant CTNNBl may evolve toward an undifferentiated phenotype with bad outcome, which justifies early HCC detection.
  • Bonzo JA Ferry CH, Matsubara T, Kim JH, Gonzalez FJ. Suppression of hepatocyte proliferation by hepatocyte nuclear factor 4alpha in adult mice. The Journal of biological chemistry 2012;287:7345-7356.
  • Odontogenic ameloblast-associated protein inhibits growth and migration of human melanoma cells and elicits PTEN elevation and inactivation of PI3K/AKT signaling.
  • Minguez B Hoshida Y, Villanueva A, Toffanin S, Cabellos L, Thung S, Mandeli J, et al. Gene-expression signature of vascular invasion in hepatocellular carcinoma. Journal of hepatology 2011;55: 1325-1331.
  • Neoangiogenesis-related genes are hallmarks of fast-growing hepatocellular carcinomas and worst survival. Results from a prospective study. Gut 2016;65:861-869.

Abstract

The invention relates to the prediction of the outcome of a patient suffering from HCC. This study was conducted to determine whether non-proliferative HCCs carrying wild-type CTNNB1 warrant consideration as a distinct, clinically relevant tumor subclass. The inventors constructed an 1133-HCC transcriptomic metadata set and identified four HCC subclasses by discriminant analyses and hierarchical clustering. They developed a method to predict CTNNB1 mutations in an independent set of 225 β-catenin-sequenced HCCs and validated HCC classification, CTNNB1 mutation prediction and survival analyses in an independent 210-HCC full-genome sequenced RNAseq dataset. Altogether, analysis of data from 1568 HCC patients identified two new well-differentiated, low-proliferation subclasses of HCCs. Both subclasses (periportal-type and perivenous-type) showed favorable outcomes. Periportal-type HCCs showed the highest 2-year recurrence-free survival rates by multivariate analysis, suggesting that these tumors have the lowest potential for early recurrence among all HCCs. Thus, the invention relates to a method for predicting the survival time of a patient suffering from HCC comprising determining the expression level of the genes elected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7.

Description

METHOD FOR PREDICTING THE SURVIVAL TIME OF A PATIENT SUFFERING FROM HEPATOCELLULAR CARCINOMA
FIELD OF THE INVENTION:
The present invention relates to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma (HCC) comprising: i) determining, in a sample obtained from the patient, the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7; ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression levels determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values. BACKGROUND OF THE INVENTION:
Hepatocellular carcinoma (HCC) is the 3rd leading cause of cancer-related death worldwide. HCC is endemic in East Asia and sub-Saharan Africa, and its incidence has doubled over the past 20 years in Western countries. Projections anticipate a further increase in incidence, despite recent breakthroughs in the management of chronic hepatitis.(l) More than 80% of HCCs arise in a field of chronic liver disease resulting from viral hepatitis, alcohol, hemochromatosis, obesity and metabolic syndrome or genotoxins. This diversity in etiology and natural history results in high HCC heterogeneity, raising major challenges in clinical management.(l)
Current therapeutic strategies are based upon tumor number, size, vascular invasion, performance status and functional reserve of the liver. These variables have been integrated in the Barcelona Clinic Liver Cancer (BCLC) classification to match the best candidates with the best therapies available.(l) Surveillance programs currently detect early-stage tumors (single or < 3 nodules < 3 cm) that are candidates for potentially curative therapies (local ablation, resection or transplantation) with 5-year survival rates of 50-70%. Five-year recurrence rates after HCC resection (up to 70%) or even higher after percutaneous ablation make liver transplantation the best possible treatment, with a recurrence rate of 10% and the additional advantage of eliminating the underlying liver disease. (1) Treatment allocation for early-stage HCCs might be improved by identifying homogeneous molecular subclasses with predictable outcomes. (2, 3) The molecular landscape of HCCs is emerging as a result of global gene expression analyses and the discovery of crucial driver tumor mutations. (1, 2) At present, HCCs are split into two molecular classes, each representing 50% of tumors: proliferative and nonproliferative HCCs. (2) Proliferative HCCs include two subclasses enriched in WNT/TGFB signals and stem/progenitor cell markers, respectively.(l, 2) Among non-proliferative HCCs, half of the tumors form a homogeneous subclass with a high rate of activating β-catenin (CTNNBl) exon 3 mutations. (2, 4-6) These tumors are well-differentiated, (2, 4-8) but patient survival rates do not differ from HCCs carrying wild-type CTNNBl. The rest of nonproliferative HCCs carry wild-type CTNNB1,(5) but no evidence to date allowed them to qualify as a homogeneous HCC subclass.
SUMMARY OF THE INVENTION:
This study was conducted to determine whether non-proliferative HCCs carrying wild- type CTNNBl warrant consideration as a distinct, clinically relevant tumor subclass. To analyze a large and statistically powerful population, the inventors constructed an 1133-HCC transcriptomic metadata set and identified four HCC subclasses by discriminant analyses and hierarchical clustering. As the 1133 HCCs were not annotated for CTNNBl mutations, they developed a reliable method to predict CTNNBl mutations in an independent set of 225 β- catenin- sequenced HCCs. CTNNBl mutation prediction, HCC classification and survival analyses were further validated in an external full-genome sequenced RNAseq dataset of 210 HCC patients.
Altogether, analysis of data from 1568 HCC patients identified two new well- differentiated, mutually exclusive, low-proliferation subclasses of HCCs. Both subclasses showed favorable outcomes and preserved metabolic liver zonation programs. They respectively displayed periportal (wild-type β-catenin) or perivenous (mutant β-catenin) phenotypes. Periportal-type HCCs showed the highest 2-year recurrence-free survival rates by multivariate analysis, suggesting that these tumors have the lowest potential for early (< 2 years) recurrence among all HCCs. Thus, the inventors established 1) a first signature consisting of 5 genes which is suitable for predicting β-catenin mutations and 2) a second signature of at least 6 genes which is also suitable for predicting the survival time of a patient suffering from a specific subclass of HCC (Periportal-type HCCs).
Thus, the present invention relates to a method for predicting the survival time of a patient suffering from hepatocellular carcinoma (HCC) comprising: i) determining, in a sample obtained from the patient, the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7; ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression levels determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values. Particularly, the invention is defined by its claims.
DETAILED DESCRIPTION OF THE INVENTION:
A first aspect of the invention relates to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma (HCC) comprising: i) determining, in a sample obtained from the patient, the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7; ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression levels determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
In other words, the expression levels of all of the genes are determined. Thus, in a particular, the invention relates to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma (HCC) comprising: i) determining, in a sample obtained from the patient, the expression level of the genes selected in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7; ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression levels determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
In one embodiment, the measurement of the expression level of at least one gene in the group consisting of OTC and SLC27A5 may be added to the method for predicting the survival time of a patient suffering from a hepatocellular carcinoma.
Thus, in another aspect, the invention relates to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and OTC ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
In other word, the invention relates to to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and OTC ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
Thus, in another aspect, the invention relates to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
In another aspect, the invention relates to a method for predicting the survival time of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7, OTC and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
Another aspect of the invention relates to a method for predicting the overall survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
Another aspect of the invention relates to a method for predicting the overall survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and OTC ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
Another aspect of the invention relates to a method for predicting the overall survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
Another aspect of the invention relates to a method for predicting the overall survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7, OTC and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
Another aspect of the invention relates to a method for predicting the disease-free- survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
Another aspect of the invention relates to a method for predicting the disease-free- survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and OTC ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
Another aspect of the invention relates to a method for predicting the disease-free- survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7 and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
Another aspect of the invention relates to a method for predicting the disease-free- survival of a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7, OTC and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression level determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression level determined at step i) are lower than their predetermined reference values.
