WO2020223233A1

WO2020223233A1 - Prognostic and therapeutic methods for colorectal cancer

Info

Publication number: WO2020223233A1
Application number: PCT/US2020/030275
Authority: WO
Inventors: Thomas SANDMANN; Akshata Ramrao UDYAVAR; Anneleen Daemen; Meghna Das Thakur HARRIS
Original assignee: Genentech, Inc.; F. Hoffmann-La Roche Ag
Priority date: 2019-04-30
Filing date: 2020-04-28
Publication date: 2020-11-05

Abstract

Provided herein are prognostic and therapeutic methods for the treatment of colorectal cancer using a prognostic gene signature capturing stromal, proliferative, and immune functions. In particular, the invention provides methods for patient selection, prognosis, and treatment.

Description

PROGNOSTIC AND THERAPEUTIC METHODS FOR COLORECTAL CANCER

SEQUENCE LISTING

The instant application contains a Sequence Listing which has been submitted electronically in ASCII format and is hereby incorporated by reference in its entirety. Said ASCII copy, created on April 27, 2020, is named 50474-196WO2_Sequence_Listing_4_27_20_ST25 and is 30,500 bytes in size.

FIELD OF THE INVENTION

BACKGROUND

Primary colorectal cancers (CRCs) are commonly classified as having high risk or low risk for recurrence of the disease following primary treatment (e.g., surgical resection) using the American Joint Committee on Cancer/Union for International Cancer Control TNM classification system (AJCC/UICC- TNM). Patients having primary CRCs classified as high risk by the AJCC/UICC-TNM generally receive chemotherapy in the adjuvant setting. Common practice for the treatment of surgically resected, node positive CRC is six months of adjuvant treatment with chemotherapy. This strategy is intended to improve cure rates for patients with high-risk primary disease. However, the AJCC/UICC-TNM classification is insufficient in describing prognostic CRC biology and in capturing true high-risk CRC patients, and some patients having cancers that are unlikely to recur are currently classified as high-risk. Current methods thus unnecessarily subject patients having cancers with a low risk of recurrence to aggressive adjuvant chemotherapy.

Thus, there exists an unmet need for robust prognostic methods that more accurately stratify patients with primary CRC into low-risk and high-risk groups for more effective management of the disease.

SUMMARY OF THE INVENTION

The present invention provides prognostic and therapeutic methods for the treatment of colorectal cancer using a prognostic gene signature capturing stromal, proliferative, and immune functions.

In one aspect, the disclosure features a method of predicting disease progression in an individual having a colorectal cancer (CRC), the method comprising determining an AVANT score from a sample from the individual, wherein an AVANT score that is above a reference AVANT score identifies the individual as one who is at high risk of CRC recurrence following surgical resection.

In another aspect, the disclosure features a method of predicting disease recurrence in an individual who has had surgical resection of a CRC, the method comprising determining an AVANT score from a sample from the individual, wherein an AVANT score that is above a reference AVANT score indicates that the individual is at high risk of CRC recurrence. In some aspects, the AVANT score determined from the sample is above the reference AVANT score, and the method further comprises administering to the individual an adjuvant treatment comprising a chemotherapy. In some aspects, the AVANT score is calculated based on the expression levels of CDCA5, DTX2, E2F1, GMNN, KDM1A, ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, TCF12, CD28, CXCL 1, and GZMB. In some aspects, the AVANT score is calculated based on the expression levels of CDCA5, DTX2, E2F1, GMNN, KDM1A, ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, TCF12, CD28, CXCL 1, GZMB, RPLN23, AXIN2, CDKN1B, RPS6KA 1, RHOA, SP2, SHISA5, MLH1, CENPM, CDK2, DNMT1, ANGPT1, IGFBP3, CD36, HBEGF, FOS, SERPINB13, APCDD1, SCD5, POU5F1, EPHA4, FLT1, CDK6, MAPK3, TP73, TAP1, TNF, PDCD1, FCRL5, and CXCR4.

In some aspects, the method further comprises determining a consensus molecular subtype (CMS) of the sample from the individual. In some aspects, the AVANT score determined from the sample is above the reference AVANT score and the CMS of the sample is CMS4.

In some aspects, the reference AVANT score is a score in a reference population of individuals who have had surgical resection of a CRC. In some aspects, the reference population of individuals has been administered an adjuvant treatment comprising a chemotherapy. In some aspects, the sample is obtained from the individual prior to the administration of any adjuvant treatment. In some aspects, the reference AVANT score significantly separates a first and a second subset of individuals based on responsiveness to treatment. In some aspects, responsiveness to treatment is an increase in disease- free survival (DFS), recurrence-free survival (RFS), or overall survival (OS). In some aspects, the reference AVANT score is a pre-assigned score. In some aspects, the reference AVANT score is the 25^th percentile of AVANT scores in the reference population. In some aspects, the reference AVANT score is the 50^th percentile of AVANT scores in the reference population. In some aspects, the reference AVANT score is the 75^th percentile of AVANT scores in the reference population.

In another aspect, the disclosure features a method of predicting disease progression in an individual having a CRC, the method comprising determining an AVANT stromal score and the expression level of GZMB in a sample from the individual, wherein an AVANT stromal score that is above a reference AVANT stromal score and an expression level of GZMB that is below a reference expression level of GZMB identifies the individual as one who is at a high risk of CRC recurrence following surgical resection.

In another aspect, the disclosure features a method of predicting disease recurrence in an individual who has had surgical resection of a CRC, the method comprising determining an AVANT stromal score and the expression level of GZMB in a sample from the individual, wherein an AVANT stromal score that is above a reference AVANT stromal score and an expression level of GZMB that is below a reference expression level of GZMB indicates that the individual is at high risk of CRC recurrence.

In some aspects, the AVANT stromal score is above a reference AVANT stromal score and the expression level of GZMB is below a reference expression level of GZMB, and the method further comprises administering to the individual an adjuvant treatment comprising a chemotherapy. In some aspects, an AVANT stromal score that is below a reference AVANT stromal score and an expression level of GZMB that is above a reference expression level of GZMB identifies the individual as one who is at low risk of CRC recurrence following surgical resection.

In some aspects, the method further comprises determining a CMS of the sample from the individual. In some aspects, the AVANT stromal score determined from the sample is above the reference AVANT stromal score and the CMS of the sample is CMS4.

In some aspects, the AVANT stromal score is calculated based on the expression levels of ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12. In some aspects, the AVANT stromal score is calculated based on the expression levels of ANGPT 1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, and MAPK3.

In some aspects, the reference AVANT stromal score is a score in a reference population of individuals who have had surgical resection of a CRC. In some aspects, the reference population of individuals has been administered an adjuvant treatment comprising a chemotherapy. In some aspects, the sample is obtained from the individual prior to the administration of any adjuvant treatment. In some aspects, the reference AVANT stromal score significantly separates a first and a second subset of individuals based on responsiveness to treatment. In some aspects, responsiveness to treatment is an increase in DFS, RFS, or OS. In some aspects, the reference AVANT stromal score is a pre-assigned score. In some aspects, the reference AVANT stromal score is the median AVANT stromal score in the reference population.

In some aspects, the reference expression level of GZMB is a pre-assigned expression level. In some aspects, the reference expression level of GZMB is the median expression level of GZMB in the reference population.

In another aspect, the disclosure features a method of treating an individual having a CRC, the method comprising (a) determining an AVANT score from a sample from the individual, wherein the AVANT score is above a reference AVANT score; and (b) administering to the individual an adjuvant treatment comprising a chemotherapy.

In another aspect, the disclosure features a method of treating an individual having a CRC, the method comprising administering an adjuvant treatment comprising a chemotherapy to the individual, for whom an AVANT score from a sample from the individual has been determined to be above a reference AVANT score.

In some aspects, the AVANT score is calculated based on the expression levels of CDCA5, DTX2, E2F1, GMNN, KDM1A, ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, TCF12, CD28, CXCL 1, and GZMB. In some aspects, the AVANT score is calculated based on the expression levels of CDCA5, DTX2, E2F1, GMNN, KDM1A, ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, TCF12, CD28, CXCL 1, GZMB, RPLN23, AXIN2, CDKN1B, RPS6KA 1, RHOA, SP2, SHISA5, MLH1, CENPM, CDK2, DNMT1, ANGPT1, IGFBP3, CD36, HBEGF, FOS, SERPINB13, APCDD1, SCD5, POU5F1, EPHA4, FLT1, CDK6, MAPK3, TP73, TAP1, TNF, PDCD1, FCRL5, and CXCR4.

In some aspects, the method further comprises determining a consensus molecular subtype (CMS) of the sample from the individual. In some aspects, the CMS of the CRC is CMS4.

In some aspects, the disclosure features a method of treating an individual having a CRC, the method comprising (a) determining an AVANT stromal score and the expression level of GZMB in a sample from the individual, wherein the AVANT stromal score is above a reference AVANT stromal score and the expression level of GZMB is below a reference expression level of GZMB ; and (b) administering to the individual an adjuvant treatment comprising a chemotherapy.

In some aspects, the disclosure features a method of treating an individual having a CRC, the method comprising administering an adjuvant treatment comprising a chemotherapy to the individual, for whom an AVANT stromal score from a sample from the individual has been determined to be above a reference AVANT stromal score and an expression level of GZMB has been determined to be below a reference expression level of GZMB.

In some aspects, the method further comprises determining a CMS of the sample from the individual. In some aspects, the CMS of the sample is CMS4.

In some aspects, the AVANT stromal score is calculated based on the expression levels of ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12. In some aspects, the AVANT stromal score is calculated based on the expression levels of ANGPT 1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4,

PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, and MAPK3.

In some aspects, the sample is a tissue biopsy, a whole blood sample, a buccal swab, a plasma sample, a serum sample, or a combination thereof. In some aspects, the sample is a tissue biopsy. In some aspects, the sample is an archival sample, a fresh sample, or a frozen sample. In some aspects, the sample is a formalin-fixed paraffin-embedded sample.

In some aspects, the expression level is a nucleic acid expression level. In some aspects, the nucleic acid expression level is a mRNA expression level. In some aspects, the mRNA expression level is determined by direct digital counting of nucleic acids, RNA-seq, RT-qPCR, qPCR, multiplex qPCR or RT-qPCR, microarray analysis, or a combination thereof. In some aspects, the digital counting of nucleic acids is by NANOSTRING^® NCOUNTER^® analysis.

In some aspects, the expression level is a protein expression level. In some aspects, the protein expression level is determined by an immunoassay, liquid chromatography-mass spectrometry (LC-MS) technology, nephelometry, aptamer technology, or a combination thereof.

In some aspects, the CRC is a stage I, stage II, or stage III CRC, according to the TNM classification system at the onset of treatment.

In some aspects, the chemotherapy comprises oxaliplatin, fluorouracil, or leucovorin. In some aspects, the chemotherapy comprises oxaliplatin, fluorouracil, and leucovorin. In some aspects, the chemotherapy consists of oxaliplatin, fluorouracil, and leucovorin. In some aspects, the chemotherapy comprises oxaliplatin and capecitabine. In some aspects, the chemotherapy consists of oxaliplatin and capecitabine. In some aspects, the adjuvant treatment further comprises bevacizumab.

In some aspects, the method further comprises administering to the individual one or more additional therapeutic agents. In some aspects, the one or more additional therapeutic agents comprise an immunomodulatory agent. In some aspects, the immunomodulatory agent is a PD-1 axis binding antagonist. In some aspects, the PD-1 axis binding antagonist is a PD-L1 binding antagonist, a PD-1 binding antagonist, or a PD-L2 binding antagonist. In some aspects, the PD-1 axis binding antagonist is a PD-L1 binding antagonist. In some aspects, the PD-L1 binding antagonist is MPDL3280A

(atezolizumab), YW243.55.S70, MDX-1 105, MEDI4736 (durvalumab), or MSB001071 8C (avelumab). In some aspects, the PD-L1 binding antagonist is MPDL3280A (atezolizumab). In some aspects, the PD-1 axis binding antagonist is a PD-1 binding antagonist. In some aspects, the PD-1 binding antagonist is MDX-1 106 (nivolumab), MK-3475 (pembrolizumab), MEDI-0680 (AMP-514), PDR001 , REGN2810, or BGB-108. In some aspects, the PD-1 axis binding antagonist is a PD-L2 binding antagonist. In some aspects, the PD-L2 binding antagonist is an antibody or an immunoadhesin.

In some aspects, the individual is a human. BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 A is a set of Kaplan-Meier curves for the AVANT signature in the AVANT biomarker evaluable population (BEP) dataset for disease-free survival (DFS). The signature was divided into quartiles as follows:“lowest” = first quartile (< 25^th percentile of AVANT signature scores);“low” = second quartile (>25^,h percentile to 50^th percentile of AVANT signature scores);“high” = third quartile (>50^,h percentile to 75^th percentile of AVANT signature scores,“highest” = fourth quartile (>75^,h percentile of AVANT signature scores). The p-value corresponds to a log-rank test.

Fig. 1 B is a set of Kaplan-Meier curves for the AVANT signature in the independent validation cohort GSE39582 for recurrence-free survival (RFS). The p-value corresponds to a log-rank test.

Fig. 1 C is a correlation plot for the genes in the AVANT signature. Blue denotes positive and red denotes negative correlation. Color intensity denotes the strength of the correlation. Signature genes were assigned to one of four clusters. Red denotes proliferative genes, light and dark green denote stromal genes, and purple denotes immune genes.

Fig. 1 D is a set of Kaplan-Meier curves for the proliferative genes of the AVANT signature for DFS divided at the median in the AVANT BEP dataset.

Fig. 1 E is a set of Kaplan-Meier curves for the immune genes of the AVANT signature for DFS divided at the median in the AVANT BEP dataset.

Fig. 1 F is a set of Kaplan-Meier curves for the stromal genes of the AVANT signature for DFS divided at the median in the AVANT BEP dataset.

Fig. 1 G is a forest plot showing RFS for the validation dataset GSE39582 showing hazard ratios and associated p-values for the AVANT signature, the OncotypeDx signature (Gray et al ., J Clin Oncol, 29(35), 461 1 -4619, 201 1 ), the T-effector signature (Mariathasan et al., Nature, 554: 544-548, 2018), the CAF signature (Isella et al., Nature Genet, 47(4), 312-319, 201 5), and the F-TBRS signature (Calon et al., Cancer Cell, 22: 571 -584, 2012) and a table showing the significance of added prognostic value (if any) provided by each published signature (OncotypeDx signature, T-effector signature, CAF signature, F- TBRS signature, and CMS subtypes (Guinney et al., Nat Med, 21 (1 1 ), 1350-1356, 201 5) when added to the AVANT signature (first column) and the significance of added prognostic value provided by the AVANT signature when added to each of the individual published signatures (second column).

Fig. 2A is a set of Kaplan-Meier curves for granzyme B ( GZMB ) expression stratified by median expression in the AVANT BEP dataset for DFS.

Fig. 2B is a set of Kaplan-Meier curves for granzyme B (GZMB) expression stratified by median expression in the GSE39582 dataset for RFS.

Fig. 2C is a set of Kaplan-Meier curves for the T-effector signature stratified by median expression in the AVANT BEP dataset for DFS.

Fig. 2D is a set of Kaplan-Meier curves for the T-effector signature stratified by median expression in the GSE39582 dataset for RFS.

Fig. 2E is a forest plot showing hazard ratios (HR) and associated P-values for the T-effector signature without GZMB and for GZMB expression in the AVANT BEP dataset for DFS and a table indicating the significance of added prognostic value (if any) provided by the T-effector signature when added to GZMB (first column) and vice versa (second column). Fig. 2F is a forest plot showing hazard ratios (HR) and associated P-values for the T-effector signature without GZMB and for GZMB expression in the GSE39582 dataset for RFS and a table indicating the significance of added prognostic value (if any) provided by the T-effector signature when added to GZMB (first column) and vice versa (second column).

Fig. 2G is a set of Kaplan-Meier curves showing the relationship between GZMB and the proliferative genes of the AVANT signature in the AVANT BEP dataset for DFS. Proliferative signature and GZMB expression were stratified by median expression. P-values correspond to a log-rank test.

Fig. 2H is a set of Kaplan-Meier curves showing the relationship between GZMB and the proliferative genes of the AVANT signature in the GSE39582 dataset for RFS. P-values correspond to a log-rank test.

Fig. 21 is a set of Kaplan-Meier curves showing the relationship between GZMB and the stromal genes of the AVANT signature in the AVANT BEP dataset for DFS. Stromal signature and GZMB expression were stratified by median expression. P-values correspond to a log-rank test.

Fig. 2J is a set of Kaplan-Meier curves showing the relationship between GZMB and the stromal genes of the AVANT signature in the GSE39582 dataset for RFS. P-values correspond to a log-rank test.

Fig. 3A is a box plot showing expression of the T-effector signature by consensus molecular subtype (CMS) in the AVANT BEP dataset. The inset table shows p-values corresponding to a pairwise T-test.

Fig. 3B is a box plot showing expression of the T-effector signature by CMS in the GSE39582 dataset. The inset table shows p-values corresponding to a pairwise T-test.

Fig. 3C is a box plot showing expression of the T-effector signature by microsatellite instability (MSI) status in the AVANT BEP dataset. MSS = microsatellite stable or microsatellite instability low; MSI- H = microsatellite instability high.

Fig. 3D is a Pearson correlation chart showing the correlation between expression of single genes from the T-effector signature and the average expression of the other T-effector genes without the gene in question by colorectal cancer (CRC), CRC CMS 1 , CRC CMS 2, lung cancer, ovary cancer, breast cancer, head and neck cancer, and bladder cancer in The Cancer Genome Atlas (TCGA) data.

Fig. 3E is a box plot showing GZMB expression by CMS in the AVANT BEP dataset. The inset table shows p-values corresponding to a pairwise T-test.

Fig. 3F is a box plot showing GZMB expression by CMS in the GSE39582 dataset. The inset table shows p-values corresponding to a pairwise T-test.

Fig. 3G is a box plot showing GZMB expression by MSI status in the AVANT BEP dataset.

Fig. 3H is a set of Kaplan-Meier curves for GZMB expression stratified by median in 279 CMS2 tumors with low T-effector score from the AVANT BEP dataset for DFS. A T-effector score, excluding GZMB, below the mean score in the full cohort is considered low. The p-value corresponds to a log-rank test.

Fig. 31 is a Pearson correlation chart showing the correlation between the modified T-effector signature (i.e. without granzyme A ( GZMA ) and GZMB) and GZMA or GZMB expression in AVANT patients, by CMS or MSI status. Fig. 3J is a Pearson correlation chart showing the correlation between the modified T-effector signature and GZMA or GZMB expression in GSE39582 patients by CMS.

Fig. 4A is a t-distributed stochastic neighbor embedding (tSNE) map of the CD45+ immune cell populations in 12 procured colorectal cancer (CRC) samples. Clusters representing different cell types are denoted by distinct colors, based on marker expression. Outliers detected by density-based clustering were excluded.

Fig. 4B is a contour plot showing CD8 vs. GZMB expression in CD16+ natural killer (NK) cells. Density is indicated by color.

Fig. 4C is a contour plot showing CDS vs. GZMB expression in plasmacytoid dendritic cells (pDCs). Density is indicated by color.

Fig. 4D is a Pearson correlation chart showing the correlation between expression of single genes from the NK signature and the average expression of the other NK genes without the gene in question by colorectal cancer (CRC), CRC CMS1 , CRC CMS2, lung cancer, ovary cancer, breast cancer, head and neck cancer, and bladder cancer in TCGA data.

Fig. 4E is a box plot showing expression of the NK signature by CMS in the GSE39582 dataset. The inset table shows p-values corresponding to a pairwise T-test.

Fig. 4F is a box plot showing expression of GZMB by CMS in CRC cell lines. The inset table shows p-values corresponding to a pairwise T-test.

Fig. 5A is a set of Kaplan-Meier curves for the three treatment arms in the AVANT BEP dataset for overall survival (OS). FOLFOX4 = oxaliplatin infusion added to Fluorocil and Leucovorin ;

FOLFOX4+Bev = FOLFOX4 plus bevacizumab; XELOX+Bev = oxaliplatin and capecitabine plus bevacizumab. The p-value corresponds to a log-rank test.

Fig. 5B is a set of Kaplan-Meier curves for the three treatment arms in the AVANT BEP dataset for DFS. The p-value corresponds to a log-rank test.

Fig. 6A is a matrix showing expression of 132 CMS classifier genes (rows) in 1062 AVANT patients (columns). The predicted CMSs are denoted for each patient on the top of the chart. The row annotation denotes the subtype in which a given gene is uniquely highly expressed. PAMR: Prediction Analysis of Microarrays for R.

Fig. 6B is a matrix showing expression of 132 CMS classifier genes (rows) in TCGA CRC patients (columns). The CMSs as predicted by the Guinney et al. , Nat Med, 21 (1 1 ): 1350-1362, 2015 random forest algorithm are denoted for each patient on the top of the chart.

Fig. 6C is a box plot showing the percentage of patients classified as having each of the CMSs in the AVANT BEP dataset. Patients that lack CMS classifier gene expression for any subtype are labeled as unclassifiable.

Fig. 6D is a box plot showing the percentage of patients classified as having each of the CMSs in TCGA. Patients that lack CMS classifier gene expression for any subtype are labeled as unclassifiable.

Fig. 6E is a matrix showing expression of 132 CMS classifier genes in the GSE39582 dataset. The CMSs as predicted by the Guinney et al., Nat Med, 21 (1 1 ): 1350-1362, 2015 random forest algorithm are denoted for each patient on the top of the chart. Fig. 6F is a box plot showing the percentage of patients classified as having each of the CMSs in the GSE39582 dataset.

Fig. 7A is a bar graph showing the percentage of patients having no mutations (WT) or at least one mutation (MUT) at an assayed position in KRAS in each CMS in the AVANT BEP dataset.

Fig. 7B is a bar graph showing the percentage of patients having no mutations (WT) or at least one mutation (MUT) at an assayed position in KRAS in each CMS in TCGA.

Fig. 7C is a bar graph showing the percentage of patients having no mutations (WT) or at least one mutation (MUT) at an assayed position in KRAS in each CMS in the GSE39582 dataset.

Fig. 7D is a bar graph showing the percentage of patients having no mutations (WT) or at least one mutation (MUT) at an assayed position in BRAF in each CMS in the AVANT BEP dataset.

Fig. 7E is a bar graph showing the percentage of patients having no mutations (WT) or at least one mutation (MUT) at an assayed position in BRAF in each CMS in TCGA.

Fig. 7F is a bar graph showing the percentage of patients having no mutations (WT) or at least one mutation (MUT) at an assayed position in BRAF in each CMS in the GSE39582 dataset.

Fig. 7G is a bar graph showing the percentage of patients having microsatellite instability status MSI-H or MSS in each CMS in the AVANT BEP dataset.

Fig. 7H is a bar graph showing the percentage of patients having microsatellite instability status MSI-H or MSS in each CMS in TCGA.

Fig. 71 is a bar graph showing the percentage of patients having right or left sidedness of the colon cancer in each CMS in the AVANT BEP dataset.

Fig. 8 is a matrix showing Cox-based elastic net regression results for the identification of genes prognostic for OS in AVANT using alpha values ranging from 0.1 to 0.9. Identified prognostic genes per alpha value are denoted by black tiles.

Fig. 9A is a box plot showing average expression of the proliferative gene cluster of the AVANT signature of Fig. 1 C by the AVANT signature quartiles in the AVANT BEP dataset. The inset table shows p-values computed using the pairwise T-test for each comparison adjusted for multiplicity testing.

Fig. 9B is a box plot showing average expression of the immune gene cluster of the AVANT signature of Fig. 1 C by the AVANT signature quartiles in the AVANT BEP dataset.

Fig. 9C is a box plot showing average expression of the TGFp-enriched stromal gene cluster of the AVANT signature of Fig. 1 C by the AVANT signature quartiles in the AVANT BEP dataset.

Fig. 9D is a box plot showing average expression of the stromal gene cluster of the AVANT signature of Fig. 1 C by the AVANT signature quartiles in the AVANT BEP dataset.

Fig. 9E is a box plot showing average expression of the proliferative gene cluster of the AVANT signature of Fig. 1 C by CMS in the AVANT BEP dataset.

Fig. 9F is a box plot showing average expression of the immune gene cluster of the AVANT signature of Fig. 1 C by CMS in the AVANT BEP dataset.

Fig. 9G is a box plot showing average expression of the TGFp-enriched stromal gene cluster of the AVANT signature of Fig. 1 C by CMS in the AVANT BEP dataset

Fig. 9H is a box plot showing average expression of the stromal gene cluster of the AVANT signature of Fig. 1 C by CMS in the AVANT BEP dataset. Fig. 91 is a matrix showing expression of the AVANT signature genes (prognostic genes; rows) in the AVANT BEP dataset (columns). Red denotes high expression and blue denotes low expression. Patients are annotated by CMS and quartile of the AVANT signature. Row annotation indicates the respective signatures from Fig. 1 C.

Fig. 10A is a box plot showing average expression of the proliferative gene cluster from Fig. 1 C by MSI status in the AVANT BEP dataset. P-values correspond to a T-test.

Fig. 10B is a box plot showing average expression of the immune gene cluster from Fig. 1 C by MSI status in the AVANT BEP dataset.

Fig. 10C is a box plot showing average expression of the two stromal gene clusters combined from Fig. 1 C by MSI status in the AVANT BEP dataset.

Fig. 10D is a set of scatter plots showing correlation between the average expression of the proliferative, immune, and stromal gene clusters of the AVANT signature in the AVANT BEP dataset, with the two stromal gene clusters combined. Pearson correlations are denoted, with font size reflecting significance.

Fig. 11 A is a set of Kaplan-Meier curves for the proliferative gene cluster from Fig. 1 C, stratified by median, in the GSE39582 dataset for RFS. P-values correspond to a log-rank test.

Fig. 11 B is a set of Kaplan-Meier curves for the immune gene cluster from Fig. 1 C, stratified by median, in the GSE39582 dataset for RFS. P-values correspond to a log-rank test.

Fig. 11 C is a set of Kaplan-Meier curves for the two stromal gene clusters combined from Fig.

1 C, stratified by median, in the GSE39582 dataset for RFS. P-values correspond to a log-rank test.

Fig. 12 is a DFS forest plot showing hazard ratios and associated P-values for each individual signature in the AVANT BEP dataset and a table indicating the significance of added prognostic value (if any) provided by each published signature when added to the AVANT signature (first column) and vice versa (second column).

Fig. 13A is a table and a forest plot reporting multivariate analysis results for the AVANT signature in the AVANT dataset. Forest plot denotes the Cox hazard ratios (HR) and p-values for the different signature quartiles after adjustment for clinical covariates. Each individual clinical covariate in each trial was tested for its effect on prognosis (DFS or RFS), and only prognostic covariates were included in the multivariate analyses. Included covariates were age (AGE-CAT), sex, level of carcinoembryonic antigen (CEA) in blood (CEABL), Eastern Cooperative Oncology Group (ECOG) status (ECOGSTAT), and American Joint Committee on Cancer (AJCC) tumor status including lymph node status (i.e. strata).

Fig. 13B is a table and a forest plot reporting multivariate analysis results for the AVANT signature in the GSE39582 dataset. Forest plot denotes the Cox hazard ratios (HR) and p-values for the different signature quartiles after adjustment for clinical covariates. Each individual clinical covariate in each trial was tested for its effect on prognosis (DFS or RFS), and only prognostic covariates were included in the multivariate analyses. Included covariates were age (age.at.diagnosis), sex, tumor stage (tnm.stage), and lymph node status (tnm.n).

Fig. 14 is a set of Kaplan-Meier curves for GZMB expression stratified by median in 177 CMS2 tumors with low T-effector score from the GSE39582 dataset for RFS. A T-effector score, excluding GZMB, below the mean score in the full cohort is considered low. The p-value corresponds to a log-rank test.

Fig. 15A is a heat map showing average expression of each marker across the detected immune cell clusters from Fig. 4A. Shown are column scaled arcsinh transformed intensity values. Red denotes high expression; blue denotes low expression.

Fig. 15B is a bar graph showing the percentage of pooled immune cells from 12 resected stage II or stage III CRC tumors that are of a given type.

Fig. 15C is a Pearson correlation chart showing the correlation between expression of single genes from the pDC signature and the average expression of the other pDC genes without the gene in question by colorectal cancer (CRC), CRC CMS 1 , CRC CMS 2, lung cancer, ovary cancer, breast cancer, head and neck cancer, and bladder cancer in TCGA data.

Fig. 15D is a box plot showing expression of the pDC signature by CMS in the GSE39582 dataset. The inset table shows p-values corresponding to a pairwise T-test.

Fig. 15E is a box plot showing expression of GZMA by CMS in CRC cell lines. The inset table shows p-values corresponding to a pairwise T-test.

Fig. 16A is a box plot showing GZMB expression by cancer type in a cohort of 671 cell lines covering 12 cancer types.

Fig. 16B is a box plot showing GZMA expression by cancer type in a cohort of 671 cell lines covering 12 cancer types.

Fig. 17A is a set of Kaplan-Meier curves for the AVANT signature in the AVANT BEP dataset for overall survival (OS). The p-value corresponds to a log-rank test.

Fig. 17B is a set of Kaplan-Meier curves for the AVANT signature in the independent validation cohort GSE39582 for OS. The p-value corresponds to a log-rank test.

Fig. 17C is a set of Kaplan-Meier curves for the proliferative genes of the AVANT signature for OS divided at the median in the AVANT BEP dataset.

Fig. 17D is a set of Kaplan-Meier curves for the immune genes of the AVANT signature for OS divided at the median in the AVANT BEP dataset.

Fig. 17E is a set of Kaplan-Meier curves for the stromal genes of the AVANT signature for OS divided at the median in the AVANT BEP dataset.

Fig. 17F is a forest plot showing OS for the validation dataset GSE39582 showing hazard ratios and associated p-values for the AVANT signature, the OncotypeDx signature, the T-effector signature, the CAF Isella et al. signature, and the F-TBRS Calon et al. signature and a table showing the significance of added prognostic value (if any) provided by each published signature (OncotypeDx signature, CAF Isella et al. signature, F-TBRS Calon et al. signature, and CMS subtypes signature) when added to the AVANT signature (first column) and the significance of added prognostic value provided by the AVANT signature when added to each of the individual published signatures (second column).

Fig. 18A is a set of Kaplan-Meier curves for the proliferative gene cluster from Fig. 1 C, stratified by median, in the GSE39582 dataset for OS. P-values correspond to a log-rank test.

Fig. 18B is a set of Kaplan-Meier curves for the immune gene cluster from Fig. 1 C, stratified by median, in the GSE39582 dataset for OS. P-values correspond to a log-rank test. Fig. 18C is a set of Kaplan-Meier curves for the two stromal gene clusters combined from Fig.

1 C, stratified by median, in the GSE39582 dataset for OS. P-values correspond to a log-rank test.

Fig. 19A is a set of Kaplan-Meier curves for GZMB expression stratified by median expression in the AVANT BEP dataset for OS.

Fig. 19B is a set of Kaplan-Meier curves for GZMB expression stratified by median expression in the GSE39582 dataset for OS.

Fig. 19C is a set of Kaplan-Meier curves for the T-effector signature stratified by median expression in the AVANT BEP dataset for OS.

Fig. 19D is a set of Kaplan-Meier curves for the T-effector signature stratified by median expression in the GSE39582 dataset for OS.

Fig. 19E is a forest plot showing OS and associated P-values for the T-effector signature without GZMB and for GZMB expression in the AVANT BEP dataset and a table indicating the significance of added prognostic value (if any) provided by the T-effector signature when added to GZMB (first column) and vice versa (second column).

Fig. 19F is a forest plot showing OS and associated P-values for the T-effector signature without GZMB and for GZMB expression in the GSE39582 dataset and a table indicating the significance of added prognostic value (if any) provided by the T-effector signature when added to GZMB (first column) and vice versa (second column).

Fig. 19G is a set of Kaplan-Meier curves showing the relationship between GZMB and the proliferative genes of the AVANT signature in the AVANT BEP dataset for OS. Proliferative signature and GZMB expression were stratified by median expression. P-values correspond to a log-rank test.

Fig. 19H is a set of Kaplan-Meier curves showing the relationship between GZMB and the proliferative genes of the AVANT signature in the GSE39582 dataset for OS. Proliferative signature and GZMB expression were stratified by median expression. P-values correspond to a log-rank test.

Fig. 191 is a set of Kaplan-Meier curves showing the relationship between GZMB and the stromal genes of the AVANT signature in the AVANT BEP dataset for OS. Stromal signature and GZMB expression were stratified by median expression. P-values correspond to a log-rank test.

Fig. 19J is a set of Kaplan-Meier curves showing the relationship between GZMB and the stromal genes of the AVANT signature in the GSE39582 dataset for OS. Stromal signature and GZMB expression were stratified by median expression. P-values correspond to a log-rank test.

Fig. 20 is an OS forest plot showing hazard ratios and associated P-values for each individual signature in the AVANT BEP dataset and a table indicating the significance of added prognostic value (if any) provided by each published signature when added to the AVANT signature (first column) and vice versa (second column).

Fig. 21 A is a table and a forest plot reporting multivariate analysis results for the AVANT signature in the AVANT dataset. Forest plot denotes the Cox hazard ratios (FIR) and p-values for the different signature quartiles after adjustment for clinical covariates. Each individual clinical covariate in each trial was tested for its effect on OS, and only prognostic covariates were included in the multivariate analyses. Included covariates were age (AGE-CAT), sex, level of carcinoembryonic antigen (CEA) in blood (CEABL), Eastern Cooperative Oncology Group (ECOG) status (ECOGSTAT), and American Joint Committee on Cancer (AJCC) tumor status including lymph node status (i.e. strata).

Fig. 21 B is a table and a forest plot reporting multivariate analysis results for the AVANT signature in the GSE39582 dataset. Forest plot denotes the Cox hazard ratios (HR) and p-values for the different signature quartiles after adjustment for clinical covariates. Each individual clinical covariate in each trial was tested for its effect on OS, and only prognostic covariates were included in the multivariate analyses. Included covariates were age (age.at.diagnosis), sex, tumor stage (tnm.stage), and lymph node status (tnm.n).

DETAILED DESCRIPTION OF THE INVENTION

I. DEFINITIONS

As used herein, the singular form“a,”“an,” and“the” includes plural references unless indicated otherwise.

The term“about” as used herein refers to the usual error range for the respective value readily known to the skilled person in this technical field. Reference to“about” a value or parameter herein includes (and describes) aspects that are directed to that value or parameter per se. For example, description referring to“about X” includes description of“X.”

It is understood that aspects of the invention described herein include“comprising,”“consisting,” and“consisting essentially of” aspects.

The term“AVANT score” refers to a numerical value that reflects an aggregated expression level for a set of genes of interest (e.g., the AVANT signature genes set forth in Table 1 or Table 2), wherein one or more genes of the set relate to proliferative biological functions, one or more genes of the set relate to stromal biological functions, and one or more genes of the set relate to immune biological functions, such that the set of genes of interest collectively reflect proliferative, stromal, and immune biological functions. An AVANT score for a set of genes of interest may be determined by aggregation methods known to one skilled in the art and also disclosed herein, including, for example, by calculating the median or mean of all the expression levels of the genes of interest. Before aggregation, the expression level of each gene of interest may be normalized by using statistical methods known to one skilled in the art and also disclosed herein, including, for example, normalized to the expression level of one or more housekeeping genes, or normalized to a total library size, or normalized to the median or mean expression level value across all genes measured. In some instances, before aggregation across multiple genes of interest, the normalized expression level of each gene of interest may be standardized by using statistical methods known to one skilled in the art and also disclosed herein, including, for example, by calculating the Z-score of the normalized expression level of each gene of interest. In some instances, each gene of interest may have an assigned weight score and the AVANT score for a set of genes of interest may be calculated by incorporating the weight score to determine the mean of all the weighted expression level of the genes of interest. An AVANT score may, for example, refer to a numerical value that reflects the aggregated normalized expression level (e.g., median of the normalized expression levels, or mean of the normalized expression levels) for the AVANT signature genes set forth in Table 1 or Table 2). In some instances, an AVANT score may, for example, refer to a numerical value that reflects the aggregated Z-score expression level (e.g., mean of the Z-score normalized expression level, or median of the Z-score normalized expression level) for the AVANT signature genes set forth in Table 1 or Table 2. An AVANT score may be detected in a sample (e.g., a blood sample (e.g., a tissue biopsy, a whole blood sample, a buccal swab, a plasma sample, a serum sample, or a combination thereof)) obtained from an individual (e.g., an individual having a CRC or having had surgical resection of a CRC). In some aspects, an AVANT score that is above a reference AVANT score identifies an individual as one who may benefit from an adjuvant treatment comprising a chemotherapy.

As used herein, the term“reference AVANT score” refers to an AVANT score against which another AVANT score is compared, e.g., to make a diagnostic, predictive, prognostic, and/or therapeutic determination. For example, the reference AVANT score may be derived from expression levels (e.g., for the AVANT signature genes set forth in Table 1 or Table 2) in a reference sample, a reference population, and/or a pre-assigned value (e.g., a cut-off value which was previously determined to significantly (e.g., statistically significantly)) separate a first subset and a second subset of individuals in the reference population based on responsiveness to treatment, e.g., overall survival (OS), disease-free survival (DFS), and/or recurrence-free survival (RFS). It will be appreciated by one skilled in the art that the numerical value for the reference AVANT score may vary depending on the indication (e.g., a cancer (e.g., a CRC, e.g., a stage I, stage II, stage III, or stage IV CRC), the methodology used to detect expression levels (e.g., digital counting of nucleic acids is by NANOSTRING^® NCOUNTER^® analysis), the statistical methods used to generate an AVANT score, and/or the specific combinations of genes examined (e.g., the AVANT signature genes set forth in Table 1 or Table 2).