According to all the methods of the invention, the expression levels of all the genes are determined. A second aspect of the invention relates to a method for predicting at least a mutation of the CTNNB1 gene in a patient suffering from hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in HAL, VNN1, ODAM, GLUL and LGR5; ii) computing a CTNNB1 mutation score conceived by the inventors thanks to these expression levels of the genes and; iii) comparing said CTNNBl mutation score determined at step ii) with its predetermined reference value to determine if there is at least a mutation on the CTNNBl gene or no mutation on the CTNNBl gene.
In a particular embodiment, the invention relates to a method for predicting at least a mutation of the CTNNBl gene in a patient suffering from hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in HAL, VNN1, ODAM, GLUL and LGR5; ii) computing a CTNNBl mutation score conceived by the inventors, as follows:
„„ Τ ΤΤ1 1 . GLUL LGR5 ODAM
C1NNB1 mutation score =
HAL VNN1
where the gene symbols denote mRNA or protein expression levels of each one of the genes,
iii) comparing the CTNNBl mutation score determined at step ii) with its predetermined reference value and iv) providing that there is at least a mutation on the CTNNBl gene when the CTNNBl mutation score determined at step ii) is higher than its predetermined reference value, or providing that there is no mutation on the β-catenin gene when the CTNNBl mutation score determined at step ii) is lower than its predetermined reference value.
Identifying a CTNNBl mutation in a hepatocellular carcinoma indicates that the patient suffering from this cancer will have a Perivenous-type HCC. Identifying this subclass of HCC is clinically relevant because: (i) this subclass of liver cancer is characterized by activation of the β-catenin signalling pathway that could be treated by specific inhibitors of this pathway (see for example the patent applications WO2011088127, US7803783 or WO2004032838); (ii) overall survival and disease-free survival rates of patients suffering from HCCs carrying CTNNBl mutations will probably be less favourable than those of patients suffering from Periportal-type HCCs, but more favourable than those of patients suffering from STEM-type HCCs. This classification could thus impact the therapeutic decision along the spectrum of potentially curative treatments for HCC (tumor resection, tumor ablation, liver transplantation) (see for example Mazzaferro V. Squaring the circle of selection and allocation in liver transplantation for HCC: An adaptive approach. Hepatology. 2016 May;63(5): 1707-17. doi: 10.1002/hep.28420. Epub 2016 Feb 26.).
As used herein, the term "Overall survival (OS)" denotes the percentage of people in a study or treatment group who are still alive for a certain period of time after they started treatment for a disease, such as HCC (according to the invention). The overall survival rate is often stated as a five-year survival rate, which is the percentage of people in a study or treatment group who are alive five years after their diagnosis or the start of treatment.
As used herein, the term "Disease-free survival (DFS)"denotes the length of time after primary treatment for a cancer ends that the patient survives without detectable relapse of that cancer (any signs or symptoms of that cancer) or without disease progression.
As used herein, the term "Good Prognosis" denotes a significantly more favourable probability of survival after patient treatment in the group of patients defined as "good prognosis" compared with the group of patients defined as "bad prognosis".
As used herein and according to all aspects of the invention, the term "sample" denotes, blood, peripheral-blood, serum, plasma, and liver tissues obtained by HCC biopsy, HCC resection or liver resection specimens.
As used herein, the term "patient" refers to an individual who is being managed for liver disease and who is susceptible to develop an HCC at any stage of this disease.
As used herein, hepatocellular carcinoma (HCCs) can be proliferative and non- proliferative HCCs. (2) Proliferative HCCs include two subclasses enriched in WNT/TGFB signals and stem/progenitor cell markers, respectively.(l, 2) Non-proliferative HCCs can be periportal or perivenous HCCs, as defined by the inventors. As used herein, HCC can be a "ECM-type HCC" (for Cancer Extracellular Matrix) or an or a STEM-type HCCs (see for example Hoshida , cancer research 2009).
As used herein the term "AGXT", refers to the gene of "Alanine-Glyoxylate
Aminotransferase". The sequence of said gene can be found under the Ensembl accession number ENSG00000172482.
As used herein the term "FETUB", refers to the gene of "Fetuin B". The sequence of said gene can be found under the Ensembl accession number ENSG00000090512.
As used herein the term "GLS2", refers to the gene of "Glutaminase 2". The sequence of said gene can be found under the Ensembl accession number ENSG00000135423.
As used herein the term "GNMT", refers to the gene of "Glycine N-methyltransferase". The sequence of said gene can be found under the Ensembl accession number ENSG00000124713.
As used herein the term "SLC 10A 1 ", refers to the gene of "Solute Carrier Family 10
Member 1 ". The sequence of said gene can be found under the Ensembl accession number ENSG00000100652. As used herein the term "SLC22A7", refers to the gene of "Solute carrier family 22 member 7". The sequence of said gene can be found under the Ensembl accession number ENSG00000137204.
As used herein the term "OTC", refers to the gene of "Ornithine Carbamoyltransferase". The sequence of said gene can be found under the Ensembl accession number ENSG00000036473.
As used herein the term "SLC27A5", refers to the gene of "Solute Carrier Family 27 Member 5 ». The sequence of said gene can be found under the Ensembl accession number ENSG00000083807.
As used herein the term "HAL", refers to the gene of "Histidine ammonia-lyase". The sequence of said gene can be found under the Ensembl accession number ENSG00000084110.
As used herein the term "VNN1", refers to the gene of "Vanin 1". The sequence of said gene can be found under the Ensembl accession number ENSG00000112299.
As used herein the term "ODAM", refers to the gene of "Odontogenic ameloblast- associated protein". The sequence of said gene can be found under the Ensembl accession number ENSG00000109205.
As used herein the term "GLUL", refers to the gene of "Glutamine synthetase". The sequence of said gene can be found under the Ensembl accession number ENSG00000135821.
As used herein the term "LGR5", refers to the gene of "Leucine-rich repeat-containing G-protein coupled receptor 5". The sequence of said gene can be found under the Ensembl accession number ENSG00000139292.
As used herein, the term "CTNNB1" or "β-catenin gene" refers to the gene which encode for the protein β-catenin. The sequence of said gene can be found under the Ensembl accession number ENSG00000168036.
Measuring the expression level of the genes listed above can be done by measuring the gene expression level of these genes and can be performed by a variety of techniques well known in the art.
Typically, the expression level of a gene may be determined by determining the quantity of mRNA. Methods for determining the quantity of mRNA are well known in the art. For example the nucleic acid contained in the samples (e.g., cell or tissue prepared from the patient) is first extracted according to standard methods, for example using lytic enzymes or chemical solutions or extracted by nucleic-acid-binding resins following the manufacturer's instructions. The extracted mRNA is then detected by hybridization (e. g., Northern blot analysis, in situ hybridization) and/or amplification (e.g., RT-PCR).
Other methods of Amplification include ligase chain reaction (LCR), transcription- mediated amplification (TMA), strand displacement amplification (SDA) and nucleic acid sequence based amplification (NASBA).
Nucleic acids having at least 10 nucleotides and exhibiting sequence complementarity or homology to the mRNA of interest herein find utility as hybridization probes or amplification primers. It is understood that such nucleic acids need not be identical, but are typically at least about 80% identical to the homologous region of comparable size, more preferably 85% identical and even more preferably 90-95% identical. In certain embodiments, it will be advantageous to use nucleic acids in combination with appropriate means, such as a detectable label, for detecting hybridization.
Typically, the nucleic acid probes include one or more labels, for example to permit detection of a target nucleic acid molecule using the disclosed probes. In various applications, such as in situ hybridization procedures, a nucleic acid probe includes a label (e.g., a detectable label). A "detectable label" is a molecule or material that can be used to produce a detectable signal that indicates the presence or concentration of the probe (particularly the bound or hybridized probe) in a sample. Thus, a labeled nucleic acid molecule provides an indicator of the presence or concentration of a target nucleic acid sequence (e.g., genomic target nucleic acid sequence) (to which the labeled uniquely specific nucleic acid molecule is bound or hybridized) in a sample. A label associated with one or more nucleic acid molecules (such as a probe generated by the disclosed methods) can be detected either directly or indirectly. A label can be detected by any known or yet to be discovered mechanism including absorption, emission and/ or scattering of a photon (including radio frequency, microwave frequency, infrared frequency, visible frequency and ultra-violet frequency photons). Detectable labels include colored, fluorescent, phosphorescent and luminescent molecules and materials, catalysts (such as enzymes) that convert one substance into another substance to provide a detectable difference (such as by converting a colorless substance into a colored substance or vice versa, or by producing a precipitate or increasing sample turbidity), haptens that can be detected by antibody binding interactions, and paramagnetic and magnetic molecules or materials.
Particular examples of detectable labels include fluorescent molecules (or fluorochromes). Numerous fluorochromes are known to those of skill in the art, and can be selected, for example from Life Technologies (formerly Invitrogen), e.g., see, The Handbook— A Guide to Fluorescent Probes and Labeling Technologies). Examples of particular fluorophores that can be attached (for example, chemically conjugated) to a nucleic acid molecule (such as a uniquely specific binding region) are provided in U.S. Pat. No. 5,866, 366 to Nazarenko et al., such as 4-acetamido-4'-isothiocyanatostilbene-2,2' disulfonic acid, acridine and derivatives such as acridine and acridine isothiocyanate, 5-(2'-aminoethyl) aminonaphthalene-1- sulfonic acid (EDANS), 4-amino -N- [3 vinylsulfonyl)phenyl]naphthalimide-3,5 disulfonate (Lucifer Yellow VS), N-(4-anilino-l- naphthyl)maleimide, antllranilamide, Brilliant Yellow, coumarin and derivatives such as coumarin, 7-amino-4-methylcoumarin (AMC, Coumarin 120), 7-amino-4- trifluoromethylcouluarin (Coumarin 151); cyanosine; 4',6-diarninidino-2-phenylindole (DAPI); 5',5"dibromopyrogallol-sulfonephthalein (Bromopyrogallol Red); 7 -diethylamino -3 (4'-isothiocyanatophenyl)-4-methylcoumarin; diethylenetriamine pentaacetate; 4,4'- diisothiocyanatodihydro-stilbene-2,2'-disulfonic acid; 4,4'-diisothiocyanatostilbene-2,2'- disulforlic acid; 5-[dimethylamino] naphthalene- 1-sulfonyl chloride (DNS, dansyl chloride); 4-(4'-dimethylaminophenylazo)benzoic acid (DABCYL); 4-dimethylaminophenylazophenyl- 4'-isothiocyanate (DABITC); eosin and derivatives such as eosin and eosin isothiocyanate; erythrosin and derivatives such as erythrosin B and erythrosin isothiocyanate; ethidium; fluorescein and derivatives such as 5-carboxyfluorescein (FAM), 5-(4,6diclllorotriazin-2- yDarninofluorescein (DTAF), 2'7'dimethoxy-4'5'-dichloro-6-carboxyfluorescein (JOE), fluorescein, fluorescein isothiocyanate (FITC), and QFITC Q(RITC); 2',7'-difluorofluorescein (OREGON GREEN®); fluorescamine; IR144; IR1446; Malachite Green isothiocyanate; 4- methylumbelliferone; ortho cresolphthalein; nitro tyro sine; pararosaniline; Phenol Red; B- phycoerythrin; o-phthaldialdehyde; pyrene and derivatives such as pyrene, pyrene butyrate and succinimidyl 1 -pyrene butyrate; Reactive Red 4 (Cibacron Brilliant Red 3B-A); rhodamine and derivatives such as 6-carboxy-X-rhodamine (ROX), 6-carboxyrhodamine (R6G), lissamine rhodamine B sulfonyl chloride, rhodamine (Rhod), rhodamine B, rhodamine 123, rhodamine X isothiocyanate, rhodamine green, sulforhodamine B, sulforhodamine 101 and sulfonyl chloride derivative of sulforhodamine 101 (Texas Red); N,N,N',N'-tetramethyl-6-carboxyrhodamine (TAMRA); tetramethyl rhodamine; tetramethyl rhodamine isothiocyanate (TRITC); riboflavin; rosolic acid and terbium chelate derivatives. Other suitable fluorophores include thiol-reactive europium chelates which emit at approximately 617 mn (Heyduk and Heyduk, Analyt. Biochem. 248:216-27, 1997; J. Biol. Chem. 274:3315-22, 1999), as well as GFP, LissamineTM, diethylaminocoumarin, fluorescein chlorotriazinyl, naphthofluorescein, 4,7-dichlororhodamine and xanthene (as described in U.S. Pat. No. 5,800,996 to Lee et al.) and derivatives thereof. Other fluorophores known to those skilled in the art can also be used, for example those available from Life Technologies (Invitrogen; Molecular Probes (Eugene, Oreg.)) and including the ALEXA FLUOR® series of dyes (for example, as described in U.S. Pat. Nos. 5,696,157, 6, 130, 101 and 6,716,979), the BODIPY series of dyes (dipyrrometheneboron difluoride dyes, for example as described in U.S. Pat. Nos. 4,774,339, 5,187,288, 5,248,782, 5,274,113, 5,338,854, 5,451,663 and 5,433,896), Cascade Blue (an amine reactive derivative of the sulfonated pyrene described in U.S. Pat. No. 5,132,432) and Marina Blue (U.S. Pat. No. 5,830,912).
In addition to the fluorochromes described above, a fluorescent label can be a fluorescent nanoparticle, such as a semiconductor nanocrystal, e.g., a QUANTUM DOTTM (obtained, for example, from Life Technologies (QuantumDot Corp, Invitrogen Nanocrystal Technologies, Eugene, Oreg.); see also, U.S. Pat. Nos. 6,815,064; 6,682,596; and 6,649, 138). Semiconductor nanocrystals are microscopic particles having size-dependent optical and/or electrical properties. When semiconductor nanocrystals are illuminated with a primary energy source, a secondary emission of energy occurs of a frequency that corresponds to the handgap of the semiconductor material used in the semiconductor nanocrystal. This emission can he detected as colored light of a specific wavelength or fluorescence. Semiconductor nanocrystals with different spectral characteristics are described in e.g., U.S. Pat. No. 6,602,671. Semiconductor nanocrystals that can he coupled to a variety of biological molecules (including dNTPs and/or nucleic acids) or substrates by techniques described in, for example, Bruchez et al., Science 281 :20132016, 1998; Chan et al., Science 281:2016-2018, 1998; and U.S. Pat. No. 6,274,323. Formation of semiconductor nanocrystals of various compositions are disclosed in, e.g., U.S. Pat. Nos. 6,927, 069; 6,914,256; 6,855,202; 6,709,929; 6,689,338; 6,500,622; 6,306,736; 6,225,198; 6,207,392; 6,114,038; 6,048,616; 5,990,479; 5,690,807; 5,571,018; 5,505,928; 5,262,357 and in U.S. Patent Puhlication No. 2003/0165951 as well as PCT Puhlication No. 99/26299 (puhlished May 27, 1999). Separate populations of semiconductor nanocrystals can he produced that are identifiable based on their different spectral characteristics. For example, semiconductor nanocrystals can he produced that emit light of different colors hased on their composition, size or size and composition. For example, quantum dots that emit light at different wavelengths based on size (565 mn, 655 mn, 705 mn, or 800 mn emission wavelengths), which are suitable as fluorescent labels in the probes disclosed herein are available from Life Technologies (Carlshad, Calif.). Additional labels include, for example, radioisotopes (such as 3 H), metal chelates such as DOTA and DPTA chelates of radioactive or paramagnetic metal ions like Gd3+, and liposomes.
Detectable labels that can he used with nucleic acid molecules also include enzymes, for example horseradish peroxidase, alkaline phosphatase, acid phosphatase, glucose oxidase, beta-galactosidase, beta-glucuronidase, or beta-lactamase.