The term“AVANT stromal score” refers to a numerical value that reflects an aggregated expression level for a set of genes of interest (e.g., a set of genes comprising ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12, e.g., a set of genes comprising ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12, as well as one or more of ANGPT1, IGFBP3, CD36, HBEGF, FOS, SERPINB13, APCDD1, SCD5, POU5F1, EPHA4, FLT1, CDK6, and/or MAPK3, e.g., a set of genes comprising ANGPT1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, and MAPK3), related to stromal biological functions. An AVANT stromal score for a set of genes of interest may be determined by aggregation methods known to one skilled in the art and also disclosed herein, including, for example, by calculating the median or mean of all the expression levels of the genes of interest. Before aggregation, the expression level of each gene of interest may be normalized by using statistical methods known to one skilled in the art and also disclosed herein, including, for example, normalized to the expression level of one or more housekeeping genes, or normalized to a total library size, or normalized to the median or mean expression level value across all genes measured. In some instances, before aggregation across multiple genes of interest, the normalized expression level of each gene of interest may be standardized by using statistical methods known to one skilled in the art and also disclosed herein, including, for example, by calculating the Z-score of the normalized expression level of each gene of interest. In some instances, each gene of interest may have an assigned weight score and the AVANT stromal score for a set of genes of interest may be calculated by incorporating the weight score to determine the mean of all the weighted expression level of the genes of interest. An AVANT stromal score may, for example, refer to a numerical value that reflects the aggregated normalized expression level (e.g., median of the normalized expression levels, or mean of the normalized expression levels) for the set of genes comprising ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12, e.g., a set of genes comprising ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12, as well as one or more of ANGPT1, IGFBP3, CD36, HBEGF, FOS, SERPINB13, APCDD 1, SCD5, POU5F1, EPHA4, FLT1, CDK6, and/or MAPK3, e.g., a set of genes comprising ANGPT1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, and MAPK3. In some instances, an AVANT stromal score may, for example, refer to a numerical value that reflects the aggregated Z-score expression level (e.g., mean of the Z-score normalized expression level, or median of the Z-score normalized expression level) for the set of genes comprising ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12, e.g., a set of genes comprising ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12, as well as one or more of ANGPT1, IGFBP3, CD36, HBEGF, FOS, SERPINB13, APCDD1, SCD5, POU5F1, EPHA4, FLT1, CDK6, and/or MAPK3, e.g., a set of genes comprising ANGPT1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, and MAPK3. An AVANT stromal score may be detected in a sample (e.g., a blood sample (e.g., a tissue biopsy, a whole blood sample, a buccal swab, a plasma sample, a serum sample, or a combination thereof)) obtained from an individual (e.g., an individual having a CRC or having had surgical resection of a CRC). In some aspects, an AVANT stromal score that is above a reference AVANT stromal score, when associated with an expression level of GZMB that is below a reference expression level of GZMB, identifies an individual as one who may benefit from an adjuvant treatment comprising a chemotherapy. In other aspects, an AVANT stromal score that is below a reference AVANT stromal score, when associated with an expression level of GZMB that is above a reference expression level of GZMB, identifies an individual as one who is at low risk of CRC recurrence following surgical resection.

As used herein, the term“reference AVANT stromal score” refers to an AVANT stromal score against which another AVANT stromal score is compared, e.g., to make a diagnostic, predictive, prognostic, and/or therapeutic determination. For example, the reference AVANT stromal score may be derived from expression levels (e.g., for a set of genes comprising ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12, e.g., a set of genes comprising ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12, as well as one or more of ANGPT1, IGFBP3, CD36, HBEGF, FOS, SERPINB13, APCDD1, SCD5, POU5F1, EPHA4, FLT1, CDK6, and/or MAPK3, e.g., a set of genes comprising ANGPT1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, and MAPK3) in a reference sample, a reference population, and/or a pre-assigned value (e.g., a cut-off value which was previously determined to significantly (e.g., statistically significantly)) separate a first subset and a second subset of individuals in the reference population based on responsiveness to treatment, e.g., overall survival (OS), disease-free survival (DFS), and/or recurrence-free survival (RFS) when associated with an expression level of GZMB that is above or below a reference expression level of GZMB (e.g., a reference expression level of GZMB as provided in Section IIA (iib) herein, e.g., a pre-assigned cutoff expression level of GZMB)). It will be appreciated by one skilled in the art that the numerical value for the reference AVANT stromal score may vary depending on the indication (e.g., a cancer (e.g., a CRC, e.g., a stage I, stage II, stage III, or stage IV CRC), the methodology used to detect expression levels (e.g., digital counting of nucleic acids is by NANOSTRING^® NCOUNTER^® analysis), the statistical methods used to generate an AVANT stromal score, and/or the specific combinations of genes examined (e.g., a set of genes comprising ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12, e.g., a set of genes comprising ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12, as well as one or more of ANGPT1, IGFBP3, CD36, HBEGF, FOS, SERPINB13, APCDD1, SCD5, POU5F1, EPHA4, FLT1, CDK6, and/or MAPK3, e.g., a set of genes comprising ANGPT1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, and MAPK3).

The term“KRAS” or“GTPase KRas,” as used herein, broadly refers to any native KRAS from any mammalian source, including primates (e.g. humans) and rodents (e.g., mice and rats), unless otherwise indicated. The term also encompasses naturally occurring variants of KRAS, e.g., splice variants or allelic variants. The amino acid sequence of an exemplary human KRAS is shown under UniProt Accession No. P01 1 16 or in SEQ ID NO: 32. As used herein the term“KRAS status” refers to the presence or absence of one or more changes at an assayed position in the nucleotide or amino acid sequence of KRAS, e.g., one or more nucleotide substitution mutations resulting in a mutation at position 12 of the KRAS amino acid sequence (e.g. a G12A, G12R, G12D, G12C, G12S, G12V, or G12D mutation) or a mutation at position 13 of the KRAS amino acid sequence (e.g., a G13D mutation), as described in Marisa et al. , PLoS Med, 10: e1 001453, 2013, Lievre et al ., J Clin Oncol, 26: 374-379, 2008, and Lievre et al., Cancer Res, 66(8): 3992-3995, 2006). The change in the nucleotide sequence may also be any missense or nonsense mutation that is observed in the CRC, but not in adjacent normal tissue (Stransky et al., Science, 333: 1 157-1 160, 201 1 ). In some aspects, KRAS status is considered to be“wild-type” or“WT” if no mutations are detected at any of the assayed position, and“mutant” or“mut” if at least one mutation is detected at any of the assayed positions.

The term“BRAF” or“Human Serine/threonine-protein kinase B-raf,” as used herein, broadly refers to any native BRAF from any mammalian source, including primates (e.g. humans) and rodents (e.g., mice and rats), unless otherwise indicated. The term also encompasses naturally occurring variants of BRAF, e.g., splice variants or allelic variants. The amino acid sequence of an exemplary human BRAF is shown under UniProt Accession No. P15056 or in SEQ ID NO: 33. As used herein, the term“BRAF status” refers to the presence or absence of one or more changes at an assayed position in the nucleotide or amino acid sequence of BRAF. The change in the nucleotide sequence may be, e.g., a c. 1799T>A nucleotide substitution mutation, e.g., a mutation resulting in a V600E change in the amino acid sequence (Marisa et al. , PLoS Med, 1 0: e1001453, 2013). The change in the nucleotide sequence may also be any missense or nonsense mutation that is observed in the CRC, but not in adjacent normal tissue (Stransky et al., Science, 333: 1 157-1 160, 201 1 ). In some aspects, BRAF status is considered to be“wild-type” or“WT” if no mutations are detected at any of the assayed position, and“mutant” or“mut” if at least one mutation is detected at any of the assayed positions.

“Adjuvant treatment” or“adjuvant therapy” herein refers to treatment or therapy given after surgery (e.g., surgical resection of a CRC), where no evidence of residual disease can be detected, so as to reduce the risk of disease recurrence (e.g., recurrence of a CRC). The goal of adjuvant treatment is to prevent recurrence of the cancer, and therefore to reduce the chance of cancer-related death.

The terms“cancer” and“cancerous” refer to or describe the physiological condition in mammals that is typically characterized by unregulated cell growth/proliferation. Aspects of cancer include solid tumor cancers. In some aspects, the solid tumor cancer is a colorectal cancer (CRC) or a metastatic form thereof.

As used herein, the term“colorectal cancer,”“CRC,”“colon cancer,” or“bowel cancer” refers to a cancer that develops from the large intestine, e.g., the colon or rectum. In some aspects, a CRC is characterized as consensus molecular subtype 1 (CMS1 ), CMS2, CMS3, CMS4, or unclassified. In some aspects, a CRC is a left-sided tumor, i.e. , a tumor occurring in the distal colon (e.g., the distal third of the transverse colon, the splenic flexure the descending colon, the sigmoid colon, or the rectum). In other aspects, a CRC is a right-sided tumor, i.e., a tumor occurring in the proximal colon (e.g., the proximal two- thirds of the transverse colon, the ascending colon, and the cecum). Right-sided tumors may be associated with decreased OS. In some aspects, the CRC is metastatic. In some aspects, the CRC is a colon carcinoma. In some aspects, the colon carcinoma is CMS1 , CMS2, CMS3, CMS4, or unclassified. In some aspects, the colon carcinoma is a left-sided colon carcinoma. In other aspects, the colon carcinoma is a right-sided colon carcinoma.

In some aspects, the stage of a CRC is assessed according to the American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) TNM Classification of Malignant Tumors (TNM) classification system. In the TNM system, cancers are designated the letter T (tumor size), N (palpable nodes), and/or M (metastases). T1 , T2, T3, and T4 describe the increasing size of the primary lesion. T1 , T2, T3, and T4 may additionally be classified as a or b (e.g., T4a or T4b) to provide further information about the status, e.g., local advancement, of the cancer. NO, N1 , N2, N3 indicates progressively advancing node involvement; and M0 and M1 reflect the absence or presence of distant metastases. In some aspects, the CRC of an individual is a stage I, stage II, or stage III CRC, e.g., a stage I, stage II, or stage III colon carcinoma. In some aspects, an individual does not have a stage IV CRC. In some aspects, an individual does not have a metastatic CRC. In some aspects, the CRC of an individual in a reference population is a stage I, stage II, stage III, or stage IV CRC, e.g., a stage I, stage II, stage III, or stage IV colon carcinoma. In some aspects, the CRC of an individual or an individual in a reference population is a stage III - N1 , stage III - N2, or high-risk stage II colon carcinoma according to the TNM classification system. A“high-risk stage II colon carcinoma” (e.g., high risk for recurrence of the CRC following surgical resection) may be identified by the individual having a stage II colon carcinoma and having one or more of the following: T4 tumors; bowel obstruction or perforation; histological signs of vascular invasion (i.e., blood and lymphatic vessels) or perineural invasion; individual aged less than 50 years; sub-optimal surgery (less than 12 nodes analyzed). In some aspects, TNM status is confirmed by histology.

As used herein, the term“consensus molecular subtype” or“CMS” refers to a subtype of CRC as defined in Guinney et al. , Nat Med, 21 (1 1 ): 1350-1362, 2015. In some aspects, a CRC is identified as consensus molecular subtype 1 (CMS1 ) (MSI immune). CMS1 may be characterized by microsatellite instability (MSI), high CpG island methylation phenotype (CIMP), hypermutation, BRAF mutations, high immune activation and infiltration, and worse survival after recurrence. In other aspects, a CRC is identified as consensus molecular subtype 2 (CMS2) (canonical). CMS2 may be characterized by high somatic copy number alterations (SCNA) and WNT and MYC signaling activation. In other aspects, a CRC is identified as consensus molecular subtype 3 (CMS3) (metabolic). CMS3 may be characterized by mixed MSI status, low SCNA, low CIMP, KRAS mutations, and evident metabolic dysregulation. In other aspects, a colorectal cancer is identified as consensus molecular subtype 4 (CMS4)

(mesenchymal). CMS4 may be characterized by high SCNA, stromal infiltration, prominent TGFp activation, angiogenesis, and worse relapse-free (recurrence-free) and overall survival. In some aspects, a CRC has a heterogeneous expression pattern that is mixed or indeterminate relative to the CMS1 , CMS2, CMS3, and CMS4 categories.

As used herein,“microsatellite instability status” or“MSI status” refers to a characterization of microsatellite stability in a tumor tissue of a patient. The tumor tissue of a patient may be characterized as“microsatellite instability high” (“MSI-H”) or“microsatellite stable” or“microsatellite instability low” (“MSS”). MSI status may be assessed, for example, by using a PCR-based approach such as the MSI Analysis System (Promega, Madison, Wl), which is comprised of 5 pseudomonomorphic mononucleotide repeats (BAT-25, BAT-26, NR-21 , NR-24, and MONO-27) to detect MSI and 2 pentanucleotide loci (PentaC and PendaD) to confirm identity between normal and tumor samples. The size in bases for each microsatellite locus can be determined, e.g., by gel electrophoresis, and a tumor may be designated MSI- H if two or more mononucleotide loci vary in length compared to the germline DNA. See, e.g., Le et al. NEJM 372:2509-2520, 201 5. In other embodiments, a patient may have a low level of microsatellite instability (e.g., MSS).

“Tumor,” as used herein, refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues. The terms“cancer,”“cancerous,”“cell proliferative disorder,”“proliferative disorder,” and“tumor” are not mutually exclusive as referred to herein.

A“tumor cell” as used herein, refers to any tumor cell present in a tumor or a sample thereof. Tumor cells may be distinguished from other cells that may be present in a tumor sample, for example, stromal cells and tumor-infiltrating immune cells, using methods known in the art and/or described herein.

As used herein,“reducing or inhibiting cancer recurrence” means to reduce or inhibit tumor or cancer relapse (recurrence) or tumor or cancer progression. As disclosed herein, cancer recurrence and/or cancer progression include, without limitation, cancer metastasis. As used herein,“partial response” or“PR” refers to a decrease in the size of one or more tumors or lesions, or in the extent of cancer in the body, in response to treatment. For example, in some aspects, PR refers to at least a 30% decrease in the sum of the longest diameters (SLD) of target lesions, taking as reference the baseline SLD.

As used herein,“stable disease” or“SD” refers to neither sufficient shrinkage of target lesions to qualify for PR, nor sufficient increase to qualify for PD, taking as reference the smallest SLD since the treatment started.

As used herein,“progressive disease” or“PD” refers to at least a 20% increase in the SLD of target lesions, taking as reference the smallest SLD recorded since the treatment started or the presence of one or more new lesions.

The term“survival” refers to the patient remaining alive, and includes overall survival as well as progression-free survival, disease-free survival, and recurrence-free survival.

As used herein,“disease-free survival” or“DFS” refers to the length of time after primary treatment for a cancer ends that the patient survives without any signs or symptoms of that cancer. DFS may also be referred to as“recurrence-free survival” or“RFS”. In some aspects, disease-free survival (DFS) is defined as the time between randomization (e.g., assignment to an adjuvant treatment group) and recurrence of a colorectal cancer, new occurrence of a colorectal cancer, or death from any cause.

As used herein,“overall survival” or“OS” refers to the percentage of individuals in a group who are likely to be alive after a particular duration of time.

As used herein,“progression-free survival” or“PFS” refers to the length of time during and after treatment during which the disease being treated (e.g., cancer) does not get worse. Progression-free survival may include the amount of time patients have experienced a complete response or a partial response, as well as the amount of time patients have experienced stable disease.

By“extending survival” is meant increasing overall survival, progression-free survival, disease- free survival, or recurrence-free survival in a treated patient relative to an untreated patient (i.e. relative to a patient not treated with the medicament).

As used herein,“hazard ratio” or“HR” is a statistical definition for rates of events. For the purpose of the invention, hazard ratio is defined as representing the probability of an event (e.g., PFS or OS) in the experimental (e.g., treatment) group/arm divided by the probability of an event in the control group/arm at any specific point in time. An HR with a value of 1 indicates that the relative risk of an endpoint (e.g., death) is equal in both the“treatment” and“control” groups; a value greater than 1 indicates that the risk is greater in the treatment group relative to the control group; and a value less than 1 indicates that the risk is greater in the control group relative to the treatment group. “Hazard ratio” in progression-free survival analysis (i.e., PFS HR) is a summary of the difference between two progression- free survival curves, representing the reduction in the risk of death on treatment compared to control, over a period of follow-up. “Hazard ratio” in overall survival analysis (i.e., OS HR) is a summary of the difference between two overall survival curves, representing the reduction in the risk of death on treatment compared to control, over a period of follow-up.

An“effective amount” of a compound, for example, a chemotherapy or a composition thereof, is at least the minimum amount required to achieve the desired therapeutic or prophylactic result, such as a measurable improvement or prevention of a particular disorder (e.g., a cell proliferative disorder, e.g., cancer, e.g., a urinary tract cancer). An effective amount herein may vary according to factors such as the disease state, age, sex, and weight of the patient, and the ability of the antibody to elicit a desired response in the individual. An effective amount is also one in which any toxic or detrimental effects of the treatment are outweighed by the therapeutically beneficial effects. For prophylactic use, beneficial or desired results include results such as eliminating or reducing the risk, lessening the severity, or delaying the onset of the disease, including biochemical, histological and/or behavioral symptoms of the disease, its complications, and intermediate pathological phenotypes presenting during development of the disease. For therapeutic use, beneficial or desired results include clinical results such as decreasing one or more symptoms resulting from the disease, increasing the quality of life of those suffering from the disease, decreasing the dose of other medications required to treat the disease, enhancing effect of another medication such as via targeting, delaying the progression of the disease, and/or prolonging survival. In the case of cancer or tumor, an effective amount of the drug may have the effect in reducing the number of cancer cells; reducing the tumor size; inhibiting (i.e., slow to some extent or desirably stop) cancer cell infiltration into peripheral organs; inhibit (i.e., slow to some extent and desirably stop) tumor metastasis; inhibiting to some extent tumor growth ; and/or relieving to some extent one or more of the symptoms associated with the disorder. An effective amount can be administered in one or more administrations. For purposes of this invention, an effective amount of drug, compound, or

pharmaceutical composition is an amount sufficient to accomplish prophylactic or therapeutic treatment either directly or indirectly. As is understood in the clinical context, an effective amount of a drug, compound, or pharmaceutical composition may or may not be achieved in conjunction with another drug, compound, or pharmaceutical composition. Thus, an“effective amount” may be considered in the context of administering one or more therapeutic agents, and a single agent may be considered to be given in an effective amount if, in conjunction with one or more other agents, a desirable result may be or is achieved.

The term“pharmaceutical formulation” refers to a preparation which is in such form as to permit the biological activity of an active ingredient contained therein to be effective, and which contains no additional components which are unacceptably toxic to a subject to which the formulation would be administered.

A“pharmaceutically acceptable carrier” refers to an ingredient in a pharmaceutical formulation, other than an active ingredient, which is nontoxic to a subject. A pharmaceutically acceptable carrier includes, but is not limited to, a buffer, excipient, stabilizer, or preservative.

As used herein,“treatment” (and grammatical variations thereof such as“treat” or“treating”) refers to clinical intervention in an attempt to alter the natural course of the individual being treated, and can be performed either for prophylaxis or during the course of clinical pathology. Desirable effects of treatment include, but are not limited to, preventing occurrence or recurrence of disease, alleviation of symptoms, diminishment of any direct or indirect pathological consequences of the disease, preventing metastasis, decreasing the rate of disease progression, amelioration or palliation of the disease state, and remission or improved prognosis. In some aspects, a chemotherapeutic agent is used to delay development of a disease or to slow the progression of a disease. The term“anti-cancer therapy” refers to a therapy useful in treating cancer. Examples of anti cancer therapeutic agents include, but are not limited to, cytotoxic agents, chemotherapeutic agents, growth inhibitory agents, agents used in radiation therapy, anti-angiogenesis agents, apoptotic agents, anti-tubulin agents, and other agents to treat cancer, for example, anti-CD20 antibodies, platelet derived growth factor inhibitors (e.g., GLEEVEC™ (imatinib mesylate)), a COX-2 inhibitor (e.g., celecoxib), interferons, cytokines, antagonists (e.g., neutralizing antibodies) that bind to one or more of the following targets PDGFR-b, BlyS, APRIL, BCMA receptor(s), TRAIL/ Apo2, other bioactive and organic chemical agents, and the like. Combinations thereof are also included in the invention.

“Chemotherapeutic agent” includes chemical compounds useful in the treatment of cancer.

Examples of chemotherapeutic agents include oxaliplatin (ELOXATIN®, Sanofi), 5-FU (5-fluorouracil), leucovorin, capecitabine (XELODA®); FOLFOX, an abbreviation for a treatment regimen with oxaliplatin (ELOXATIN™) combined with 5-FU and leucovorin; and XELOX, an abbreviation for a treatment regimen with oxaliplatin and capecitabine. The FOLFOX treatment regimen may be, e.g., a FOLFOX4 treatment regimen. Treatment with FOLFOX (e.g., FOLFOX4) or XELOX may further comprise treatment with bevacizumab (AVASTIN®, Genentech), e.g., concurrent treatment with bevacizumab.