Alternatively, an enzyme can he used in a metallographic detection scheme. For example, silver in situ hyhridization (SISH) procedures involve metallographic detection schemes for identification and localization of a hybridized genomic target nucleic acid sequence. Metallographic detection methods include using an enzyme, such as alkaline phosphatase, in combination with a water-soluble metal ion and a redox-inactive substrate of the enzyme. The substrate is converted to a redox-active agent by the enzyme, and the redoxactive agent reduces the metal ion, causing it to form a detectable precipitate. (See, for example, U.S. Patent Application Publication No. 2005/0100976, PCT Publication No. 2005/ 003777 and U.S. Patent Application Publication No. 2004/ 0265922). Metallographic detection methods also include using an oxido-reductase enzyme (such as horseradish peroxidase) along with a water soluble metal ion, an oxidizing agent and a reducing agent, again to form a detectable precipitate. (See, for example, U.S. Pat. No. 6,670,113).
Probes made using the disclosed methods can be used for nucleic acid detection, such as ISH procedures (for example, fluorescence in situ hybridization (FISH), chromo genie in situ hybridization (CISH) and silver in situ hybridization (SISH)) or comparative genomic hybridization (CGH).
In situ hybridization (ISH) involves contacting a sample containing target nucleic acid sequence (e.g., genomic target nucleic acid sequence) in the context of a metaphase or interphase chromosome preparation (such as a cell or tissue sample mounted on a slide) with a labeled probe specifically hybridizable or specific for the target nucleic acid sequence (e.g., genomic target nucleic acid sequence). The slides are optionally pretreated, e.g., to remove paraffin or other materials that can interfere with uniform hybridization. The sample and the probe are both treated, for example by heating to denature the double stranded nucleic acids. The probe (formulated in a suitable hybridization buffer) and the sample are combined, under conditions and for sufficient time to permit hybridization to occur (typically to reach equilibrium). The chromosome preparation is washed to remove excess probe, and detection of specific labeling of the chromosome target is performed using standard techniques. For example, a biotinylated probe can be detected using fluorescein-labeled avidin or avidin- alkaline phosphatase. For fluorochrome detection, the fluorochrome can be detected directly, or the samples can be incubated, for example, with fluorescein isothiocyanate (FITC)- conjugated avidin. Amplification of the FrfC signal can be effected, if necessary, by incubation with biotin-conjugated goat antiavidin antibodies, washing and a second incubation with FITC- conjugated avidin. For detection by enzyme activity, samples can be incubated, for example, with streptavidin, washed, incubated with biotin-conjugated alkaline phosphatase, washed again and pre-equilibrated (e.g., in alkaline phosphatase (AP) buffer). For a general description of in situ hybridization procedures, see, e.g., U.S. Pat. No. 4,888,278.
Numerous procedures for FISH, CISH, and SISH are known in the art. For example, procedures for performing FISH are described in U.S. Pat. Nos. 5,447,841; 5,472,842; and 5,427,932; and for example, in Pirlkel et al., Proc. Natl. Acad. Sci. 83:2934-2938, 1986; Pinkel et al., Proc. Natl. Acad. Sci. 85:9138-9142, 1988; and Lichter et al., Proc. Natl. Acad. Sci. 85:9664-9668, 1988. CISH is described in, e.g., Tanner et al., Am. .1. Pathol. 157: 1467-1472, 2000 and U.S. Pat. No. 6,942,970. Additional detection methods are provided in U.S. Pat. No. 6,280,929.
Numerous reagents and detection schemes can be employed in conjunction with FISH, CISH, and SISH procedures to improve sensitivity, resolution, or other desirable properties. As discussed above probes labeled with fluorophores (including fluorescent dyes and QUANTUM DOTS®) can be directly optically detected when performing FISH. Alternatively, the probe can be labeled with a nonfluorescent molecule, such as a hapten (such as the following non- limiting examples: biotin, digoxigenin, DNP, and various oxazoles, pyrrazoles, thiazoles, nitroaryls, benzofurazans, triterpenes, ureas, thioureas, rotenones, coumarin, courmarin-based compounds, Podophyllotoxin, Podophyllotoxin-based compounds, and combinations thereof), ligand or other indirectly detectable moiety. Probes labeled with such non-fluorescent molecules (and the target nucleic acid sequences to which they bind) can then be detected by contacting the sample (e.g., the cell or tissue sample to which the probe is bound) with a labeled detection reagent, such as an antibody (or receptor, or other specific binding partner) specific for the chosen hapten or ligand. The detection reagent can be labeled with a fluorophore (e.g., QUANTUM DOT®) or with another indirectly detectable moiety, or can be contacted with one or more additional specific binding agents (e.g., secondary or specific antibodies), which can be labeled with a fluorophore.
In other examples, the probe, or specific binding agent (such as an antibody, e.g., a primary antibody, receptor or other binding agent) is labeled with an enzyme that is capable of converting a fluorogenic or chromogenic composition into a detectable fluorescent, colored or otherwise detectable signal (e.g., as in deposition of detectable metal particles in SISH). As indicated above, the enzyme can be attached directly or indirectly via a linker to the relevant probe or detection reagent. Examples of suitable reagents (e.g., binding reagents) and chemistries (e.g., linker and attachment chemistries) are described in U.S. Patent Application Publication Nos. 2006/0246524; 2006/0246523, and 2007/ 01 17153.
It will be appreciated by those of skill in the art that by appropriately selecting labelled probe- specific binding agent pairs, multiplex detection schemes can he produced to facilitate detection of multiple target nucleic acid sequences (e.g., genomic target nucleic acid sequences) in a single assay (e.g., on a single cell or tissue sample or on more than one cell or tissue sample). For example, a first probe that corresponds to a first target sequence can he labelled with a first hapten, such as biotin, while a second probe that corresponds to a second target sequence can be labelled with a second hapten, such as DNP. Following exposure of the sample to the probes, the bound probes can he detected by contacting the sample with a first specific binding agent (in this case avidin labelled with a first fluorophore, for example, a first spectrally distinct QUANTUM DOT®, e.g., that emits at 585 mn) and a second specific binding agent (in this case an anti-DNP antibody, or antibody fragment, labelled with a second fluorophore (for example, a second spectrally distinct QUANTUM DOT®, e.g., that emits at 705 mn). Additional probes/binding agent pairs can he added to the multiplex detection scheme using other spectrally distinct fluorophores. Numerous variations of direct, and indirect (one step, two step or more) can he envisioned, all of which are suitable in the context of the disclosed probes and assays.
Probes typically comprise single-stranded nucleic acids of between 10 to 1000 nucleotides in length, for instance of between 10 and 800, more preferably of between 15 and 700, typically of between 20 and 500. Primers typically are shorter single- stranded nucleic acids, of between 10 to 25 nucleotides in length, designed to perfectly or almost perfectly match a nucleic acid of interest, to be amplified. The probes and primers are "specific" to the nucleic acids they hybridize to, i.e. they preferably hybridize under high stringency hybridization conditions (corresponding to the highest melting temperature Tm, e.g., 50 % formamide, 5x or 6x SCC. SCC is a 0.15 M NaCl, 0.015 M Na-citrate).
The nucleic acid primers or probes used in the above amplification and detection method may be assembled as a kit. Such a kit includes consensus primers and molecular probes. A preferred kit also includes the components necessary to determine if amplification has occurred. The kit may also include, for example, PCR buffers and enzymes; positive control sequences, reaction control primers; and instructions for amplifying and detecting the specific sequences.
In a particular embodiment, the methods of the invention comprise the steps of providing total RNAs extracted from cumulus cells and subjecting the RNAs to amplification and hybridization to specific probes, more particularly by means of a quantitative or semiquantitative RT-PCR.
In another preferred embodiment, the expression level is determined by DNA chip analysis. Such DNA chip or nucleic acid microarray consists of different nucleic acid probes that are chemically attached to a substrate, which can be a microchip, a glass slide or a micro sphere- sized bead. A microchip may be constituted of polymers, plastics, resins, polysaccharides, silica or silica-based materials, carbon, metals, inorganic glasses, or nitrocellulose. Probes comprise nucleic acids such as cDNAs or oligonucleotides that may be about 10 to about 60 base pairs. To determine the expression level, a sample from a test subject, optionally first subjected to a reverse transcription, is labelled and contacted with the microarray in hybridization conditions, leading to the formation of complexes between target nucleic acids that are complementary to probe sequences attached to the microarray surface. The labelled hybridized complexes are then detected and can be quantified or semi-quantified. Labelling may be achieved by various methods, e.g. by using radioactive or fluorescent labelling. Many variants of the microarray hybridization technology are available to the man skilled in the art (see e.g. the review by Hoheisel, Nature Reviews, Genetics, 2006, 7:200-210).