Further examples of chemotherapeutic agents include erlotinib (TARCEVA®, Genentech/OSI Pharm.), bortezomib (VELCADE®, Millennium Pharm.), disulfiram, epigallocatechin gallate ,

salinosporamide A, carfilzomib, 17-AAG (geldanamycin), radicicol, lactate dehydrogenase A (LDH-A), fulvestrant (FASLODEX®, AstraZeneca), sunitib (SUTENT®, Pfizer/Sugen), letrozole (FEMARA®, Novartis), imatinib mesylate (GLEEVEC®, Novartis), finasunate (VATALANIB®, Novartis), Rapamycin (Sirolimus, RAPAMUNE®, Wyeth), Lapatinib (TYKERB®, GSK572016, Glaxo Smith Kline), Lonafamib (SCH 66336), sorafenib (NEXAVAR®, Bayer Labs), gefitinib (IRESSA®, AstraZeneca), AG1478, alkylating agents such as thiotepa and CYTOXAN® cyclosphosphamide; alkyl sulfonates such as busulfan, improsulfan and piposulfan; aziridines such as benzodopa, carboquone, meturedopa, and uredopa; ethylenimines and methylamelamines including altretamine, triethylenemelamine,

triethylenephosphoramide, triethylenethiophosphoramide and trimethylomelamine; acetogenins

(especially bullatacin and bullatacinone); a camptothecin (including topotecan and irinotecan); bryostatin; callystatin; CC-1065 (including its adozelesin, carzelesin and bizelesin synthetic analogs); cryptophycins (particularly cryptophycin 1 and cryptophycin 8); adrenocorticosteroids (including prednisone and prednisolone); cyproterone acetate; 5a-reductases including finasteride and dutasteride); vorinostat, romidepsin, panobinostat, valproic acid, mocetinostat dolastatin; aldesleukin, talc duocarmycin (including the synthetic analogs, KW-2189 and CB1 -TM1 ); eleutherobin; pancratistatin; a sarcodictyin ; spongistatin; nitrogen mustards such as chlorambucil, chlomaphazine, chlorophosphamide, estramustine, ifosfamide, mechlorethamine, mechlorethamine oxide hydrochloride, melphalan, novembichin, phenesterine, prednimustine, trofosfamide, uracil mustard; nitrosoureas such as carmustine, chlorozotocin, fotemustine, lomustine, nimustine, and ranimnustine; antibiotics such as the enediyne antibiotics (e.g., calicheamicin, especially calicheamicin g1 1 and calicheamicin w1 1 (Angew Chem. Inti. Ed. Engl. 1 994 33:1 83-186); dynemicin, including dynemicin A; bisphosphonates, such as clodronate; an esperamicin; as well as neocarzinostatin chromophore and related chromoprotein enediyne antibiotic chromophores), aclacinomysins, actinomycin, authramycin, azaserine, bleomycins, cactinomycin, carabicin, caminomycin, carzinophilin, chromomycinis, dactinomycin, daunorubicin, detorubicin, 6-diazo-5-oxo-L-norleucine, ADRIAMYCIN® (doxorubicin), morpholino-doxorubicin, cyanomorpholino-doxorubicin, 2-pyrrolino- doxorubicin and deoxydoxorubicin), epirubicin, esorubicin, idarubicin, marcellomycin, mitomycins such as mitomycin C, mycophenolic acid, nogalamycin, olivomycins, peplomycin, porfiromycin, puromycin, quelamycin, rodorubicin, streptonigrin, streptozocin, tubercidin, ubenimex, zinostatin, zorubicin; anti metabolites such as methotrexate and 5-fluorouracil (5-FU); folic acid analogs such as denopterin, methotrexate, pteropterin, trimetrexate; purine analogs such as fludarabine, 6-mercaptopurine, thiamiprine, thioguanine; pyrimidine analogs such as ancitabine, azacitidine, 6-azauridine, carmofur, cytarabine, dideoxyuridine, doxifluridine, enocitabine, floxuridine; androgens such as calusterone, dromostanolone propionate, epitiostanol, mepitiostane, testolactone; anti-adrenals such as

aminoglutethimide, mitotane, trilostane; folic acid replenisher such as frolinic acid; aceglatone;

aldophosphamide glycoside; aminolevulinic acid; eniluracil; amsacrine; bestrabucil; bisantrene;

edatraxate; defofamine; demecolcine; diaziquone; elfomithine; elliptinium acetate; an epothilone;

etoglucid; gallium nitrate; hydroxyurea; lentinan; lonidainine; maytansinoids such as maytansine and ansamitocins; mitoguazone; mitoxantrone; mopidamnol; nitraerine; pentostatin; phenamet; pirarubicin; losoxantrone; podophyllinic acid; 2-ethylhydrazide; procarbazine; PSK® polysaccharide complex (JHS Natural Products, Eugene, Oreg.); razoxane; rhizoxin; sizofuran; spirogermanium; tenuazonic acid; triaziquone; 2,2’,2”-trichlorotriethylamine; trichothecenes (especially T-2 toxin, verracurin A, roridin A and anguidine); urethan; vindesine; dacarbazine; mannomustine; mitobronitol ; mitolactol; pipobroman;

gacytosine; arabinoside (“Ara-C”); cyclophosphamide; thiotepa; taxoids, e.g., TAXOL (paclitaxel; Bristol- Myers Squibb Oncology, Princeton, N.J.), ABRAXANE® (Cremophor-free), albumin-engineered nanoparticle formulations of paclitaxel (American Pharmaceutical Partners, Schaumberg, III.), and TAXOTERE® (docetaxel, doxetaxel; Sanofi-Aventis); chloranmbucil; GEMZAR® (gemcitabine); 6- thioguanine; mercaptopurine; methotrexate; platinum analogs such as cisplatin and carboplatin;

vinblastine; etoposide (VP-16); ifosfamide; mitoxantrone; vincristine; NAVELBINE® (vinorelbine);

novantrone; teniposide; edatrexate; daunomycin; aminopterin; ibandronate; CPT-1 1 ; topoisomerase inhibitor RFS 2000; difluoromethylornithine (DMFO); retinoids such as retinoic acid; and pharmaceutically acceptable salts, acids and derivatives of any of the above.

Chemotherapeutic agent also includes (i) anti-hormonal agents that act to regulate or inhibit hormone action on tumors such as anti-estrogens and selective estrogen receptor modulators (SERMs), including, for example, tamoxifen (including NOLVADEX®; tamoxifen citrate), raloxifene, droloxifene, iodoxyfene , 4-hydroxytamoxifen, trioxifene, keoxifene, LY1 17018, onapristone, and FARESTON® (toremifine citrate); (ii) aromatase inhibitors that inhibit the enzyme aromatase, which regulates estrogen production in the adrenal glands, such as, for example, 4(5)-imidazoles, aminoglutethimide, MEGASE® (megestrol acetate), AROMASIN® (exemestane; Pfizer), formestanie, fadrozole, RIVISOR® (vorozole), FEMARA® (letrozole; Novartis), and ARIMIDEX® (anastrozole; AstraZeneca); (iii) anti-androgens such as flutamide, nilutamide, bicalutamide, leuprolide and goserelin; buserelin, tripterelin,

medroxyprogesterone acetate, diethylstilbestrol, premarin, fluoxymesterone, all transretionic acid, fenretinide, as well as troxacitabine (a 1 ,3-dioxolane nucleoside cytosine analog); (iv) protein kinase inhibitors; (v) lipid kinase inhibitors; (vi) antisense oligonucleotides, particularly those which inhibit expression of genes in signaling pathways implicated in aberrant cell proliferation, such as, for example, PKC-alpha, Ralf and H-Ras; (vii) ribozymes such as VEGF expression inhibitors (e.g., ANGIOZYME®) and HER2 expression inhibitors; (viii) vaccines such as gene therapy vaccines, for example,

ALLOVECTIN®, LEUVECTIN®, and VAXID®; PROLEUKIN®, rlL-2; a topoisomerase 1 inhibitor such as LURTOTECAN®; ABARELIX® rmRH; and (ix) pharmaceutically acceptable salts, acids and derivatives of any of the above.

Chemotherapeutic agent also includes antibodies such as bevacizumab (AVASTIN®,

Genentech), alemtuzumab (Campath), cetuximab (ERBITUX®, Imclone), panitumumab (VECTIBIX®, Amgen), rituximab (RITUXAN®, Genentech/Biogen Idee), pertuzumab (OMNITARG®, 2C4, Genentech), trastuzumab (HERCEPTIN®, Genentech), tositumomab (Bexxar, Corixia), and the antibody drug conjugate, gemtuzumab ozogamicin (MYLOTARG®, Wyeth). Additional humanized monoclonal antibodies with therapeutic potential as agents in combination with the compounds of the invention include: apolizumab, aselizumab, atlizumab, bapineuzumab, bivatuzumab mertansine, cantuzumab mertansine, cedelizumab, certolizumab pegol, cidfusituzumab, cidtuzumab, daclizumab, eculizumab, efalizumab, epratuzumab, erlizumab, felvizumab, fontolizumab, gemtuzumab ozogamicin, inotuzumab ozogamicin, ipilimumab, labetuzumab, lintuzumab, matuzumab, mepolizumab, motavizumab, motovizumab, natalizumab, nimotuzumab, nolovizumab, numavizumab, ocrelizumab, omalizumab, palivizumab, pascolizumab, peefusituzumab, pectuzumab, pexelizumab, ralivizumab, ranibizumab, reslivizumab, reslizumab, resyvizumab, rovelizumab, ruplizumab, sibrotuzumab, siplizumab, sontuzumab, tacatuzumab tetraxetan, tadocizumab, talizumab, tefibazumab, tocilizumab, toralizumab, tucotuzumab celmoleukin, tucusituzumab, umavizumab, urtoxazumab, ustekinumab, visilizumab, and the anti interleukin-12 (ABT-874/J695, Wyeth Research and Abbott Laboratories) which is a recombinant exclusively human-sequence, full-length IgG 1 l antibody genetically modified to recognize interleukin-12 p40 protein.

Chemotherapeutic agent also includes“EGFR inhibitors,” which refers to compounds that bind to or otherwise interact directly with EGFR and prevent or reduce its signaling activity, and is alternatively referred to as an“EGFR antagonist.” Examples of such agents include antibodies and small molecules that bind to EGFR. Examples of antibodies which bind to EGFR include MAb 579 (ATCC CRL HB 8506), MAb 455 (ATCC CRL HB8507), MAb 225 (ATCC CRL 8508), MAb 528 (ATCC CRL 8509) (see, US Patent No. 4,943, 533, Mendelsohn et al.) and variants thereof, such as chimerized 225 (C225 or cetuximab; ERBUTIX®) and reshaped human 225 (H225) (see, WO 96/40210, Imclone Systems Inc.); IMC-1 1 F8, a fully human, EGFR-targeted antibody (Imclone); antibodies that bind type II mutant EGFR (US Patent No. 5,212,290); humanized and chimeric antibodies that bind EGFR as described in US Patent No. 5,891 ,996; and human antibodies that bind EGFR, such as ABX-EGF or Panitumumab (see WO98/50433, Abgenix/Amgen); EMD 55900 (Stragliotto et al. Eur. J. Cancer 32A:636-640 (1 996));

EMD7200 (matuzumab) a humanized EGFR antibody directed against EGFR that competes with both EGF and TGF-alpha for EGFR binding (EMD/Merck); human EGFR antibody, HuMax-EGFR (GenMab); fully human antibodies known as E1 .1 , E2.4, E2.5, E6.2, E6.4, E2.1 1 , E6. 3 and E7.6. 3 and described in US 6,235,883; MDX-447 (Medarex Inc); and mAb 806 or humanized mAb 806 (Johns et al., J. Biol.

Chem. 279(29) :30375-30384 (2004)). The anti-EGFR antibody may be conjugated with a cytotoxic agent, thus generating an immunoconjugate (see, e.g., EP659,439A2, Merck Patent GmbH). EGFR antagonists include small molecules such as compounds described in US Patent Nos: 5,616,582, 5,457,105, 5,475,001 , 5,654,307, 5,679,683, 6,084,095, 6,265,410, 6,455,534, 6,521 ,620, 6,596,726, 6,713,484, 5,770,599, 6,140,332, 5,866,572, 6,399,602, 6,344,459, 6,602,863, 6,391 ,874, 6,344,455, 5,760,041 , 6,002,008, and 5,747,498, as well as the following PCT publications: W098/14451 ,

W098/50038, W099/0901 6, and WO99/24037. Particular small molecule EGFR antagonists include OSI-774 (CP-358774, erlotinib, TARCEVA® Genentech/OSI Pharmaceuticals); PD 183805 (Cl 1033, 2- propenamide, N-[4-[(3-chloro-4-fluorophenyl)amino]-7-[3-(4-morpholinyl)propoxy]-6-quinazolinyl]-, dihydrochloride, Pfizer Inc.) ; ZD1839, gefitinib (IRESSA®) 4-(3’-Chloro-4’-fluoroanilino)-7-methoxy-6-(3- morpholinopropoxy)quinazoline, AstraZeneca); ZM 105180 ((6-amino-4-(3-methylphenyl-amino)- quinazoline, Zeneca); BIBX-1382 (N8-(3-chloro-4-fluoro-phenyl)-N2-(1 -methyl-piperidin-4-yl)- pyrimido[5,4-d]pyrimidine-2, 8-diamine, Boehringer Ingelheim); PKI-166 ((R)-4-[4-[(1 -phenylethyl)amino]- 1 H-pyrrolo[2,3-d]pyrimidin-6-yl]-phenol); (R)-6-(4-hydroxyphenyl)-4-[(1 -phenylethyl)amino]-7H-pyrrolo[2,3- d]pyrimidine); CL-387785 (N-[4-[(3-bromophenyl)amino]-6-quinazolinyl]-2-butynamide); EKB-569 (N-[4- [(3-chloro-4-fluorophenyl)amino]-3-cyano-7-ethoxy-6-quinolinyl]-4-(dimethylamino)-2-butenamide) (Wyeth); AG1478 (Pfizer); AG1571 (SU 5271 ; Pfizer); dual EGFR/HER2 tyrosine kinase inhibitors such as lapatinib (TYKERB®, GSK572016 or N-[3-chloro-4-[(3 fluorophenyl)methoxy]phenyl]- 6[5[[[2methylsulfonyl)ethyl]amino]methyl]-2-furanyl]-4-quinazolinamine).

Chemotherapeutic agents also include“tyrosine kinase inhibitors” including the EGFR-targeted drugs noted in the preceding paragraph; small molecule HER2 tyrosine kinase inhibitor such as TAK165 available from Takeda; CP-724,714, an oral selective inhibitor of the ErbB2 receptor tyrosine kinase (Pfizer and OSI); dual-HER inhibitors such as EKB-569 (available from Wyeth) which preferentially binds EGFR but inhibits both HER2 and EGFR-overexpressing cells; lapatinib (GSK572016; available from Glaxo-SmithKIine), an oral HER2 and EGFR tyrosine kinase inhibitor; PKI-166 (available from Novartis); pan-HER inhibitors such as canertinib (CI-1033; Pharmacia); Raf-1 inhibitors such as antisense agent ISIS-5132 available from ISIS Pharmaceuticals which inhibit Raf-1 signaling; non-HER targeted TK inhibitors such as imatinib mesylate (GLEEVEC®, available from Glaxo SmithKIine); multi-targeted tyrosine kinase inhibitors such as sunitinib (SUTENT®, available from Pfizer); VEGF receptor tyrosine kinase inhibitors such as vatalanib (PTK787/ZK222584, available from Novartis/Schering AG); MAPK extracellular regulated kinase I inhibitor CI-1040 (available from Pharmacia); quinazolines, such as PD 153035, 4-(3-chloroanilino) quinazoline; pyridopyrimidines; pyrimidopyrimidines; pyrrolopyrimidines, such as CGP 59326, CGP 60261 and CGP 62706; pyrazolopyrimidines, 4-(phenylamino)-7H-pyrrolo[2,3-d] pyrimidines; curcumin (diferuloyl methane, 4,5-bis (4-fluoroanilino)phthalimide); tyrphostines containing nitrothiophene moieties; PD-0183805 (Warner-Lamber) ; antisense molecules (e.g. those that bind to HER-encoding nucleic acid); quinoxalines (US Patent No. 5,804,396); tryphostins (US Patent No.

5,804,396); ZD6474 (Astra Zeneca); PTK-787 (Novartis/Schering AG); pan-HER inhibitors such as CI- 1033 (Pfizer); Affinitac (ISIS 3521 ; Isis/Lilly); imatinib mesylate (GLEEVEC®); PKI 166 (Novartis);

GW2016 (Glaxo SmithKIine); CI-1033 (Pfizer); EKB-569 (Wyeth); Semaxinib (Pfizer); ZD6474

(AstraZeneca); PTK-787 (Novartis/Schering AG); INC-1 C1 1 (Imclone), rapamycin (sirolimus,

RAPAMUNE®); or as described in any of the following patent publications: US Patent No. 5,804,396; WO 1999/09016 (American Cyanamid); WO 1998/43960 (American Cyanamid); WO 1997/38983 (Warner Lambert); WO 1999/06378 (Warner Lambert); WO 1999/06396 (Warner Lambert); WO 1996/30347 (Pfizer, Inc); WO 1996/33978 (Zeneca); WO 1996/3397 (Zeneca) and WO 1996/33980 (Zeneca).

Chemotherapeutic agents also include dexamethasone, interferons, colchicine, metoprine, cyclosporine, amphotericin, metronidazole, alemtuzumab, alitretinoin, allopurinol, amifostine, arsenic trioxide, asparaginase, BCG live, bevacuzimab, bexarotene, cladribine, clofarabine, darbepoetin alfa, denileukin, dexrazoxane, epoetin alfa, elotinib, filgrastim, histrelin acetate, ibritumomab, interferon alfa- 2a, interferon alfa-2b, lenalidomide, levamisole, mesna, methoxsalen, nandrolone, nelarabine, nofetumomab, oprelvekin, palifermin, pamidronate, pegademase, pegaspargase, pegfilgrastim, pemetrexed disodium, plicamycin, porfimer sodium, quinacrine, rasburicase, sargramostim,

temozolomide, VM-26, 6-TG, toremifene, tretinoin, ATRA, valrubicin, zoledronate, and zoledronic acid, and pharmaceutically acceptable salts thereof.

Chemotherapeutic agents also include hydrocortisone, hydrocortisone acetate, cortisone acetate, tixocortol pivalate, triamcinolone acetonide, triamcinolone alcohol, mometasone, amcinonide, budesonide, desonide, fluocinonide, fluocinolone acetonide, betamethasone, betamethasone sodium phosphate, dexamethasone, dexamethasone sodium phosphate, fluocortolone, hydrocortisone-1 7- butyrate, hydrocortisone-1 7-valerate, aclometasone dipropionate, betamethasone valerate,

betamethasone dipropionate, prednicarbate, clobetasone-17-butyrate, clobetasol-17-propionate, fluocortolone caproate, fluocortolone pivalate and fluprednidene acetate; immune selective anti inflammatory peptides (ImSAIDs) such as phenylalanine-glutamine-glycine (FEG) and its D-isomeric form (feG) (IMULAN BioTherapeutics, LLC); anti-rheumatic drugs such as azathioprine, ciclosporin

(cyclosporine A), D-penicillamine, gold salts, hydroxychloroquine, leflunomideminocycline, sulfasalazine, tumor necrosis factor alpha (TNFa) blockers such as etanercept (Enbrel), infliximab (Remicade), adalimumab (Humira), certolizumab pegol (Cimzia), golimumab (Simponi), interleukin 1 (IL-1 ) blockers such as anakinra (Kineret), T cell costimulation blockers such as abatacept (Orencia), interleukin 6 (IL-6) blockers such as tocilizumab (ACTEMERA®); interleukin 13 (IL-13) blockers such as lebrikizumab;

interferon alpha (IFN) blockers such as Rontalizumab; beta 7 integrin blockers such as rhuMAb Beta7;

IgE pathway blockers such as Anti-M1 prime; Secreted homotrimeric LTa3 and membrane bound heterotrimer LTa1 /p2 blockers such as anti-lymphotoxin alpha (LTa); radioactive isotopes (e.g., At^{21 1} , I¹³¹ , I¹²⁵, Y⁹⁰, Re¹⁸⁶, Re¹⁸⁸, Sm¹⁵³, Bi²¹², P³², Pb²¹², and radioactive isotopes of Lu); miscellaneous

investigational agents such as thioplatin, PS-341 , phenylbutyrate, ET-18- OCH3, or farnesyl transferase inhibitors (L-739749, L-744832); polyphenols such as quercetin, resveratrol, piceatannol,

epigallocatechine gallate, theaflavins, flavanols, procyanidins, betulinic acid and derivatives thereof; autophagy inhibitors such as chloroquine; delta-9-tetrahydrocannabinol (dronabinol, MARINOL®); beta- lapachone; lapachol; colchicines; betulinic acid; acetylcamptothecin, scopolectin, and 9- aminocamptothecin); podophyllotoxin; tegafur (UFTORAL®); bexarotene (TARGRETIN®);

bisphosphonates such as clodronate (for example, BONEFOS® or OSTAC®), etidronate (DIDROCAL®), NE-58095, zoledronic acid/zoledronate (ZOMETA®), alendronate (FOSAMAX®), pamidronate

(AREDIA®), tiludronate (SKELID®), or risedronate (ACTONEL®); and epidermal growth factor receptor (EGF-R); vaccines such as THERATOPE® vaccine; perifosine, COX-2 inhibitor (e.g. celecoxib or etoricoxib), proteosome inhibitor (e.g. PS341 ); CCI-779; tipifarnib (R1 1577); orafenib, ABT510; Bcl-2 inhibitor such as oblimersen sodium (GENASENSE®); pixantrone; farnesyltransferase inhibitors such as lonafarnib (SCH 6636, SARASARTM); and pharmaceutically acceptable salts, acids or derivatives of any of the above; as well as combinations of two or more of the above such as CHOP, an abbreviation for a combined therapy of cyclophosphamide, doxorubicin, vincristine, and prednisolone.

Chemotherapeutic agents also include non-steroidal anti-inflammatory drugs with analgesic, antipyretic and anti-inflammatory effects. NSAIDs include non-selective inhibitors of the enzyme cyclooxygenase. Specific examples of NSAIDs include aspirin, propionic acid derivatives such as ibuprofen, fenoprofen, ketoprofen, flurbiprofen, oxaprozin and naproxen, acetic acid derivatives such as indomethacin, sulindac, etodolac, diclofenac, enolic acid derivatives such as piroxicam, meloxicam, tenoxicam, droxicam, lornoxicam and isoxicam, fenamic acid derivatives such as mefenamic acid, meclofenamic acid, flufenamic acid, tolfenamic acid, and COX-2 inhibitors such as celecoxib, etoricoxib, lumiracoxib, parecoxib, rofecoxib, rofecoxib, and valdecoxib. NSAIDs can be indicated for the symptomatic relief of conditions such as rheumatoid arthritis, osteoarthritis, inflammatory arthropathies, ankylosing spondylitis, psoriatic arthritis, Reiter’s syndrome, acute gout, dysmenorrhoea, metastatic bone pain, headache and migraine, postoperative pain, mild-to-moderate pain due to inflammation and tissue injury, pyrexia, ileus, and renal colic.

As used herein, the term“immunomodulatory agent” refers to a therapeutic agent that modulates (e.g., up-regulates or down-regulates) an immune response. An immunomodulatory agent may be, e.g., an immune checkpoint inhibitor. As used herein, the term“immune checkpoint inhibitor” refers to a therapeutic agent that targets at least one immune checkpoint protein to alter the regulation of an immune response, e.g., down-modulating, inhibiting, up-modulating, or activating an immune response. The term “immune checkpoint blockade” may be used to refer to a therapy comprising an immune checkpoint inhibitor. Immune checkpoint proteins are known in the art and include, without limitation, cytotoxic T- lymphocyte antigen 4 (CTLA-4), programmed cell death 1 (PD-1 ), programmed cell death ligand 1 (PD- L1 ), programmed cell death ligand 2 (PD-L2), V-domain Ig suppressor of T cell activation (VISTA), B7-H2, B7-H3, B7-H4, B7-H6, 2B4, ICOS, HVEM, CD160, gp49B, PIR-B, KIR family receptors, TIM-1 , TIM-3, TIM-4, LAG-3, BTLA, SIRPalpha (CD47), CD48, 2B4 (CD244), B7.1 , B7.2, ILT-2, ILT-4, TIGIT, LAG-3, BTLA, IDO, 0X40, and A2aR. In some aspects, an immune checkpoint protein may be expressed on the surface of an activated T cell. Therapeutic agents that can act as immune checkpoint inhibitors useful in the methods of the present invention, include, but are not limited to, therapeutic agents that target one or more of CTLA-4, PD-1 , PD-L1 , PD-L2, VISTA, B7-H2, B7-H3, B7-H4, B7-H6, 2B4, ICOS, HVEM, CD160, gp49B, PIR-B, KIR family receptors, TIM-1 , TIM-3, TIM-4, LAG- 3, BTLA, SIRPalpha (CD47), CD48, 2B4 (CD244), B7.1 , B7.2, ILT-2, ILT-4, TIGIT, LAG-3, BTLA, IDO, 0X40, and A2aR. In some aspects, an immune checkpoint inhibitor enhances or suppresses the function of one or more targeted immune checkpoint proteins. In some aspects, the immune checkpoint inhibitor is a PD-L1 axis binding antagonist, such as atezolizumab, as described herein.

The term“PD-1 axis binding antagonist” refers to a molecule that inhibits the interaction of a PD-1 axis binding partner with either one or more of its binding partner, so as to remove T cell dysfunction resulting from signaling on the PD-1 signaling axis - with a result being to restore or enhance T cell function (e.g., proliferation, cytokine production, target cell killing). As used herein, a PD-1 axis binding antagonist includes a PD-1 binding antagonist, a PD-L1 binding antagonist, and a PD-L2 binding antagonist.

The term“PD-1 binding antagonist” refers to a molecule that decreases, blocks, inhibits, abrogates or interferes with signal transduction resulting from the interaction of PD-1 with one or more of its binding partners, such as PD-L1 , PD-L2. In some aspects, the PD-1 binding antagonist is a molecule that inhibits the binding of PD-1 to one or more of its binding partners. In a specific aspect, the PD-1 binding antagonist inhibits the binding of PD-1 to PD-L1 and/or PD-L2. For example, PD-1 binding antagonists include anti-PD-1 antibodies, antigen binding fragments thereof, immunoadhesins, fusion proteins, oligopeptides and other molecules that decrease, block, inhibit, abrogate or interfere with signal transduction resulting from the interaction of PD-1 with PD-L1 and/or PD-L2. In one aspect, a PD-1 binding antagonist reduces the negative co-stimulatory signal mediated by or through cell surface proteins expressed on T lymphocytes mediated signaling through PD-1 so as render a dysfunctional T cell less dysfunctional (e.g., enhancing effector responses to antigen recognition). In some aspects, the PD-1 binding antagonist is an anti-PD-1 antibody. In a specific aspect, a PD-1 binding antagonist is MDX-1 106 (nivolumab). In another specific aspect, a PD-1 binding antagonist is MK-3475

(pembrolizumab). In another specific aspect, a PD-1 binding antagonist is AMP-224. In another specific aspect, a PD-1 binding antagonist is MED1 -0680. In another specific aspect, a PD-1 binding antagonist is PDR001 (spartalizumab). In another specific aspect, a PD-1 binding antagonist is REGN281 0

(cemiplimab). In another specific aspect, a PD-1 binding antagonist is BGB-108.

The term“PD-L1 binding antagonist” refers to a molecule that decreases, blocks, inhibits, abrogates or interferes with signal transduction resulting from the interaction of PD-L1 with either one or more of its binding partners, such as PD-1 and B7-1 . In some aspects, a PD-L1 binding antagonist is a molecule that inhibits the binding of PD-L1 to its binding partners. In a specific aspect, the PD-L1 binding antagonist inhibits binding of PD-L1 to PD-1 and/or B7-1 . In some aspects, the PD-L1 binding antagonists include anti-PD-L1 antibodies, antigen binding fragments thereof, immunoadhesins, fusion proteins, oligopeptides and other molecules that decrease, block, inhibit, abrogate or interfere with signal transduction resulting from the interaction of PD-L1 with one or more of its binding partners, such as PD-1 and B7-1 . In one aspect, a PD-L1 binding antagonist reduces the negative co-stimulatory signal mediated by or through cell surface proteins expressed on T lymphocytes mediated signaling through PD- L1 so as to render a dysfunctional T cell less dysfunctional (e.g., enhancing effector responses to antigen recognition). In some aspects, a PD-L1 binding antagonist is an anti-PD-L1 antibody. In still another specific aspect, an anti-PD-L1 antibody is MPDL3280A (atezolizumab, marketed as TECENTRIQ™ with a WHO Drug Information (International Nonproprietary Names for Pharmaceutical Substances),

Recommended INN: List 74, Vol. 29, No. 3, 2015 (see page 387)). In a specific aspect, an anti-PD-L1 antibody is YW243.55.S70. In another specific aspect, an anti-PD-L1 antibody is MDX-1 105. In another specific aspect, an anti PD-L1 antibody is MSB0015718C. In still another specific aspect, an anti-PD-L1 antibody is MEDI4736.

The term“PD-L2 binding antagonist” refers to a molecule that decreases, blocks, inhibits, abrogates or interferes with signal transduction resulting from the interaction of PD-L2 with either one or more of its binding partners, such as PD-1 . In some aspects, a PD-L2 binding antagonist is a molecule that inhibits the binding of PD-L2 to one or more of its binding partners. In a specific aspect, the PD-L2 binding antagonist inhibits binding of PD-L2 to PD-1 . In some aspects, the PD-L2 antagonists include anti-PD-L2 antibodies, antigen binding fragments thereof, immunoadhesins, fusion proteins, oligopeptides and other molecules that decrease, block, inhibit, abrogate or interfere with signal transduction resulting from the interaction of PD-L2 with either one or more of its binding partners, such as PD-1 . In one aspect, a PD-L2 binding antagonist reduces the negative co-stimulatory signal mediated by or through cell surface proteins expressed on T lymphocytes mediated signaling through PD-L2 so as render a dysfunctional T cell less dysfunctional (e.g., enhancing effector responses to antigen recognition). In some aspects, a PD-L2 binding antagonist is an immunoadhesin.

A“subject” or an“individual” is a mammal. Mammals include, but are not limited to, domesticated animals (e.g., cows, sheep, cats, dogs, and horses), primates (e.g., humans and non-human primates such as monkeys), rabbits, and rodents (e.g., mice and rats). In certain aspects, the subject or individual is a human.

As used herein,“administering” is meant a method of giving a dosage of a compound (e.g., a chemotherapeutic agent) to a subject. In some aspects, the compositions utilized in the methods herein are administered intravenously. The compositions utilized in the methods described herein can be administered, for example, intramuscularly, intravenously, intradermally, percutaneously, intraarterially, intraperitoneally, intralesionally, intracranially, intraarticularly, intraprostatically, intrapleurally, intratracheally, intranasally, intravitreally, intravaginally, intrarectally, topically, intratumorally, peritoneally, subcutaneously, subconjunctivally, intravesicularlly, mucosally, intrapericardially, intraumbilically, intraocularly, orally, topically, locally, by inhalation, by injection, by infusion, by continuous infusion, by localized perfusion bathing target cells directly, by catheter, by lavage, in cremes, or in lipid compositions. The method of administration can vary depending on various factors (e.g., the compound or composition being administered and the severity of the condition, disease, or disorder being treated).

The term“concomitant” or“concurrent” is used herein to refer to administration of two or more therapeutic agents, where at least part of the administration overlaps in time. Accordingly, concurrent administration includes a dosing regimen when the administration of one or more agent(s) continues after discontinuing the administration of one or more other agent(s).

By“reduce or inhibit” is meant the ability to cause an overall decrease of 20%, 30%, 40%, 50%, 60%, 70%, 75%, 80%, 85%, 90%, 95%, or greater. Reduce or inhibit can refer, for example, to the symptoms of the disorder being treated, the presence or size of metastases, or the size of the primary tumor.

II. DIAGNOSTIC METHODS AND ASSAYS

A. Diagnostic methods and assays

The invention features prognostic gene signatures for colorectal cancer (CRC) (e.g., an AVANT gene signature and a gene signature comprising the AVANT stromal genes and Granzyme B ( GZMB )), which, when measured and quantified as a score or expression level in a sample from an individual (e.g., an AVANT score, or an AVANT stromal score and a GZMB expression level), may be used to identify individuals that are at high risk or low risk of recurrence of a CRC following surgical resection of the CRC.

These prognostic gene signatures and the related scores enable improved strategies to guide diagnostic and therapeutic decisions for patients having a CRC, e.g., a stage I, stage II, or stage III CRC, or having had surgical resection of a CRC. Specifically, they may be used to identify individuals (e.g., individuals having an early stage CRC) who are at high risk for recurrence of the CRC following surgical resection and who may benefit from an adjuvant treatment comprising a chemotherapy. Similarly, the provided gene signatures and related scores may be used to identify patients who are at low risk for recurrence of a CRC following surgical resection and who are unlikely to need further treatment, e.g., an adjuvant treatment comprising a chemotherapy.

The invention is based, at least in part, on the discovery that measuring expression of (a) a set of genes comprising genes relating to proliferative, stromal, and immune biological functions (e.g., a set of genes comprising the AVANT gene signature) or (b) a set of genes comprising genes relating to stromal biological functions (e.g., a set of genes comprising the AVANT stromal signature) and GZMB can be used as a prognostic signature in an individual having a CRC or having had surgical resection of a CRC, e.g., for determining whether the individual is a high risk of CRC recurrence following surgical resection of a CRC.

/^'. A VANT score

In some aspects, the invention features a method of predicting disease progression in an individual having a colorectal cancer (CRC), the method comprising determining an AVANT score from a sample from the individual, wherein an AVANT score that is above a reference AVANT score identifies the individual as one who is at high risk of CRC recurrence following surgical resection.

In some aspects, the invention features a method of predicting disease recurrence in an individual who has had surgical resection of a CRC, the method comprising determining an AVANT score from a sample from the individual, wherein an AVANT score that is above a reference AVANT score indicates that the individual is at high risk of CRC recurrence. ia. Determination of A VANT score

In some aspects, the invention features methods that include determining an AVANT score from a sample from an individual having a CRC or having had surgical resection of a CRC, e.g., a CRC described in Section MB herein.

In some aspects, the AVANT score is determined by measuring the expression level of a set of genes comprising the AVANT signature genes, which relate to stromal, immune, and proliferative biological functions and are set forth in Table 1 or Table 2.

Table 1. 23-gene AVANT signature

Table 2. 53-gene AVANT signature

In some aspects, determining the AVANT score comprises measuring the expression level of one or more genes relating to stromal biological function. In some aspects, the gene relating to stromal biological function is WBSCR17, TLL 1, CRYAB, ABCC9, HEYL, DTX1, SPP1, RGS2, IGFBP1, KDM5D, REG4, PCSK1, SMAD9, TCF12, or SMAD3. In some aspects, the gene relating to stromal biological function is ANGPT1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, or MAPK3.

In some aspects, determining the AVANT score comprises measuring the expression level of one or more genes relating to immune biological function. In some aspects, the gene relating to immune biological function is GZMB, CXCL 1, or CD28. In some aspects, the gene relating to immune biological function is TP73, TAP1, GZMB, TNF, CXCL 1, PDCD1, FCRL5, CXCR4, or CD28.

In some aspects, determining the AVANT score comprises measuring the expression level of one or more genes relating to proliferative biological function. In some aspects, the one or more genes relating to proliferative biological function are selected from DTX2, KDM1A, CDCA5, E2F1, or GMNN. In some aspects, the one or more genes relating to proliferative biological function are selected from RPL23, AXIN2, CDKN1B, DTX2, RPS6KA 1, KDM1A, RHOA, SP2, SHISA5, MLH1, CDCA5, E2F1, CENPM, CDK2, GMNN, or DNMT1.

In some aspects, determining the AVANT score comprises measuring the expression level of CDCA5, DTX2, E2F1, GMNN, KDM1A, ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, TCF12, CD28, CXCL 1, and GZMB in a sample from an individual.

In some aspects, determining the AVANT score comprises measuring the expression level of CDCA5, DTX2, E2F1, GMNN, KDM1A, ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, TCF12, CD28, CXCL 1, GZMB, RPLN23, AXIN2, CDKN1B, RPS6KA 1, RHOA, SP2, SHISA5, MLH1, CENPM, CDK2, DNMT1, ANGPT1, IGFBP3, CD36, HBEGF, FOS, SERPINB13, APCDD1, SCD5, POU5F1, EPHA4, FLT1, CDK6, MAPK3, TP73, TAP1,

TNF, PDCD 1, FCRL5, and CXCR4 in a sample from an individual.

The AVANT score may be determined from any suitable sample, e.g., a tissue biopsy, a whole blood sample, a buccal swab, a plasma sample, a serum sample, or a combination thereof, e.g., an archival sample, a fresh sample, or a frozen sample, e.g., a tissue biopsy, e.g., a formalin-fixed paraffin- embedded sample. In some aspects, the sample is from a surgically resected CRC. In some aspects, the sample is obtained from the individual prior to the administration of any adjuvant treatment.

In some aspects, the AVANT score is determined by measuring the expression level of a set of genes in the sample from the individual. In some aspects, the expression level is a nucleic acid expression level, e.g., a mRNA expression level. In some aspects, the mRNA expression level is determined by, e.g., direct digital counting of nucleic acids (e.g., digital counting of nucleic acids is by NANOSTRING^® NCOUNTER^® analysis), RNA-seq, RT-qPCR, qPCR, multiplex qPCR or RT-qPCR, microarray analysis, or a combination thereof. In other aspects, the expression level is a protein expression level. In some aspects, the protein expression level is determined by, e.g., an immunoassay, liquid chromatography-mass spectrometry (LC-MS) technology, nephelometry, aptamer technology, or a combination thereof. lb. Reference A VANT score

In some aspects, the AVANT score of a sample from an individual is compared to a reference AVANT score, e.g., an AVANT score in a reference population of individuals. In some aspects, the reference population is a population of individuals who have had surgical resection of a CRC, e.g., a CRC as described in Section MB herein. In some aspects, the reference population includes individuals having a CRC that is stage I, stage II, stage III, or stage IV, according to the TNM classification system at the onset of treatment. In some aspects, the reference population is the population of the GSE39582 cohort (Marisa et al, PLoS Med 2013). In other aspects, the reference population includes individuals having a histologically confirmed stage III - N1 , stage III - N2, or high-risk stage II colon carcinoma, according to the TNM classification system at the onset of treatment. In some aspects, the reference population is the population of the AVANT clinical trial (ClinicalTrials.gov identifier NCT001 12918) (de Gramont et al., J Clin Oncol., 1 8: 2938-2947, 2000). In some aspects, the reference population is the biomarker evaluable population (BEP) of the AVANT clinical trial. In some aspects, the reference population of individuals has been administered an adjuvant treatment comprising a chemotherapy, e.g., a chemotherapy as described in Section NIC herein. In some aspects, a sample, e.g., a tissue biopsy, a whole blood sample, a buccal swab, a plasma sample, a serum sample, or a combination thereof, is obtained from the individual in a reference population of individuals prior to the administration of any adjuvant treatment, e.g., prior to the administration of an adjuvant treatment comprising a chemotherapy.