In another embodiment, the expression level is determined by metabolic imaging (see for example Yamashita T et al., Hepatology 2014, 60: 1674-1685 or Ueno A et al., Journal of hepatology 2014, 61: 1080-1087). Expression level of a gene may be expressed as absolute expression level or normalized expression level. Typically, expression levels are normalized by correcting the absolute expression level of a gene by comparing its expression to the expression of a gene that is not a relevant for determining the cancer stage of the patient, e.g., a housekeeping gene that is constitutively expressed. Suitable genes for normalization include housekeeping genes such as the actin gene ACTB, ribosomal 18S gene, GUSB, PGK1, TFRC, GAPDH, GUSB, TBP and ABL1. This normalization allows the comparison of the expression level in one sample, e.g., a patient sample, to another sample, or between samples from different sources.
Predetermined reference values used for comparison may comprise "cut-off or "threshold" values that may be determined as described herein. Each reference ("cut-off) value for the genes' expression may be predetermined by carrying out a method comprising the steps of
a) providing a collection of samples from patients suffering of HCC (after diagnosis of HCC for example);
b) determining the expression level of the genes for each sample contained in the collection provided at step a);
c) ranking the tumor tissue samples according to said gene expression level and determining a threshold value above which the expression level is said to be "high" and below which the expression level is said to be "low";
d) quantitatively defining the threshold/cut-off/reference value by determining the number of copies of the said gene corresponding to the threshold/cut-off/reference value; to be done by constructing a calibration curve using known input quantities of cDNA or protein for the said gene;
e) classifying said samples in pairs of subsets of increasing, respectively decreasing, number of members ranked according to their expression level,
f) providing, for each sample provided at step a), information relating to the actual clinical outcome for the corresponding cancer patient (i.e. the duration of the overall survival (OS));
g) for each pair of subsets of samples, obtaining a Kaplan Meier percentage of survival curve;
h) for each pair of subsets of samples calculating the statistical significance (p value) between both subsets
i) selecting as reference value for the expression level, the value of expression level for which the p value is the smallest.
For example the expression level of the genes has been assessed for 100 HCC samples from 100 patients. The 100 samples are ranked according to their expression level. Sample 1 has the highest expression level and sample 100 has the lowest expression level. A first grouping provides two subsets: on one side sample Nr 1 and on the other side the 99 other samples. The next grouping provides on one side samples 1 and 2 and on the other side the 98 remaining samples etc., until the last grouping: on one side samples 1 to 99 and on the other side sample Nr 100. According to the information relating to the actual clinical outcome for the corresponding HCC patient, Kaplan Meier curves are prepared for each of the 99 groups of two subsets. Also for each of the 99 groups, the p value between both subsets was calculated. The reference value is selected such as the discrimination based on the criterion of the minimum p value is the strongest. In other terms, the expression level corresponding to the boundary between both subsets for which the p value is minimum is considered as the reference value. It should be noted that the reference value is not necessarily the median value of expression levels.
In routine work, the reference value (cut-off value) may be used in the present method to discriminate HCC samples and therefore the corresponding patients.
Kaplan-Meier curves of percentage of survival as a function of time are commonly used to measure the fraction of patients living for a certain amount of time after treatment and are well known by the person skilled in the art.
The man skilled in the art also understands that the same technique of assessment of the expression level of a gene should of course be used for obtaining the reference value and thereafter for assessment of the expression level of a gene of a patient subjected to the method of the invention.
Such predetermined reference values of expression level may be determined for any gene defined above.
Another aspect of the invention relates to a chemotherapeutic compound for use in the treatment of HCC in a patient with a bad prognosis as described above.
According to the invention, chemotherapeutic compounds may be selected in the group consisting in: fludarabine, gemcitabine, capecitabine, methotrexate, taxol, taxotere, mercaptopurine, thioguanine, hydroxyurea, cytarabine, cyclophosphamide, ifosfamide, nitrosoureas, platinum complexes such as cisplatin, carboplatin and oxaliplatin, mitomycin, dacarbazine, procarbizine, etoposide, teniposide, campathecins, bleomycin, doxorubicin, idarubicin, daunorubicin, dactinomycin, plicamycin, mitoxantrone, L-asparaginase, doxorubicin, epimbicm, 5-fluorouracil, taxanes such as docetaxel and paclitaxel, leucovorin, levamisole, irinotecan, estramustine, etoposide, nitrogen mustards, BCNU, nitrosoureas such as carmustme and lomustine, vinca alkaloids such as vinblastine, vincristine and vinorelbine, imatimb mesylate, hexamethyhnelamine, topotecan, kinase inhibitors, phosphatase inhibitors, ATPase inhibitors, tyrphostins, protease inhibitors, inhibitors herbimycm A, genistein, erbstatin, temolozomide and lavendustin A. In one embodiment, additional anticancer agents may be selected from, but are not limited to, one or a combination of the following class of agents: alkylating agents, plant alkaloids, DNA topoisomerase inhibitors, anti-folates, pyrimidine analogs, purine analogs, DNA antimetabolites, taxanes, podophyllotoxin, hormonal therapies, retinoids, photosensitizers or photodynamic therapies, angiogenesis inhibitors, antimitotic agents, isoprenylation inhibitors, cell cycle inhibitors, actinomycins, bleomycins, anthracyclines, MDR inhibitors and Ca2+ ATPase inhibitors.
In one embodiment, a more aggressive chemo therapeutic compound may be used to treat patient with bad prognosis. This compound may be the sorafenib for example..
HCC patients with good prognosis may benefit from potentially curative therapies that include but may not be limited to tumor resection, local tumor ablation and liver transplantation. The choice among these alternatives will greatly depend on the functional reserve of the liver, tumor accessibility and localization in the liver, donor liver availability and the intrinsic aggressiveness of the tumor, which can be predicted using different methods to predict survival time in patients with HCC. (See for example: Sapisochin G, Bruix J. Liver transplantation for hepatocellular carcinoma: outcomes and novel surgical approaches. Nature reviews. Gastroenterology & hepatology 2017;14:203-217).
In a particular embodiment, resection of the HCC in the patient with bad prognosis may be done to diminish tumor burden and to provide the best supportive care to the patient. Alternatively, resection of the HCC in the patient with good prognosis may be done to avoid tumor progression while the patient is in the waiting list for liver transplantation. In another embodiment, resection of the HCC in the patient with good prognosis may be done to downstage the patient in such a way that they meet transplantation criteria.
In a particular embodiment, local ablation of the HCC in the patient with good prognosis may be done to avoid tumor progression while the patient is in the waiting list for liver transplantation. In another embodiment, local ablation of the HCC in the patient with good prognosis may be done to downstage the patient in such a way that they meet transplantation criteria.
The choice between local ablation and tumor resection will depend on the localization of the tumor and on the functional liver reserve that will allow the patient to go through surgery without metabolic decompensation. Local tumor ablation enables tumor destruction without destruction of the remaining non-tumor liver. Tumor ablation techniques comprise, but are not limited to, techniques based on radiofrequency, microvawe, alcohol or acetic acid percutaneous injection.
In another particular embodiment, a transplantation of a liver may be realized to treat the patient with good prognosis. In this case, the transplantation has more chances to be successful than a transplantation in a patient with a bad prognosis. Thus, the genes of the invention are in a particular interest to help clinicians to have the best therapeutic answer for the patient.
Another aspect of the invention relates to a therapeutic composition comprising a chemotherapeutic compound for use in the treatment of HCC in a patient with a bad prognosis as described above.
Any therapeutic agent of the invention may be combined with pharmaceutically acceptable excipients, and optionally sustained-release matrices, such as biodegradable polymers, to form therapeutic compositions.