In some aspects, the reference AVANT score is an AVANT score that significantly separates a first subset and a second subset of individuals in the reference population based on responsiveness to treatment, e.g., overall survival (OS), disease-free survival (DFS), and/or recurrence-free survival (RFS).

In some aspects, the reference AVANT score is a pre-assigned reference AVANT score. In some aspects, the reference AVANT score is defined as between the 25^th percentile and the 75^th percentile of AVANT scores in the reference population, e.g., the 25^th percentile, 26^th percentile, 27^th percentile, 28^th percentile, 29^th percentile, 30^th percentile, 31 ^st percentile, 32^nd percentile, 33^rd percentile, 34^th percentile, 35^th percentile, 36^th percentile, 37^th percentile, 38^th percentile, 39^th percentile, 40^th percentile, 41 ^st percentile, 42^nd percentile, 43^rd percentile, 44^th percentile, 45^th percentile, 46^th percentile, 47^th percentile, 48^th percentile, 49^th percentile, 50^th percentile, 51 ^st percentile, 52^nd percentile, 53^rd percentile, 54^th percentile, 55^th percentile, 56^th percentile, 57^th percentile, 58^th percentile, 59^th percentile, 60^th percentile, 61 ^st percentile, 62^nd percentile, 63^rd percentile, 64^th percentile, 65^th percentile, 66^th percentile, 67^th percentile, 68^th percentile, 69^th percentile, 70^th percentile, 71 ^st percentile, 72^nd percentile, 73^rd percentile, 74^th percentile, or 75^th percentile of AVANT scores in the reference population. In some aspects, the reference AVANT score is defined as between the 25^th percentile and the 99^th percentile of AVANT scores in the reference population.

In some aspects, the reference AVANT score is defined as the 25^th percentile of AVANT scores in the reference population. In some aspects, the reference AVANT score is defined as the 50^th percentile of AVANT scores in the reference population. In some aspects, the reference AVANT score is defined as the 75^th percentile of AVANT scores in the reference population. ic. Prognostic methods using A VANT score

In some aspects, the invention features a method of predicting disease progression in an individual having a CRC, the method comprising determining an AVANT score from a sample from the individual, wherein an AVANT score that is above a reference AVANT score identifies the individual as one who is at high risk of CRC recurrence following surgical resection. In some aspects, the AVANT score of the individual is above the reference AVANT score and the individual is identified as one who is at a high risk of CRC recurrence following surgical resection. In some aspects, the method further comprises administering to the individual an adjuvant treatment comprising a chemotherapy. In other aspects, the AVANT score of the individual is below the reference AVANT score. In some aspects, the individual is identified as one who is at a low risk of CRC recurrence following surgical resection. In some aspects, the individual is not administered an adjuvant treatment comprising a chemotherapy.

In some aspects, the invention features a method of predicting disease recurrence in an individual who has had surgical resection of a CRC, the method comprising determining an AVANT score from a sample from the individual, wherein an AVANT score that is above a reference AVANT score indicates that the individual is at high risk of CRC recurrence. In some aspects, the AVANT score of the individual is above the reference AVANT score and the individual is identified as one who is at a high risk of CRC recurrence. In some aspects, the method further comprises administering to the individual an adjuvant treatment comprising a chemotherapy. In other aspects, the AVANT score of the individual is below the reference AVANT score. In some aspects, the individual is identified as one who is at a low risk of CRC recurrence. In some aspects, the individual is not administered an adjuvant treatment comprising a chemotherapy.

In some aspects, the disclosure features a method of providing a prognosis for an individual having a CRC, the method comprising determining an AVANT score from a sample from the individual, wherein an AVANT score that is above a reference AVANT score identifies the individual as one who may have a poor prognosis. In some aspects, the method further comprises administering to the individual an adjuvant treatment comprising a chemotherapy.

/^'/^'. A VANT stromal score and expression level of GZMB

In some aspects, the invention features a method of predicting disease progression in an individual having a CRC, the method comprising determining an AVANT stromal score and the expression level of GZMB in a sample from the individual, wherein an AVANT stromal score that is above a reference AVANT stromal score and an expression level of GZMB that is below a reference expression level of GZMB identifies the individual as one who is at a high risk of CRC recurrence following surgical resection.

In some aspects, the invention features a method of predicting disease recurrence in an individual who has had surgical resection of a CRC, the method comprising determining an AVANT stromal score and the expression level of GZMB in a sample from the individual, wherein an AVANT stromal score that is above a reference AVANT stromal score and an expression level of GZMB that is below a reference expression level of GZMB indicates that the individual is at high risk of CRC recurrence. iia. Determination of AV ANT stromal score and expression level of GZMB In some aspects, the invention features methods that include determining an AVANT stromal score and the expression level of GZMB from a sample from an individual having a CRC or having had surgical resection of a CRC, e.g., a CRC described in Section MB herein.

In some aspects, the AVANT stromal score is determined by measuring the expression level of one or more genes relating to stromal biological function. In some aspects, the gene relating to stromal biological function is WBSCR17, TLL 1, CRYAB, ABCC9, HEYL, DTX1, SPP1, RGS2, IGFBP1, KDM5D, REG4, PCSK1, SMAD9, TCF12, or SMAD3. In some aspects, the gene relating to stromal biological function is ANGPT1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, or MAPK3.

In some aspects, determining the AVANT stromal score comprises measuring the expression level of ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12 in a sample from an individual.

In some aspects, determining the AVANT stromal score comprises measuring the expression level of ANGPT1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, and MAPK3 in a sample from an individual.

In some aspects, determining the expression level of GZMB comprises measuring the expression level of GZMB.

The AVANT stromal score and expression level of GZMB may be determined from any suitable sample, e.g., a tissue biopsy, a whole blood sample, a buccal swab, a plasma sample, a serum sample, or a combination thereof, e.g., an archival sample, a fresh sample, or a frozen sample, e.g., a tissue biopsy, e.g., a formalin-fixed paraffin-embedded sample. In some aspects, the sample is from a surgically resected CRC. In some aspects, the sample is obtained from the individual prior to the administration of any adjuvant treatment.

In some aspects, the AVANT stromal score is determined by measuring the expression level of a set of genes in the sample from the individual. In some aspects, the expression level is a nucleic acid expression level, e.g., a mRNA expression level. In some aspects, the mRNA expression level is determined by, e.g., direct digital counting of nucleic acids (e.g., digital counting of nucleic acids is by NANOSTRING^® NCOUNTER^® analysis), RNA-seq, RT-qPCR, qPCR, multiplex qPCR or RT-qPCR, microarray analysis, or a combination thereof. In other aspects, the expression level is a protein expression level. In some aspects, the protein expression level is determined by, e.g., an immunoassay, liquid chromatography-mass spectrometry (LC-MS) technology, nephelometry, aptamer technology, or a combination thereof. lib. Reference A VANT stromal score and GZMB expression level

In some aspects, the AVANT stromal score and expression level of GZMB in a sample from an individual are compared to an AVANT stromal score and expression level of GZMB in a reference population, e.g., an AVANT stromal score and expression level of GZMB as in a reference population of individuals, e.g., a reference population as described in Section 11 A (ib) herein.

In some aspects, reference expression level of GZMB alone, or the reference AVANT stromal score and reference expression level of GZMB, when considered together, significantly separate a first subset and a second subset of individuals based on responsiveness to treatment, e.g., OS, DFS, and/or RFS.

In some aspects, the reference AVANT stromal score is a pre-assigned reference AVANT stromal score. In some aspects, the reference AVANT stromal score is defined as between the 25^th percentile and the 75^th percentile of AVANT stromal scores in the reference population, e.g., the 25^th percentile, 26^th percentile, 27^th percentile, 28^th percentile, 29^th percentile, 30^th percentile, 31 ^st percentile, 32^nd percentile, 33^rd percentile, 34^th percentile, 35^th percentile, 36^th percentile, 37^th percentile, 38^th percentile, 39^th percentile, 40^th percentile, 41 ^st percentile, 42^nd percentile, 43^rd percentile, 44^th percentile, 45^th percentile, 46^th percentile, 47^th percentile, 48^th percentile, 49^th percentile, 50^th percentile, 51 ^st percentile, 52^nd percentile, 53^rd percentile, 54^th percentile, 55^th percentile, 56^th percentile, 57^th percentile, 58^th percentile, 59^th percentile, 60^th percentile, 61 ^st percentile, 62^nd percentile, 63^rd percentile, 64^th percentile, 65^th percentile, 66^th percentile, 67^th percentile, 68^th percentile, 69^th percentile, 70^th percentile, 71 ^st percentile, 72^nd percentile, 73^rd percentile, 74^th percentile, or 75^th percentile of AVANT stromal scores in the reference population. In some aspects, the reference AVANT stromal score is defined as between the 25^th percentile and the 99^th percentile of AVANT stromal scores in the reference population.

In some aspects, the reference AVANT stromal score is defined as the median AVANT stromal score in the reference population.

In some aspects, the reference expression level of GZMB is a pre-assigned reference expression level of GZMB. In some aspects, the reference expression level of GZMB is defined as between the 25^th percentile and the 75^th percentile of expression levels of GZMB in the reference population, e.g., the 25^th percentile, 26^th percentile, 27^th percentile, 28^th percentile, 29^th percentile, 30^th percentile, 31 ^st percentile, 32^nd percentile, 33^rd percentile, 34^th percentile, 35^th percentile, 36^th percentile, 37^th percentile, 38^th percentile, 39^th percentile, 40^th percentile, 41 ^st percentile, 42^nd percentile, 43^rd percentile, 44^th percentile, 45^th percentile, 46^th percentile, 47^th percentile, 48^th percentile, 49^th percentile, 50^th percentile, 51 ^st percentile, 52^nd percentile, 53^rd percentile, 54^th percentile, 55^th percentile, 56^th percentile, 57^th percentile, 58^th percentile, 59^th percentile, 60^th percentile, 61 ^st percentile, 62^nd percentile, 63^rd percentile, 64^th percentile, 65^th percentile, 66^th percentile, 67^th percentile, 68^th percentile, 69^th percentile, 70^th percentile, 71 ^st percentile, 72^nd percentile, 73^rd percentile, 74^th percentile, or 75^th percentile of AVANT scores in the reference population. In some aspects, the reference expression level of GZMB is defined as between the 25^th percentile and the 99^th percentile of expression levels of GZMB in the reference population.

In some aspects, the reference expression level of GZMB is defined as the median expression level of GZMB in the reference population.

In some aspects, the reference AVANT stromal score is defined as the median of AVANT stromal scores in the reference population and the reference expression level of GZMB is defined as the median expression level of GZMB in the reference population. iic. Prognostic methods using A VANT stromal score and GZMB expression level

In some aspects, the invention features a method of predicting disease recurrence in an individual who has had surgical resection of a CRC, the method comprising determining an AVANT stromal score and the expression level of GZMB in a sample from the individual, wherein an AVANT stromal score that is above a reference AVANT stromal score and an expression level of GZMB that is below a reference expression level of GZMB indicates that the individual is at high risk of CRC recurrence.

In some aspects, the AVANT stromal score is above a reference AVANT stromal score and the expression level of GZMB is below a reference expression level of GZMB, and the method further comprises administering to the individual an adjuvant treatment comprising a chemotherapy. In some aspects, an AVANT stromal score that is below a reference AVANT stromal score and an expression level of GZMB that is above a reference expression level of GZMB identifies the individual as one who is at low risk of CRC recurrence following surgical resection. In some aspects, the individual is not administered an adjuvant treatment comprising a chemotherapy.

In some aspects, an AVANT stromal score that is below a reference AVANT stromal score and an expression level of GZMB that is below a reference expression level of GZMB identifies the individual as one who is at low risk of CRC recurrence following surgical resection. In some aspects, the individual is not administered an adjuvant treatment comprising a chemotherapy. iii. Methods of assessing tumors

In some aspects, the invention comprises determining (a) an AVANT score or (b) an AVANT stromal score and the expression level of GZMB for an individual, and further comprises determining one or more additional properties (e.g., consensus molecular subtype (CMS), microsatellite instability (MSI) status, KRAS status, or BRAF status) from a sample from the individual. In some aspects, the AVANT score or AVANT stromal score and expression level of GZMB and the one or more additional properties are determined from the same sample from the individual, e.g., a tissue biopsy, a whole blood sample, a buccal swab, a plasma sample, a serum sample, or a combination thereof, e.g., an archival sample, a fresh sample, or a frozen sample, e.g., a tissue biopsy, e.g., a formalin-fixed paraffin-embedded sample. On other aspects, the one or more additional properties are determined from an additional sample from the individual, e.g., an additional tissue biopsy, whole blood sample, buccal swab, plasma sample, serum sample, or combination thereof. In some aspects, the one or more additional properties are determined following surgical resection of the CRC, e.g., are determined from a surgically resected CRC tumor. In some aspects, the sample is obtained from the individual prior to the administration of any adjuvant treatment.

In some aspects, the additional property is CMS. CMS may be determined as described in Guinney et al., Nat Med, 21 (1 1 ): 1350-1362, 2015. In some aspects, the CMS of the sample is CMS1 , CMS2, CMS3, or CMS4. In some aspects, the CMS of the sample is CMS4.

In some aspects, the additional property is MSI status. In some aspects, MSI status is determined to be microsatellite stable or microsatellite instability low (MSS). In other aspects, MSI status is determined to be microsatellite instability high (MSI-H). MSI status may be determined using methods known in the art, e.g., by assessing a panel of five microsatellite loci as described in Marisa et al. , PLoS Med, 10: e1001453, 2013 and Boland et al., Cancer Res, 58(22): 5248-5257, 1998.

In some aspects, the additional property is KRAS status. In some aspects, KRAS status refers to the presence or absence of one or more changes in the nucleotide or amino acid sequence of KRAS, e.g., one or more nucleotide substitution mutations resulting in a mutation at position 12 of the KRAS amino acid sequence (e.g. a G12A, G12R, G12D, G12C, G12S, G12V, or G12D mutation) or a mutation at position 13 of the KRAS amino acid sequence (e.g., a G13D mutation), as described in Marisa et al., PLoS Med, 10: e1001453, 2013, Lievre et al., J Clin Oncol, 26: 374-379, 2008, and Lievre et al., Cancer Res, 66(8): 3992-3995, 2006). The change in the nucleotide sequence may also be any missense or nonsense mutation that is observed in the CRC, but not in adjacent normal tissue (Stransky et al., Science, 333: 1 157-1 160, 201 1 ). KRAS status may be determined using methods known in the art, e.g., an allelic discrimination assay using TaqMan probes, as described in Lievre et al., J Clin Oncol, 26: 374- 379, 2008, or a MuTect assay, as described in Stransky et al., Science, 333: 1 157-1 160, 201 1 .

In some aspects, the additional property is BRAF status. In some aspects, BRAF status refers to the presence or absence of one or more changes in the nucleotide or amino acid sequence of BRAF.

The change in the nucleotide sequence may be, e.g., a c. 1799T>A nucleotide substitution mutation, e.g., a mutation resulting in a V600E change in the amino acid sequence (Marisa et al., PLoS Med, 10:

e1001453, 2013). The change in the nucleotide sequence may also be any missense or nonsense mutation that is observed in the CRC, but not in adjacent normal tissue (Stransky et al., Science, 333:

1 157-1 160, 201 1 ). BRAF status may be determined using methods known in the art, e.g., an allelic discrimination assay using TaqMan probes, as described in Marisa et al., PLoS Med, 1 0: e1001453,

2013, or a MuTect assay, as described in Stransky et al., Science, 333: 1 1 57-1 160, 201 1 .

B. Cancers

In some aspects, the individual has a colorectal cancer (CRC). In some aspects, the individual has had surgical resection of a CRC. In some aspects, the CRC of the individual is a stage I, stage II, or stage III CRC, according to the TNM classification system at the onset of treatment. In some aspects, the CRC of the individual is a stage III - N1 , stage III - N2, or high-risk stage II CRC, according to the TNM classification system at the onset of treatment, wherein a“high-risk stage II CRC” may be identified as a stage II CRC in an individual having one or more of T4 tumors; bowel obstruction or perforation;

histological signs of vascular invasion (i.e., blood and lymphatic vessels) or perineural invasion; age less than 50 years; and sub-optimal surgery (less than 12 nodes analyzed). In some aspects, the individual does not have a stage IV CRC according to the TNM classification system at the onset of treatment. In some aspects, the individual does not have a metastatic CRC. In some aspects, the CRC of the individual is characterized as consensus molecular subtype 1 (CMS1 ), CMS2, CMS3, CMS4, or unclassified, as defined in Guinney et al., Nat Med, 21 (1 1 ): 1350-1362, 2015. In some aspects, the CRC of the individual is a left-sided tumor, i.e., a tumor occurring in the distal colon (e.g., the distal third of the transverse colon, the splenic flexure the descending colon, the sigmoid colon, or the rectum) or a right sided tumor, i.e., a tumor occurring in the proximal colon (e.g., the proximal two-thirds of the transverse colon, the ascending colon, and the cecum). In some aspects, the CRC of the individual is a colon carcinoma. The colon carcinoma may be CMS1 , CMS2, CMS3, CMS4, or unclassified and may be a left sided or a right-sided colon carcinoma. In some aspects, the colon carcinoma is a stage III - N1 , stage III - N2, or high-risk stage II colon carcinoma, according to the TNM classification system at the onset of treatment. In some aspects, the CRC (e.g., colon carcinoma) of the individual is resectable. In some aspects, the CRC has been surgically resected. In some aspects, one or more properties of the CRC of the individual, e.g., CMS, are determined following surgical resection of the CRC, e.g., are determined from the surgically resected CRC tumor.

In some aspects, an individual in a reference population has a colorectal cancer (CRC). In some aspects, the individual in a reference population has had surgical resection of a CRC. In some aspects, the CRC of the individual in a reference population is a stage I, stage II, stage III, or stage IV CRC, according to the TNM classification system at the onset of treatment. In some aspects, the CRC of the individual in a reference population is a stage III - N1 , stage III - N2, or high-risk stage II CRC, according to the TNM classification system at the onset of treatment, wherein a“high-risk stage II CRC” may be identified as a stage II CRC in an individual having one or more of T4 tumors; bowel obstruction or perforation ; histological signs of vascular invasion (i.e. , blood and lymphatic vessels) or perineural invasion; age less than 50 years; and sub-optimal surgery (less than 12 nodes analyzed). In some aspects, the CRC of the individual in a reference population is characterized as consensus molecular subtype 1 (CMS1 ), CMS2, CMS3, CMS4, or unclassified, as defined in Guinney et al., Nat Med, 21 (1 1 ): 1350-1362, 2015. In some aspects, the CRC of the individual in a reference population is a left-sided tumor, i.e., a tumor occurring in the distal colon (e.g., the distal third of the transverse colon, the splenic flexure the descending colon, the sigmoid colon, or the rectum) or a right-sided tumor, i.e., a tumor occurring in the proximal colon (e.g., the proximal two-thirds of the transverse colon, the ascending colon, and the cecum). In some aspects, the CRC of the individual in a reference population is a colon carcinoma. The colon carcinoma may be CMS1 , CMS2, CMS3, CMS4, or unclassified and may be a left sided or a right-sided colon carcinoma. In some aspects, the colon carcinoma is a stage III - N1 , stage III - N2, or high-risk stage II colon carcinoma, according to the TNM classification system at the onset of treatment. In some aspects, the CRC (e.g., colon carcinoma) of the individual in a reference population is resectable. In some aspects, the CRC has been surgically resected. In some aspects, one or more properties of the CRC of the individual in a reference population, e.g., CMS, are determined following surgical resection of the CRC, e.g., are determined from the surgically resected CRC tumor.

III. Methods of treatment

A. Methods

/^'. Methods of treatment using A VANT score

In some aspects, the invention features a method of treating an individual having a CRC or having had surgical resection of a CRC, the method comprising (a) determining an AVANT score from a sample from the individual, wherein the AVANT score is above a reference AVANT score; and (b) administering to the individual an adjuvant treatment comprising a chemotherapy.