"Pharmaceutically" or "pharmaceutically acceptable" refers to molecular entities and compositions that do not produce an adverse, allergic or other untoward reaction when administered to a mammal, especially a human, as appropriate. A pharmaceutically acceptable carrier or excipient refers to a non-toxic solid, semi-solid or liquid filler, diluent, encapsulating material or formulation auxiliary of any type.
The form of the pharmaceutical compositions, the route of administration, the dosage and the regimen naturally depend upon the condition to be treated, the severity of the illness, the age, weight, and sex of the patient, etc.
The pharmaceutical compositions of the invention can be formulated for a topical, oral, intranasal, parenteral, intraocular, intravenous, intramuscular, intrathecal or subcutaneous administration and the like.
Particularly, the pharmaceutical compositions contain vehicles which are pharmaceutically acceptable for a formulation capable of being injected (like lipiodol, gelfoam, ivalon). These may be in particular isotonic, sterile, saline solutions (monosodium or disodium phosphate, sodium, potassium, calcium or magnesium chloride and the like or mixtures of such salts), or dry, especially freeze-dried compositions which upon addition, depending on the case, of sterilized water or physiological saline, permit the constitution of injectable solutions.
The doses used for the administration can be adapted as a function of various parameters, and in particular as a function of the mode of administration used, of the relevant pathology, or alternatively of the desired duration of treatment.
In addition, other pharmaceutically acceptable forms include, e.g. tablets or other solids for oral administration; time release capsules; and any other form currently can be used. The invention will be further illustrated by the following figures and examples. However, these examples and figures should not be interpreted in any way as limiting the scope of the present invention. FIGURES:
Figure 1. Periportal-type HCCs show the most favorable clinical features and the highest early (2-year) disease-free and overall survival rates after resection. (A) Clinical features of HCC subclasses in a 247-patient dataset(34). (B) Kaplan-Meier plots of subclass- specific overall and disease-free survival; *P<0.05, **P<0.01, ***P<0.001. (C) Subclass- specific clinical features, CTNNB1 and TP53 mutation rates (full genome sequencing) in an external validation 210-HCC RNAseq dataset (TGCA-LIHC-US). (D) Subclass -specific mPvNA expression levels of Periportal HCC signature genes in 1133 HCCs. (E, F) Kaplan- Meier plots of overall and disease-free survival in HCC patients with and without the Periportal HCC signature in two datasets. AFP, serum alpha-fetoprotein; NA, not available; BCLC (Barcelona Clinic Liver Cancer); CLIP (Cancer of the Liver Italian Program). Statistics: Fisher exact test (categorical variables); Student's t test (continuous variables); Log-rank test (survival analyses).
EXAMPLE:
Example 1
Material & Methods
Patients, study design and data management
Nine public transcriptomic datasets passing the quality control analyses were integrated into a metadata set totalizing 1133 HCCs and 9542 genes (data not shown). As HCCs in these datasets were not annotated for CTNNB 1 mutations, we developed a robust prediction method. Complying with REMARK guidelines, identification of CTNNB 1 mutation predictors in a training set (n=87) was confirmed in a validation set (n=56) and in our recently described in- house independent cohort (n=82).(9) The three datasets (data not shown) were annotated for Sanger-sequenced CTNNB 1 exon 3 mutations (data not shown). We thus predicted CTNNB 1 mutational status in the 1133-HCC transcriptomic metadata set. Independently, hierarchical cluster analysis was used in this metadata set to identify robust HCC subclasses. Then, the resulting tumor classification was validated in a 210-HCC patient dataset from The Cancer Genome Atlas (TCGA) consortium(lO) (normalized RNAseq genome-wide mRNA expression, whole genome sequencing and clinical data downloaded in June 2016 from the TCGA website). Out of 294 HCCs with available RNAseq and clinical annotations, 84 met our exclusion criteria (data not shown). Quality control of clinical annotations was performed by studying the relationship between tumor staging and overall/disease-free survival by Kaplan-Meier plots and Log Rank tests (data not shown).
Raw data from publically available transcriptome profiling experiments were extracted from Gene Expression Omnibus. Probes detected over background in at least one HCC were quantile normalized (R package preprocessCore) and log2 intensity expression values for each probe set were calculated by Robust Multi-array Average Cross-platform and batch-dependent variances were corrected with COMBAT(l l) (R package sva) in the 1133-HCC metadata set and with YuGene(12) (R package YuGene) in the datasets used for CTNNB 1 mutation prediction.
Statistical analyses
To optimize the identification of stable gene predictors of CTNNB 1 activating mutations, we applied Sparse Partial Least Squares Discriminant Analysis (sPLS-DA) with bootstrap subsampling (data not shown), as described.(13) After further marker validation in the in-house cohort by real-time PCR, we established a score to predict CTNNB 1 mutations (CTNNB1 mutation score as explained in the description of the patent application). Independently, robust HCC subclasses were identified using hierarchical cluster analysis defined by a stepwise algorithm (data not shown). Survival analyses were performed using the Log Rank test, Kaplan-Meier curves and Cox models. Statistical analyses were performed with R (version 3.3.0).
Results
A robust 5- gene score predicts CTNNB 1 mutations in large transcriptomic datasets As described in the Patients and Methods section, nine public transcriptomic datasets were integrated into a metadata set of 1133 HCCs and 9542 genes (data not sown). The 1133- HCC transcriptomic dataset was not annotated for CTNNB 1 mutational status; thus, we set up a robust pipeline to predict CTNNB 1 activating mutations (data not shown). The model achieved a prediction accuracy of 87% in the training set and 93% in the independent validation sets (data not shown). The analysis identified Histidine Ammonia-Lyase (HAL) and Vanin 1 (VNN1) (selected in >85% of the models after 300 bootstrap runs), which were both downregulated in HCCs carrying mutant CTNNB 1. In addition, a search for the top upregulated genes in HCCs carrying CTNNB 1 mutations identified ODontogenic AMeloblast-associated protein (ODAM). Then, to construct a score predicting CTNNB 1 mutations (CTNNB 1 mutation score as explained in the description of the patent application), we combined HAL, VNNl and ODAM with two well-known markers of CTNNBl activating mutations in HCCs: GLUL and LGR5.(14) RNA expression levels of the five biomarkers were significantly associated with mutant CTNNBl in the three datasets (data not shown). AXIN2, which reflects Wnt/p-catenin pathway activation,(15) was positively correlated with GLUL, LGR5 and ODAM and negatively correlated with HAL and VNNl (data not shown). Cluster analyses confirmed the association of the five markers with CTNNBl mutation (data not shown). In the external validation set, CTNNBl mutation was negatively associated with invasive (Gamma= -0.83, p<10-3) and multinodular (Gamma= -0.56, p=0.02) tumors (data not shown). In turn, nuclear β-catenin immuno staining was positively correlated with CTNNBl mutations, GLUL, ODAM and LGR5 and negatively with VNNl and HAL and (data not shown). Combination of the five markers into an arithmetic score resulted in a reliable prediction in the three datasets (AUROC=0.87-0.90; Sensitivity=0.86-0.91; Specificity=0.83-1; data not shown).
Tissue microarray-based immunohistochemistry in 20 HCCs carrying mutant versus 20 HCCs carrying wild-type CTNNBl revealed a clear-cut difference in GLUL expression between HCCs showing mutant versus wild-type CTNNBl at low power microscopic examination, whereas HAL and VNNl were globally higher in wild-type samples (data not shown). ODAM protein expression was low in all samples (not shown), but detected in HCCs carrying mutant CTNNBl and expressing high GLUL (data not shown).