In some aspects, the invention features a method of treating an individual having a CRC or having had surgical resection of a CRC, the method comprising administering an adjuvant treatment comprising a chemotherapy to the individual, for whom an AVANT score from a sample from the individual has been determined to be above a reference AVANT score.

The CRC may be a CRC as described in Section MB herein.

The AVANT score from a sample from the individual may be determined as described in Section IIA (ia) herein.

The reference AVANT score may be a reference AVANT score as described in Section IIA (ib) herein.

The adjuvant treatment comprising a chemotherapy may be an adjuvant treatment as described in Section MID herein.

In some aspects, the invention features a method of treating an individual having a CRC, the method comprising (a) determining an AVANT stromal score and the expression level of GZMB in a sample from the individual, wherein the AVANT stromal score is above a reference AVANT stromal score and the expression level of GZMB is below a reference expression level of GZMB ; and (b) administering to the individual an adjuvant treatment comprising a chemotherapy.

In some aspects, the invention features a method of treating an individual having a CRC, the method comprising administering an adjuvant treatment comprising a chemotherapy to the individual, for whom an AVANT stromal score from a sample from the individual has been determined to be above a reference AVANT stromal score and an expression level of GZMB has been determined to be below a reference expression level of GZMB.

The CRC may be a CRC as described in Section MB herein.

The AVANT stromal score and expression level of GZMB from a sample from the individual may be determined as described in Section IIA (iia) herein.

The reference AVANT stromal score and reference expression level of GZMB may be a reference AVANT stromal score and reference expression level of GZMB as described in Section IIA (lib) herein.

B. Cancers

In some aspects, an adjuvant therapy comprising a chemotherapeutic agent is used to treat or delay recurrence or progression of a colorectal cancer (CRC) in a subject in need thereof. In some aspects, the subject is a human.

In some aspects, an individual has a colorectal cancer (CRC) or has had surgical resection of a CRC, e.g., a stage I, stage II, or stage III CRC according to the TNM classification system at the onset of treatment, e.g., a CRC as described in Section MB herein.

In some aspects, an individual in a reference population has a colorectal cancer (CRC) or has had surgical resection of a CRC, e.g., a stage I, stage II, or stage III CRC according to the TNM classification system at the onset of treatment, e.g., a CRC as described in Section MB herein.

C. Primary therapies

In some aspects, the primary therapy comprises surgical resection of the cancer, e.g., surgical resection of a CRC. In some aspects, the surgical resection has occurred no less than four weeks and not more than eight weeks before the onset of adjuvant treatment.

D. Adjuvant therapies comprising a chemotherapeutic agent

In some aspects, the individual is further treated with an adjuvant therapy, e.g., treated with an adjuvant therapy comprising a chemotherapeutic agent following surgical resection of a CRC. In some aspects, the individual is not treated with a therapy comprising a chemotherapeutic agent preceding surgical resection of the CRC. Chemotherapeutic agents

In some aspects, an individual is administered an adjuvant treatment comprising a

chemotherapeutic agent. A chemotherapeutic agent is a chemical compound useful in the treatment of cancer. Exemplary chemotherapeutic agents include, but are not limited to erlotinib (TARCEVA®, Genentech/OSI Pharm.), anti-hormonal agents that act to regulate or inhibit hormone action on tumors such as anti-estrogens and selective estrogen receptor modulators (SERMs), antibodies such as bevacizumab (AVASTIN®, Genentech), alemtuzumab (Campath), cetuximab (ERBITUX®, Imclone), panitumumab (VECTIBIX®, Amgen), rituximab (RITUXAN®, Genentech/Biogen Idee), pertuzumab (OMNITARG®, 2C4, Genentech), or trastuzumab (HERCEPTIN®, Genentech), EGFR inhibitors (EGFR antagonists), tyrosine kinase inhibitors, and chemotherapeutic agents also include non-steroidal anti inflammatory drugs (NSAIDs) with analgesic, antipyretic and anti-inflammatory effects.

In some aspects, the chemotherapy comprises oxaliplatin, fluorouracil, or leucovorin. In some aspects, the chemotherapy consists of oxaliplatin, fluorouracil, and leucovorin, e.g., is FOLFOX4. In some aspects, the adjuvant treatment comprises FOLFOX4 and bevacizumab. In some aspects, the adjuvant treatment comprises a first treatment comprising FOLFOX4 and bevacizumab and a second treatment comprising bevacizumab.

In some aspects, the chemotherapy comprises oxaliplatin and capecitabine, e.g., is XELOX. In some aspects, the adjuvant treatment comprises XELOX and bevacizumab.

E. Methods of delivery

The compositions utilized in the methods described herein (e.g., a chemotherapy, e.g., a chemotherapy comprising FOLFOX4 or XELOX) can be administered by any suitable method, including, for example, intravenously, intramuscularly, subcutaneously, intradermally, percutaneously,

intraarterially, intraperitoneally, intralesionally, intracranially, intraarticularly, intraprostatically, intrapleurally, intratracheally, intrathecally, intranasally, intravaginally, intrarectally, intratumorally, peritoneally, subconjunctivally, intravesicularly, mucosally, intrapericardially, intraumbilically, intraocularly, intraorbitally, orally, topically, transdermally, intravitreally (e.g., by intravitreal injection), by eye drop, by inhalation, by injection, by implantation, by infusion, by continuous infusion, by localized perfusion bathing target cells directly, by catheter, by lavage, in cremes, or in lipid compositions. The compositions utilized in the methods described herein can also be administered systemically or locally. The method of administration can vary depending on various factors (e.g., the compound or composition being administered and the severity of the condition, disease, or disorder being treated). In some aspects, a chemotherapeutic agent is administered intravenously, intramuscularly, subcutaneously, topically, orally, transdermally, intraperitoneally, intraorbitally, by implantation, by inhalation, intrathecally,

intraventricularly, or intranasally. Dosing can be by any suitable route, e.g., by injections, such as intravenous or subcutaneous injections, depending in part on whether the administration is brief or chronic. Various dosing schedules including but not limited to single or multiple administrations over various time-points, bolus administration, and pulse infusion are contemplated herein.

A chemotherapeutic agent may be formulated, dosed, and administered in a fashion consistent with good medical practice. Factors for consideration in this context include the particular disorder being treated, the particular mammal being treated, the clinical condition of the individual patient, the cause of the disorder, the site of delivery of the agent, the method of administration, the scheduling of

administration, and other factors known to medical practitioners. The immune checkpoint inhibitor need not be, but is optionally formulated with and/or administered concurrently with one or more agents currently used to prevent or treat the disorder in question, e.g., one or more of the agents provided in Section NI C herein. The effective amount of such other agents depends on the amount of the chemotherapeutic agent present in the formulation, the type of disorder or treatment, and other factors discussed above. These are generally used in the same dosages and with administration routes as described herein, or about from 1 to 99% of the dosages described herein, or in any dosage and by any route that is empirically/clinically determined to be appropriate.

For the treatment of a cancer, e.g., a cancer described in Section IIIA herein, the appropriate dosage of a chemotherapeutic agent described herein (when used alone or in combination with one or more other additional therapeutic agents) will depend on the type of disease to be treated, the severity and course of the disease, whether the chemotherapeutic agent is administered for preventive or therapeutic purposes, previous therapy, the patient’s clinical history and response to the

chemotherapeutic agent, and the discretion of the attending physician. The chemotherapeutic agent is suitably administered to the patient at one time or over a series of treatments. One typical daily dosage might range from about 1 pg/kg to 100 mg/kg or more, depending on the factors mentioned above. For repeated administrations over several days or longer, depending on the condition, the treatment would generally be sustained until a desired suppression of disease symptoms occurs. Such doses may be administered intermittently, e.g., every week or every three weeks (e.g., such that the patient receives, for example, from about two to about twenty, or e.g., about six doses of the chemotherapeutic agent). An initial higher loading dose, followed by one or more lower doses, may be administered. However, other dosage regimens may be useful. The progress of this therapy is easily monitored by conventional techniques and assays.

In some aspects, the treatment comprises 24 weeks of treatment with FOLFOX4 (oxaliplatin, leucovorin calcium, and 5-Fluorouracil (5-FU)); FOLFOX4 in combination with bevacizumab; or XELOX (capecitabine) in combination with bevacizumab. In some aspects, the treatment further comprises 24 weeks treatment with single-agent bevacizumab following the 24 week treatment with FOLFOX4 in combination with bevacizumab or XELOX in combination with bevacizumab.

F. Additional therapeutic agents

In some aspects, the chemotherapeutic agent is used with one or more additional therapeutic agents, e.g., a combination therapy. In some aspects, the composition comprising the chemotherapeutic agent further comprises the additional therapeutic agent. In another aspect, the additional therapeutic agent is delivered in a separate composition. In some aspects, the one or more additional therapeutic agents comprise a growth inhibitory agent, an anti-angiogenic agent, a radiation therapy, a cytotoxic agent, or a combination thereof.

Combination therapies as described above encompass combined administration (wherein two or more therapeutic agents are included in the same or separate formulations) and separate administration (wherein administration of a chemotherapeutic agent can occur prior to, simultaneously, and/or following, administration of the additional therapeutic agent or agents). In one aspect, administration of a chemotherapeutic agent and administration of an additional therapeutic agent occur within about one month, or within about one, two or three weeks, or within about one, two, three, four, five, or six days, of each other.

/^'. Growth inhibitory agents

In some aspects, the additional therapeutic agent is a growth inhibitory agent. Exemplary growth inhibitory agents include agents that block cell cycle progression at a place other than S phase, e.g., agents that induce G1 arrest (e.g., DNA alkylating agents such as tamoxifen, prednisone, dacarbazine, mechlorethamine, cisplatin, methotrexate, 5-fluorouracil, or ara-C) or M-phase arrest (e.g., vincristine, vinblastine, taxanes (e.g., paclitaxel and docetaxel), doxorubicin, epirubicin, daunorubicin, etoposide, or bleomycin).

/^'/^'. Radiation therapies

In some aspects, the additional therapeutic agent is a radiation therapy. Radiation therapies include the use of directed gamma rays or beta rays to induce sufficient damage to a cell so as to limit its ability to function normally or to destroy the cell altogether. Typical treatments are given as a one-time administration and typical dosages range from 10 to 200 units (Grays) per day. iii. Cytotoxic agents

In some aspects, the additional therapeutic agent is a cytotoxic agent, e.g., a substance that inhibits or prevents a cellular function and/or causes cell death or destruction. Cytotoxic agents include, but are not limited to, radioactive isotopes (e.g., At^{21 1} , I¹³¹ , 1¹²⁵, Y⁹⁰, Re¹⁸⁶, Re¹⁸⁸, Sm¹⁵³, Bi²¹², P³², Pb²¹², and radioactive isotopes of Lu); chemotherapeutic agents or drugs (e.g., methotrexate, adriamicin, vinca alkaloids (vincristine, vinblastine, etoposide), doxorubicin, melphalan, mitomycin C, chlorambucil, daunorubicin or other intercalating agents); growth inhibitory agents; enzymes and fragments thereof such as nucleolytic enzymes; antibiotics; toxins such as small molecule toxins or enzymatically active toxins of bacterial, fungal, plant or animal origin, including fragments and/or variants thereof; and antitumor or anticancer agents. iv. Immunomodulatory agents

In some aspects, the additional therapeutic agent is an immunomodulatory agent, e.g., a PD-L1 axis binding antagonist, which may be a PD-1 binding antagonist, a PD-L1 binding antagonist, or a PD-L2 binding antagonist. PD-1 (programmed death 1 ) is also referred to in the art as“programmed cell death 1 ,”“PDCD1 ,”“CD279,” and“SLEB2.” An exemplary human PD-1 is shown in UniProtKB/Swiss-Prot Accession No. Q151 16. PD-L1 (programmed death ligand 1 ) is also referred to in the art as

“programmed cell death 1 ligand 1 ,”“PDCD1 LG1 ,”“CD274,”“B7-H,” and“PDL1 An exemplary human PD-L1 is shown in UniProtKB/Swiss-Prot Accession No.Q9NZQ7.1 . PD-L2 (programmed death ligand 2) is also referred to in the art as“programmed cell death 1 ligand 2,”“PDCD1 LG2,”“CD273,”“B7-DC,” “Btdc,” and“PDL2.” An exemplary human PD-L2 is shown in UniProtKB/Swiss-Prot Accession No. Q9BQ51 . In some instances, PD-1 , PD-L1 , and PD-L2 are human PD-1 , PD-L1 and PD-L2.

In some aspects, the PD-1 binding antagonist is a molecule that inhibits the binding of PD-1 to its ligand binding partners. In a specific aspect the PD-1 ligand binding partners are PD-L1 and/or PD-L2.

In another instance, a PD-L1 binding antagonist is a molecule that inhibits the binding of PD-L1 to its binding ligands. In a specific aspect, PD-L1 binding partners are PD-1 and/or B7-1 . In another instance, the PD-L2 binding antagonist is a molecule that inhibits the binding of PD-L2 to its ligand binding partners. In a specific aspect, the PD-L2 binding ligand partner is PD-1 . The antagonist may be an antibody, an antigen binding fragment thereof, an immunoadhesin, a fusion protein, or oligopeptide.

In some aspects, the PD-1 binding antagonist is an anti-PD-1 antibody (e.g., a human antibody, a humanized antibody, or a chimeric antibody), for example, as described below. In some aspects, the anti-PD-1 antibody is selected from the group consisting of MDX-1 106 (nivolumab), MK-3475

(pembrolizumab), MEDI-0680 (AMP-514), PDR001 , REGN2810, and BGB-108. MDX-1 106, also known as MDX- 1 106-04, ONO-4538, BMS-936558, or nivolumab, is an anti-PD-1 antibody described in W02006/121 168. MK-3475, also known as pembrolizumab or lambrolizumab, is an anti-PD-1 antibody described in WO 2009/1 14335. In some instances, the PD-1 binding antagonist is an immunoadhesin (e.g., an immunoadhesin comprising an extracellular or PD-1 binding portion of PD-L1 or PD-L2 fused to a constant region (e.g., an Fc region of an immunoglobulin sequence). In some instances, the PD-1 binding antagonist is AMP-224. AMP-224, also known as B7-DCIg, is a PD-L2-Fc fusion soluble receptor described in WO 2010/027827 and WO 201 1 /066342.

In some aspects, the anti-PD-1 antibody is MDX-1 106. Alternative names for“MDX-1 106” include MDX-1 106-04, ONO-4538, BMS-936558, and nivolumab. In some aspects, the anti-PD-1 antibody is nivolumab (CAS Registry Number: 946414-94-4). In a still further aspect, provided is an isolated anti-PD-1 antibody comprising a heavy chain variable region comprising the heavy chain variable region amino acid sequence from SEQ ID NO: 1 and/or a light chain variable region comprising the light chain variable region amino acid sequence from SEQ ID NO: 2. In a still further aspect, provided is an isolated anti-PD-1 antibody comprising a heavy chain and/or a light chain sequence, wherein:

(a) the heavy chain sequence has at least 85%, at least 90%, at least 91 %, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99% or 100% sequence identity to the heavy chain sequence:

QVQLVESGGGVVQPGRSLRLDCKASGITFSNSGMHWVRQAPGKGLEWVAVIWYDGSKRYYADSVKGR

FTISRDNSKNTLFLQMNSLRAEDTAVYYCATNDDYWGQGTLVTVSSASTKGPSVFPLAPCSRSTSESTA

ALGCLVKDYFPEPVTVSWNSGALTSGVHTFPAVLQSSGLYSLSSVVTVPSSSLGTKTYTCNVDHKPSNT

KVDKRVESKYGPPCPPCPAPEFLGGPSVFLFPPKPKDTLMISRTPEVTCVVVDVSQEDPEVQFNWYVDG

VEVHNAKTKPREEQFNSTYRVVSVLTVLHQDWLNGKEYKCKVSNKGLPSSI EKTISKAKGQPREPQVYTL

PPSQEEMTKNQVSLTCLVKGFYPSDIAVEWESNGQPENNYKTTPPVLDSDGSFFLYSRLTVDKSRWQE

GNVFSCSVMHEALHNHYTQKSLSLSLGK (SEQ ID NO: 1 ), and

(b) the light chain sequences has at least 85%, at least 90%, at least 91 %, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99% or 100% sequence identity to the light chain sequence: EIVLTQSPATLSLSPGERATLSCRASQSVSSYLAWYQQKPGQAPRLLIYDASNRATGIPARFSGSGSGTD FTLTISSLEPEDFAVYYCQQSSNWPRTFGQGTKVEIKRTVAAPSVFIFPPSDEQLKSGTASVVCLLNNFYP REAKVQWKVDNALQSGNSQESVTEQDSKDSTYSLSSTLTLSKADYEKHKVYACEVTHQGLSSPVTKSFN RGEC (SEQ ID NO: 2).

In some aspects, the PD-L1 axis binding antagonist is a PD-L2 binding antagonist. In some aspects, the PD-L2 binding antagonist is an anti-PD-L2 antibody (e.g., a human antibody, a humanized antibody, or a chimeric antibody). In some aspects, the PD-L2 binding antagonist is an immunoadhesin.

In some aspects, the PD-L1 binding antagonist is an anti-PD-L1 antibody, for example, as described below. In some aspects, the anti-PD-L1 antibody is capable of inhibiting binding between PD- L1 and PD-1 and/or between PD-L1 and B7-1 . In some aspects, the anti-PD-L1 antibody is a monoclonal antibody. In some aspects, the anti-PD-L1 antibody is an antibody fragment selected from the group consisting of Fab, Fab’-SH, Fv, scFv, and (Fab’)2 fragments. In some aspects, the anti-PD-L1 antibody is a humanized antibody. In some aspects, the anti-PD-L1 antibody is a human antibody. In some aspects, the anti-PD-L1 antibody is selected from the group consisting of YW243.55.S70, MPDL3280A

(atezolizumab), MDX-1 105, and MEDI4736 (durvalumab), and MSB001071 8C (avelumab). Antibody YW243.55.S70 is an anti-PD-L1 described in WO 2010/077634. MDX-1 105, also known as BMS- 936559, is an anti-PD-L1 antibody described in W02007/005874. MEDI4736 (durvalumab) is an anti-PD- L1 monoclonal antibody described in WO201 1 /066389 and US2013/034559. Examples of anti-PD-L1 antibodies useful for the methods of this invention, and methods for making thereof are described in PCT patent application WO 2010/077634, WO 2007/005874, WO 201 1 /066389, U.S. Pat. No. 8,21 7,149, and US 2013/034559, which are incorporated herein by reference.

Anti-PD-L1 antibodies described in WO 2010/077634 A1 and US 8,217,149 may be used in the methods described herein. In some aspects, the anti-PD-L1 antibody comprises a heavy chain variable region sequence of SEQ ID NO: 3 and/or a light chain variable region sequence of SEQ ID NO: 4. In a still further aspect, provided is an isolated anti-PD-L1 antibody comprising a heavy chain variable region and/or a light chain variable region sequence, wherein:

EVQLVESGGGLVQPGGSLRLSCAASGFTFSDSWIHWVRQAPGKGLEWVAWISPYGGSTYYADSVKGR FTISADTSKNTAYLQMNSLRAEDTAVYYCARRHWPGGFDYWGQGTLVTVSS (SEQ ID NO: 3), and

(b) the light chain sequence has at least 85%, at least 90%, at least 91 %, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99% or 100% sequence identity to the light chain sequence:

DIQMTQSPSSLSASVGDRVTITCRASQDVSTAVAWYQQKPGKAPKLLIYSASFLYSGVPSRFSGSGSGT DFTLTISSLQPEDFATYYCQQYLYHPATFGQGTKVEIKR (SEQ ID NO: 4).