In the external validation set, analysis of matching HCC and non-tumor samples showed that tumor/non-tumor ratios were highly predictive of CTNNBl mutations (AUROC=0.90, Se 0.87; Sp 0.88) (data not shown). As data from non-tumor tissues were not available in all the transcriptomic datasets, further predictions of CTNNBl mutations were performed with tumor samples. Thus, we predicted CTNNBl mutations in the 1133 HCCs of the metadata set (data not shown). Predicted mutation rates between 20-40% matched the previously described CTNNBl mutation rates in HCC.(16)
To better understand the association of the newly discovered biomarkers (HAL, VNNl and ODAM) with CTNNBl activating mutations, we analyzed human HCC cell lines (data not shown). HAL was expressed at higher levels in HCC cell lines carrying wild- type CTNNBl, i.e., Huh7 or HepaRG, than in those carrying activating CTNNBl mutations, i.e., B16, BC2, HepG2 and Huh-6. VNNl was expressed at much higher levels in HepaRG cells than in the cell lines carrying mutant CTNNBl. By contrast, Huh7 expressed VNNl at low levels. Last, ODAM was clearly expressed at higher levels in cell lines carrying mutant than in those carrying wild-type CTNNB 1. The GSK3P inhibitor e-bromoindirubin-S -oxime (BIO), which activates β-catenin signaling,(17) strongly upregulated β-catenin-dependent transcriptional activity (data not shown). BIO upregulated GLUL, LGR5 and ODAM (data not shown) and attenuated the increase in HNF4A, ALDOB, HAL and VNN1 mRNA expression over the 30 days required for differentiation of HepaRG progenitors to hepatocyte-like cells (data not shown). Conversely, HepaRG cells transfected with β-catenin targeting siRNA downregulated AXIN2 and ODAM and upregulated HAL and VNN1 mRNA expression (data not shown). In addition, in silico analysis of the 5000 base pairs upstream the transcription start site of ODAM DNA (NM_017855; PROMO program,(18) TRANSFAC database), revealed three putative TCF-4/LEF-1 consensus transcription factor binding sites in the ODAM 5'UTR region at positions -99; -1262 and -3956. Taken together, these data suggest that β-catenin signaling regulates HAL, VNN1 and ODAM mRNA expression.
Predicted CTNNB1 mutations cluster within a homogeneous tumor subclass after analysis of transcriptomic data from 1343 HCCs
We integrated the nine datasets into an 1133 HCC metadata set with 9542 common genes and performed cross-platform normalization with the COMBAT algorithm(l 1) (data not shown). Identification of the 1618 most discriminant genes by partial least squares discriminant analysis (PLS-DA), using a VIP score threshold >1, followed by stepwise hierarchical cluster analysis, identified four subclasses. Subclasses were named red, green, blue and purple before further functional characterization (data not shown). The red subclass had a predicted CTNNB1 mutation rate of 84% (data not shown). The predicted CTNNB1 mutation rates in this subclass were high in all datasets (65% to 100%). These findings are consistent with previous evidence that HCCs carrying CTNNB1 mutation are a homogeneous subclass. (4, 6)
Reproducibility (data not shown) and robustness (data not shown) analyses showed that the red and green subclasses had similarly low intra-cluster inertia, indicating high homogeneity of HCC samples within each cluster. In terms of gene expression profiles, the purple cluster was highly different from the red and green ones, whereas the blue cluster was intermediate between the green and purple ones (data not shown). To further test the robustness of the HCC classification, we repeated PLS-DA-based identification of the most discriminant genes with a more stringent VIP score threshold (>1.5), which yielded 550 top discriminant genes and confirmed the four tumor subclasses (data not shown). Further, the value of the 550-geneset as a classifier was confirmed in the external validation RNAseq dataset (n= 210 HCCs). Thus, using the top 550 genes, both the 1133-HCC transcriptomic (data not shown) and the 210-HCC RNAseq (data not shown) datasets confirmed four HCC subclasses and three gene sets. In the red subclass, CTNNB1 was predicted to be mutated in 89% of HCCs (data not shown). In consistency with the high rate of predicted CTNNBl mutations, the red subclass showed the highest levels of GLUL, LGR5 and ODAM and the lowest levels of VNNl and HAL (data not shown).
By immunohistochemistry in human liver (data not shown), GLUL showed a clear perivenous localization, as expected. (19) HAL showed a clear-cut periportal distribution, consistently with its expression by periportal hepatocytes in mice. (20) VNNl was panlobular and was abundantly detected in the cytoplasm and in bile canaliculi in normal liver and in well- differentiated HCCs (data not shown), which goes well with the evidence that VNNl is one of the 59 major proteins in human bile. (21). Further, anti-VNNl staining of bile canaliculi was totally suppressed by the immunogen polypeptide (data not shown). In consistency with the above findings, full genome sequencing data from the independent RNAseq 210-HCC TCGA dataset confirmed that 81% of HCCs within the red subclass carried CTNNBl mutations (data not shown).
Well-differentiated HCCs display a preserved metabolic liver zonation program.
Functional genomics studies by gene set enrichment analysis (GSEA) (data not shown) revealed that the HCC subclass containing the highest rate of predicted CTNNBl mutations (84%) was enriched in signatures of HCCs carrying mutant CTNNBl, such as the G6(6) and the CTNNBl subclasses, (4) as well as perivenous hepatocyte signatures, such as fatty acid and bile salt metabolism. (20) We thus called this subclass "Perivenous-type HCCs" (PV). The HCC subclass enriched in signatures of differentiated periportal hepatocytes (gluconeogenesis, amino acid catabolism, HNF4A-induced genes), (20) good prognosis, (hepatocyte-like (S3) subclass HCCs)(5) and low recurrence, (5, 22) was called "Periportal-type HCCs" (PP). Both PP and PV subclasses were enriched in signatures of favorable survival(23) and low proliferation in HCCs. (4) The HCC subclass featuring signatures of cancer extracellular matrix (ECM) remodeling and epithelial mesenchymal transition(24) was called "ECM-type HCCs". It was characterized by integrin cell-surface interactions, KRAS, TGFB, IL6, and the MMP14 network typical of invasive tumors. The last HCC subclass was associated with high grade metastasis signatures, tumor aggressiveness with decreased patient survival,(23) the cancer stem cell program predicting metastasis and death(25) and upregulation of p53 mutation markers (data not shown). It was also enriched in signatures of cell cycle progression (MYC, RAC, AURKA, RBI and PDGFRB pathways), HCCs displaying stem cell features(26) and extrahepatic undifferentiated cancers of various origins, as well as cancer cell resistance to doxorubicin and vincristine. Thus, we called this subclass "STEM-type HCCs". Both ECM- and STEM-type HCCs shared signatures of high tumor cell proliferation^) and were associated with the Wnt/TGF-β (SI) HCC subclass, (5) indicating bad prognosis. (27) Also, they were both associated with early recurrence(28). Functional genomics findings were confirmed by gene ontology analysis of gene clusters (data not shown).
We observed differences in the percentage of samples in each subclass according to the dataset of origin (data not shown). The sampling technique (1060 resections versus 73 biopsy specimens) had no impact on tumor classification (data not shown). By contrast, cohorts containing >95% HCV (+) HCCs showed a higher rate of PV samples than cohorts with >95% HBV (+) (p= 10-3), in agreement with the well-known positive association of CTNNB1 mutation with HCV and its negative association with HBV. (2)
The metabolic program of Periportal-type HCCs is regulated by HNF4A
The interplay between TCF4, β-catenin and HNF4A(20) governs the differential distribution of metabolic liver functions along the porto-central axis of the liver, which is known as "liver zonation".(29) Using the ortholog genes of the mouse liver periportal and perivenous signatures, (20) we clustered the 326 Periportal-type and the 210 Perivenous-type HCCs from the 1133 HCC metadata set. We observed a remarkable matching of mouse normal liver perivenous genes with Perivenous-type HCCs and mouse normal liver periportal genes with Periportal-type HCCs, thus confirming the identity of both HCC subclasses described above (data not shown). Subsequently, network analysis in the 1133 patient metadata set revealed that periportal and perivenous genes were negatively correlated and respectively upregulated in Periportal-type and Perivenous-type HCCs (data not shown). Predictive markers of CTNNB1 mutation showed high connectivity within this network. GLUL, HAL and LGR5 were connected respectively with 60 (42%), 54 (38%) and 54 (38%) of genes in the network. Although mouse Odam and Vnnl were not present in the original periportal and perivenous signatures, (20) human ODAM and VNN1 were connected respectively with 47 (33%) and 28 (20%) of the genes in human HCCs.
Suppression of HNF4A in mouse liver has profound effects on zonated metabolic functions, (30, 31) cell proliferation(30) and oncogenesis. (32, 33) Consistent with this, the top 550 genes representative of the four HCC subclasses perfectly discriminated Hnf4a-KO and Hnf4a-WT(31) mouse livers (data not shown). Among the 550 genes, a first cluster was strongly upregulated in Hnf4a-KO mice and clearly enriched in genes upregulated in ECM/STEM HCCs. A second cluster was downregulated in Hnf4a-KO mice and enriched in genes upregulated in Periportal-type HCCs. The rest of the genes (20%) were poorly affected by HNF4A. Finally, we extracted from the Hnf4a-KO dataset the genes showing the highest modulation (fold change >2 or <0.5 and Bonferroni adjusted P value <0.01) to look at the expression of their orthologs in the 1133 HCC metadata set (data not shown). Hierarchical clustering of these genes showed a good discrimination of the four subclasses (80% of samples correctly classified), with a strong enrichment of genes highly downregulated by Hnf4a-KO in Periportal-type HCCs. Conversely, genes highly upregulated by Hnf4a-KO were remarkably enriched in the STEM-type HCC subclass. These findings are in line with the notion that HNF4A induces hepatocyte differentiation of cancer stem cells, suppressing hepatocyte proliferation and oncogenesis. (30, 32, 33)
Periportal-type HCCs show the most favorable clinical features and the highest early (2- year) disease-free and overall survival rates after resection
Comparative analysis of the clinical outcome of the four HCC subclasses in a 247-HCC transcriptomic dataset(34) (data not shown) revealed increasingly aggressive tumor phenotypes from Periportal through Perivenous ->ECM STEM HCCs (Fig. 1A). These subclasses showed a progressive increase in metastatic signature(34) rates, CLIP and BCLC scores as well as serum AFP concentrations. Survival curves (Fig. IB) showed a progressive decrease in overall and disease free survival (DF) rates from Periportal through Perivenous ECM
STEM HCCs. Thus, the Periportal-type is a well-differentiated, favorable-outcome HCC subclass carrying wild-type CTNNB1, displaying a periportal liver metabolic program and expressing HNF4A target genes. In turn, the Peri venous-type is a well-differentiated HCC subclass carrying mutant CTNNB1, displaying a perivenous liver metabolic program and expressing β-catenin target genes.
The above data were further validated using an external 210-HCC RNAseq dataset. Tumor aggressiveness was inferred from increasing AFP serum levels, tumor grade, TNM staging, vascular invasion, TP53 mutation rates, tumor onset in younger patients (Fig. 1C), as well as survival (data not shown). This analysis confirmed the existence of increasingly aggressive tumor phenotypes from Periportal-type through Perivenous-type ECM-type
STEM-type HCCs. The overall survival of Perivenous-type HCCs was significantly more favorable than that of STEM-type HCCs in both the 247-HCC transcriptomic (Fig. IB) and in the 210-HCC RNAseq (data not shown) datasets.
To obtain a Periportal-type HCC gene signature, we searched for genes meeting the following criteria: >2 fold change between the Periportal and the other HCC subclasses; high connectivity within the periportal gene network in HCCs (>0.30 correlation coefficient with >50% of the genes) and association with survival (p<0.05 in >7/8 tests. The resulting 8-gene Periportal-type HCC signature (Fig. ID) was associated with favorable overall and disease-free outcome in the 247-HCC transcriptomic (34) (Fig. IE) and in the 210-HCC RNAseq (Fig. IF) datasets. Periportal-type HCCs showed the lowest early (2-year) recurrence and the highest overall survival rates after resection among all other HCCs taken together. Univariate and multivariate survival analysis revealed that the Periportal-type HCC signature was independently associated with low early recurrence after HCC resection.
Of note, the Periportal-type HCC signature was predominantly expressed in normal liver, as shown by analysis of their mRNA expression levels in 84 tissues, (35, 36) from the GSE1133 microarray dataset (data not shown). In addition, the expression levels of the eight genes constituting the signature were highly correlated (data not shown). These genes were expressed at higher levels in Periportal-type HCCs than in the other HCC subclasses (Fig. ID). The expression levels of these genes in 70 Periportal HCCs were closer to those detected in 232 non-tumor livers than in 167 non-Periportal HCCs. Two of these genes (AGXT and OTC) were not significantly different in non-tumor livers from Periportal HCCs (data not shown).
Example 2: Exploration of the impact of phenotypic diversity in the outcome of Peri venous-type HCCs.
Material & Methods
First, to confirm the specificity of our previous 5-gene score used to predict CTNNBl mutations (Hepatology 2017, doi: 10.1002/hep.29254), we retrovirally transduced mutant (T41A) CTNNBl to well-differentiated, hepatocyte-like human HCC cells (HepaRG cell line). Then, we predicted CTNNB 1 mutations in a 242-HCC transcriptomic dataset (GSE 14520) and analyzed 12509 genes by Cox-PLS combined to genetic algorithms to allow feature selection. Cell proliferation was assessed in an independent series of 72 CTNNB l -Sanger-sequenced HCCs by immunohistochemistry for MKI67. Results:
HepaRG cells expressing mutated CTNNBl confirmed the specificity of the mutation markers GLUL, LGR5, HAL, VNN1 and ODAM (data not shown). Analysis of 72 HCCs showed that cell proliferation rates were low in tumors with mutated CTNNBl (Sanger- sequenced or predicted) or with high GLUL staining. As expected, high cell proliferation was associated with HCC recurrence (p = 0.007). However, neither GLUL staining nor CTNNBl mutation rates were associated with recurrence. In the 242-HCC dataset, CTNNBl was predicted to be mutated in 63 and wild-type in 179 tumors. Discriminant analyses revealed the phenotypic diversity of HCCs with mutated CTNNBl, which ranged from well-differentiated tumors with hepatocyte-like features to HCCs expressing a stem/progenitor-like cell program. Thus, HCCs with mutated CTNNBl could develop substantial cancer stem/progenitor cell subpopulations overtime. Conclusions: Albeit non-proliferative, HCCs with mutant CTNNBl may evolve toward an undifferentiated phenotype with bad outcome, which justifies early HCC detection.
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Claims

CLAIMS:
A method for predicting the survival time of a patient suffering from an hepatocellular carcinoma (HCC) comprising: i) determining, in a sample obtained from the patient, the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7; ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression levels determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression levels determined at step i) are lower than their predetermined reference values.
A method according to claim 1 wherein at least one gene in the group consisting of OTC and SLC27A5 may be added.
A method for predicting the survival time of a patient suffering from an hepatocellular carcinoma according to claims 1 or 2 comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1, SLC22A7, OTC and SLC27A5 ii) comparing the expression level of the genes determined at step i) with their predetermined reference values and iii) providing a good prognosis when the expression levels determined at step i) are higher than their predetermined reference values, or providing a bad prognosis when the expression levels determined at step i) are lower than their predetermined reference values.
A method for predicting at least a mutation of the CTNNB1 gene in a patient suffering from an hepatocellular carcinoma comprising i) determining in a sample obtained from the patient the expression level of the genes selected in the group consisting in HAL, VNN1, ODAM, GLUL and LGR5; ii) computing a CTNNB1 mutation score conceived by the inventors thanks to these expression levels of the genes and; iii) comparing said CTNNB1 mutation score determined at step ii) with its predetermined reference value to determine if there is at least a mutation on the CTNNB1 gene or no mutation on the CTNNB1 gene.
A chemotherapeutic compound for use in the treatment of HCC in a patient with prognosis according to the claims 1 to 3. A therapeutic composition comprising a chemotherapeutic compound for use in treatment of HCC in a patient with a bad prognosis according to the claims 1 to 3.
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