In one aspect, the anti-PD-L1 antibody comprises a heavy chain variable region comprising an HVR-H1 , HVR-H2 and HVR-H3 sequence, wherein:

(a) the HVR-H1 sequence is GFTFSXiSWIH (SEQ ID NO: 5);

(b) the HVR-H2 sequence is AWIX2PYGGSX3YYADSVKG (SEQ ID NO: 6); (c) the HVR-H3 sequence is RHWPGGFDY (SEQ ID NO: 7);

further wherein: Xi is D or G; X2 is S or L; X3 is T or S. In one specific aspect, Xi is D; X2 is S and X3 is T. In another aspect, the polypeptide further comprises variable region heavy chain framework sequences juxtaposed between the HVRs according to the formula: (FR-H1 )-(HVR-H1 )-(FR-H2)-(HVR- H2)-(FR-H3)-(HVR-H3)-(FR-H4). In yet another aspect, the framework sequences are derived from human consensus framework sequences. In a further aspect, the framework sequences are VH subgroup III consensus framework. In a still further aspect, at least one of the framework sequences is the following:

FR-H1 is EVQLVESGGGLVQPGGSLRLSCAAS (SEQ ID NO: 8) FR-H2 is WVRQAPGKGLEWV (SEQ ID NO: 9)

FR-H3 is RFTISADTSKNTAYLQMNSLRAEDTAVYYCAR (SEQ ID NO: 10) FR-H4 is WGQGTLVTVSS (SEQ ID NO: 1 1 ).

In a still further aspect, the heavy chain polypeptide is further combined with a variable region light chain comprising an HVR-L1 , HVR-L2 and HVR-L3, wherein:

(a) the HVR-L1 sequence is RASQX₄X₅X₆TX7X₈A (SEQ ID NO: 12)

(b) the HVR-L2 sequence is SASX9LX10S, (SEQ ID NO: 13)

(c) the HVR-L3 sequence is QQX11X12X13X14PX15T (SEQ ID NO: 14) wherein: X4 IS D or V; X5 is V or I; Cb is S or N; X7 is A or F; Xs is V or L; X9 is F or T; X10 is Y or A; Xn is Y, G, F, or S; X12 IS L, Y, F or W; X13 is Y, N, A, T, G, F or l ; Xi₄ is H, V, P, T or I ; X15 is A, W, R, P or T. In a still further aspect, X4 is D; X5 is V; Cb ίe S; X7 IS A; Xe is V; X9 is F; X10 is Y; Xn is Y; X12 IS L; X13 is Y; XM IS H ; X15 is A.

In a still further aspect, the light chain further comprises variable region light chain framework sequences juxtaposed between the HVRs according to the formula: (FR-L1 )-(HVR-L1 )-(FR-L2)-(HVR- L2)-(FR-L3)-(HVR-L3)-(FR-L4). In a still further aspect, the framework sequences are derived from human consensus framework sequences. In a still further aspect, the framework sequences are VL kappa I consensus framework. In a still further aspect, at least one of the framework sequence is the following:

FR-L1 is DIQMTQSPSSLSASVGDRVTITC (SEQ ID NO: 15)

FR-L2 is WYQQKPGKAPKLLIY (SEQ ID NO: 16)

FR-L3 is GVPSRFSGSGSGTDFTLTISSLQPEDFATYYC (SEQ ID NO: 17)

FR-L4 is FGQGTKVEIKR (SEQ ID NO: 18).

In another aspect, provided is an isolated anti-PD-L1 antibody or antigen binding fragment comprising a heavy chain and a light chain variable region sequence, wherein:

(a) the heavy chain comprises an HVR-H1 , HVR-H2 and HVR-H3, wherein further:

(i) the HVR-H1 sequence is GFTFSXiSWIH; (SEQ ID NO: 5)

(ii) the HVR-H2 sequence is AWIX2PYGGSX3YYADSVKG (SEQ ID NO: 6)

(iii) the HVR-H3 sequence is RHWPGGFDY, and (SEQ ID NO: 7)

(b) the light chain comprises an HVR-L1 , HVR-L2 and HVR-L3, wherein further:

(i) the HVR-L1 sequence is RASQX₄X₅X₆TX7X₈A (SEQ ID NO: 12)

(ii) the HVR-L2 sequence is SASX9LX10S; and (SEQ ID NO: 13) (iii) the HVR-L3 sequence is QQX11X12X13X14PX15T; (SEQ ID NO: 14) wherein: Xi is D or G; X2 IS S or L; X3 is T or S; X4 is D or V; Xs is V or I; Cb ίe S or N; X7 IS A or F; Xe is V or L; X₉ is F or T; X10 is Y or A; Xn is Y, G, F, or S; X12 is L, Y, F or W; X13 is Y, N, A, T, G, F or I; Xi₄ is H, V, P, T or I; X15 is A, W, R, P or T. In a specific aspect, Xi is D; X2 is S and X3 is T. In another aspect, X4 is D; Xs is V; X₆ is S; X₇ is A; X₈ is V; X₉ is F; X10 is Y; Xn is Y; X12 is L; X13 is Y; XM is H; X15 is A. In yet another aspect, Xi is D; X2 is S and X3 is T, X4 IS D; Xs is V; Cb ίe S; X₇ is A; X₈ is V; X₉ is F; X10 is Y; Xn is Y; X12 is L; X13 is Y; XM is H and X15 is A.

In a further aspect, the heavy chain variable region comprises one or more framework sequences juxtaposed between the HVRs as: (FR-H1 )-(HVR-H1 )-(FR-H2)-(HVR-H2)-(FR-H3)-(HVR-H3)-(FR-H4), and the light chain variable regions comprises one or more framework sequences juxtaposed between the HVRs as: (FR-L1 )-(HVR-L1 )-(FR-L2)-(HVR-L2)-(FR-L3)-(HVR-L3)-(FR-L4). In a still further aspect, the framework sequences are derived from human consensus framework sequences. In a still further aspect, the heavy chain framework sequences are derived from a Kabat subgroup I, II, or III sequence.

In a still further aspect, the heavy chain framework sequence is a VH subgroup III consensus framework. In a still further aspect, one or more of the heavy chain framework sequences are set forth as SEQ ID NOs: 8, 9, 10, and 1 1 . In a still further aspect, the light chain framework sequences are derived from a Kabat kappa I, II, II or IV subgroup sequence. In a still further aspect, the light chain framework sequences are VL kappa I consensus framework. In a still further aspect, one or more of the light chain framework sequences are set forth as SEQ ID NOs: 15, 16, 17, and 18.

In a still further specific aspect, the antibody further comprises a human or murine constant region. In a still further aspect, the human constant region is selected from the group consisting of lgG1 , lgG2, lgG2, lgG3, and lgG4. In a still further specific aspect, the human constant region is lgG1 . In a still further aspect, the murine constant region is selected from the group consisting of IgG 1 , lgG2A, lgG2B, and lgG3. In a still further aspect, the murine constant region in lgG2A. In a still further specific aspect, the antibody has reduced or minimal effector function. In a still further specific aspect, the minimal effector function results from an“effector-less Fc mutation” or aglycosylation mutation. In still a further aspect, the effector-less Fc mutation is an N297A or D265A/N297A substitution in the constant region.

In yet another aspect, provided is an anti-PD-L1 antibody comprising a heavy chain and a light chain variable region sequence, wherein:

(a) the heavy chain further comprises an HVR-H1 , HVR-H2 and an HVR-H3 sequence

having at least 85% sequence identity to GFTFSDSWIH (SEQ ID NO: 19), AWISPYGGSTYYADSVKG (SEQ ID NO: 20) and RHWPGGFDY (SEQ ID NO: 21 ), respectively, or

(b) the light chain further comprises an HVR-L1 , HVR-L2 and an HVR-L3 sequence having at least 85% sequence identity to RASQDVSTAVA (SEQ ID NO: 22), SASFLYS (SEQ ID NO: 23) and QQYLYHPAT (SEQ ID NO: 24), respectively.

In a specific aspect, the sequence identity is 86%, 87%, 88%, 89%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%.

In another aspect, the heavy chain variable region comprises one or more framework sequences juxtaposed between the HVRs as: (FR-H1 )-(HVR-H1 )-(FR-H2)-(HVR-H2)-(FR-H3)-(HVR-H3)-(FR-H4), and the light chain variable regions comprises one or more framework sequences juxtaposed between the HVRs as: (FR-L1 )-(HVR-L1 )-(FR-L2)-(HVR-L2)-(FR-L3)-(HVR-L3)-(FR-L4). In yet another aspect, the framework sequences are derived from human consensus framework sequences. In a still further aspect, the heavy chain framework sequences are derived from a Kabat subgroup I, II, or III sequence. In a still further aspect, the heavy chain framework sequence is a VH subgroup III consensus framework. In a still further aspect, one or more of the heavy chain framework sequences are set forth as SEQ ID NOs: 8, 9,

10, and 1 1 . In a still further aspect, the light chain framework sequences are derived from a Kabat kappa I, II, II, or IV subgroup sequence. In a still further aspect, the light chain framework sequences are VL kappa I consensus framework. In a still further aspect, one or more of the light chain framework sequences are set forth as SEQ ID NOs: 15, 16, 17, and 18.

In a still further aspect, the heavy chain framework sequence is a VH subgroup III consensus framework. In a still further aspect, one or more of the heavy chain framework sequences is the following:

FR-H1 EVQLVESGGGLVQPGGSLRLSCAASGFTFS (SEQ ID NO: 27)

FR-H2 WVRQAPGKGLEWVA (SEQ ID NO: 28)

FR-H3 RFTISADTSKNTAYLQMNSLRAEDTAVYYCAR (SEQ ID NO: 10)

FR-H4 WGQGTLVTVSS (SEQ ID NO: 1 1 ).

In a still further aspect, the light chain framework sequences are derived from a Kabat kappa I, II, II or IV subgroup sequence. In a still further aspect, the light chain framework sequences are VL kappa I consensus framework. In a still further aspect, one or more of the light chain framework sequences is the following:

FR-L1 DIQMTQSPSSLSASVGDRVTITC (SEQ ID NO: 15)

FR-L2 WYQQKPGKAPKLLIY (SEQ ID NO: 16)

FR-L3 GVPSRFSGSGSGTDFTLTISSLQPEDFATYYC (SEQ ID NO: 17)

FR-L4 FGQGTKVEIK (SEQ ID NO: 26).

In a still further specific aspect, the antibody further comprises a human or murine constant region. In a still further aspect, the human constant region is selected from the group consisting of lgG1 , lgG2, lgG2, lgG3, and lgG4. In a still further specific aspect, the human constant region is lgG1 . In a still further aspect, the murine constant region is selected from the group consisting of IgG 1 , lgG2A, lgG2B, and lgG3. In a still further aspect, the murine constant region in lgG2A. In a still further specific aspect, the antibody has reduced or minimal effector function. In a still further specific aspect the minimal effector function results from an“effector-less Fc mutation” or aglycosylation. In still a further aspect, the effector less Fc mutation is an N297A or D265A/N297A substitution in the constant region.

In yet another aspect, provided is an anti-PD-L1 antibody comprising a heavy chain and a light chain variable region sequence, wherein: (c) the heavy chain further comprises an HVR-H1 , HVR-H2 and an HVR-H3 sequence having at least 85% sequence identity to GFTFSDSWIH (SEQ ID NO: 19), AWISPYGGSTYYADSVKG (SEQ ID NO: 20) and RHWPGGFDY (SEQ ID NO: 21 ), respectively, and/or

(d) the light chain further comprises an HVR-L1 , HVR-L2 and an HVR-L3 sequence having at least 85% sequence identity to RASQDVSTAVA (SEQ ID NO: 22), SASFLYS (SEQ ID NO: 23) and QQYLYHPAT (SEQ ID NO: 24), respectively.

In a specific aspect, the sequence identity is 86%, 87%, 88%, 89%, 90%, 91 %, 92%, 93%, 94%,

95%, 96%, 97%, 98%, 99% or 100%.

In another aspect, the heavy chain variable region comprises one or more framework sequences juxtaposed between the HVRs as: (FR-H1 )-(HVR-H1 )-(FR-H2)-(HVR-H2)-(FR-H3)-(HVR-H3)-(FR-H4), and the light chain variable regions comprises one or more framework sequences juxtaposed between the HVRs as: (FR-L1 )-(HVR-L1 )-(FR-L2)-(HVR-L2)-(FR-L3)-(HVR-L3)-(FR-L4). In yet another aspect, the framework sequences are derived from human consensus framework sequences. In a still further aspect, the heavy chain framework sequences are derived from a Kabat subgroup I, II, or III sequence. In a still further aspect, the heavy chain framework sequence is a VH subgroup III consensus framework. In a still further aspect, one or more of the heavy chain framework sequences are set forth as SEQ ID NOs: 8, 9, 10, and WGQGTLVTVSSASTK (SEQ ID NO: 29).

In a still further aspect, the light chain framework sequences are derived from a Kabat kappa I, II, II or IV subgroup sequence. In a still further aspect, the light chain framework sequences are VL kappa I consensus framework. In a still further aspect, one or more of the light chain framework sequences are set forth as SEQ ID NOs: 1 5, 16, 17, and 18. In a still further specific aspect, the antibody further comprises a human or murine constant region. In a still further aspect, the human constant region is selected from the group consisting of lgG1 , lgG2, lgG2, lgG3, and lgG4. In a still further specific aspect, the human constant region is lgG1 . In a still further aspect, the murine constant region is selected from the group consisting of IgG 1 , lgG2A, lgG2B, and lgG3. In a still further aspect, the murine constant region in lgG2A. In a still further specific aspect, the antibody has reduced or minimal effector function.

In a still further specific aspect the minimal effector function results from an“effector-less Fc mutation” or aglycosylation. In still a further aspect, the effector-less Fc mutation is an N297A or D265A/N297A substitution in the constant region.

In a still further aspect, provided is an isolated anti-PD-L1 antibody comprising a heavy chain and a light chain variable region sequence, wherein:

(a) the heavy chain sequence has at least 85% sequence identity to the heavy chain sequence:

EVQLVESGGGLVQPGGSLRLSCAASGFTFSDSWIHWVRQAPGKGLEWVAWISPYGGSTYYADSVKGR FTISADTSKNTAYLQMNSLRAEDTAVYYCARRHWPGGFDYWGQGTLVTVSSASTK (SEQ ID NO: 25), or

(b) the light chain sequences has at least 85% sequence identity to the light chain sequence: DIQMTQSPSSLSASVGDRVTITCRASQDVSTAVAWYQQKPGKAPKLLIYSASFLYSGVPSRFSGSGSGT DFTLTISSLQPEDFATYYCQQYLYHPATFGQGTKVEIKR (SEQ ID NO: 4). In some aspects, provided is an isolated anti-PD-L1 antibody comprising a heavy chain and a light chain variable region sequence, wherein the light chain variable region sequence has at least 85%, at least 86%, at least 87%, at least 88%, at least 89%, at least 90%, at least 91 %, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99% or 100% sequence identity to the amino acid sequence of SEQ ID NO: 4. In some aspects, provided is an isolated anti-PD-L1 antibody comprising a heavy chain and a light chain variable region sequence, wherein the heavy chain variable region sequence has at least 85%, at least 86%, at least 87%, at least 88%, at least 89%, at least 90%, at least 91 %, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99% or 100% sequence identity to the amino acid sequence of SEQ ID NO: 25. In some aspects, provided is an isolated anti-PD-L1 antibody comprising a heavy chain and a light chain variable region sequence, wherein the light chain variable region sequence has at least 85%, at least 86%, at least 87%, at least 88%, at least 89%, at least 90%, at least 91 %, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% sequence identity to the amino acid sequence of SEQ ID NO: 4 and the heavy chain variable region sequence has at least 85%, at least 86%, at least 87%, at least 88%, at least 89%, at least 90%, at least 91 %, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% sequence identity to the amino acid sequence of SEQ ID NO: 25. In some aspects, one, two, three, four, or five amino acid residues at the N-terminal of the heavy and/or light chain may be deleted, substituted or modified.

In a still further aspect, provided is an isolated anti-PD-L1 antibody comprising a heavy chain and a light chain sequence, wherein:

EVQLVESGGGLVQPGGSLRLSCAASGFTFSDSWIHWVRQAPGKGLEWVAWISPYGGSTYYADSVKGR

FTISADTSKNTAYLQMNSLRAEDTAVYYCARRHWPGGFDYWGQGTLVTVSSASTKGPSVFPLAPSSKST

SGGTAALGCLVKDYFPEPVTVSWNSGALTSGVHTFPAVLQSSGLYSLSSVVTVPSSSLGTQTYICNVNHK

PSNTKVDKKVEPKSCDKTHTCPPCPAPELLGGPSVFLFPPKPKDTLMISRTPEVTCVVVDVSHEDPEVKF

NWYVDGVEVHNAKTKPREEQYASTYRVVSVLTVLHQDWLNGKEYKCKVSNKALPAPIEKTISKAKGQPR

EPQVYTLPPSREEMTKNQVSLTCLVKGFYPSDIAVEWESNGQPENNYKTTPPVLDSDGSFFLYSKLTVD

KSRWQQGNVFSCSVMHEALHNHYTQKSLSLSPG (SEQ ID NO: 30), and/or

(b) the light chain sequences has at least 85% sequence identity to the light chain sequence: DIQMTQSPSSLSASVGDRVTITCRASQDVSTAVAWYQQKPGKAPKLLIYSASFLYSGVPSRFSGSGSGT DFTLTISSLQPEDFATYYCQQYLYHPATFGQGTKVEIKRTVAAPSVFIFPPSDEQLKSGTASVVCLLNNFY PREAKVQWKVDNALQSGNSQESVTEQDSKDSTYSLSSTLTLSKADYEKHKVYACEVTHQGLSSPVTKSF NRGEC (SEQ ID NO: 31 ).

In some aspects, provided is an isolated anti-PD-L1 antibody comprising a heavy chain and a light chain sequence, wherein the light chain sequence has at least 85%, at least 86%, at least 87%, at least 88%, at least 89%, at least 90%, at least 91 %, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99% sequence identity to the amino acid sequence of SEQ ID NO: 31 . In some aspects, provided is an isolated anti-PD-L1 antibody comprising a heavy chain and a light chain sequence, wherein the heavy chain sequence has at least 85%, at least 86%, at least 87%, at least 88%, at least 89%, at least 90%, at least 91 %, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99% sequence identity to the amino acid sequence of SEQ ID NO: 30. In some aspects, provided is an isolated anti-PD-L1 antibody comprising a heavy chain and a light chain sequence, wherein the light chain sequence has at least 85%, at least 86%, at least 87%, at least 88%, at least 89%, at least 90%, at least 91 %, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99% sequence identity to the amino acid sequence of SEQ ID NO: 31 and the heavy chain sequence has at least 85%, at least 86%, at least 87%, at least 88%, at least 89%, at least 90%, at least 91 %, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99% sequence identity to the amino acid sequence of SEQ ID NO: 30.

In some aspects, the isolated anti-PD-L1 antibody is aglycosylated. Glycosylation of antibodies is typically either N-linked or O-linked. N-linked refers to the attachment of the carbohydrate moiety to the side chain of an asparagine residue. The tripeptide sequences asparagine-X-serine and asparagine-X- threonine, where X is any amino acid except proline, are the recognition sequences for enzymatic attachment of the carbohydrate moiety to the asparagine side chain. Thus, the presence of either of these tripeptide sequences in a polypeptide creates a potential glycosylation site. O-linked glycosylation refers to the attachment of one of the sugars N-aceylgalactosamine, galactose, or xylose to a

hydroxyamino acid, most commonly serine or threonine, although 5-hydroxyproline or 5-hydroxylysine may also be used. Removal of glycosylation sites form an antibody is conveniently accomplished by altering the amino acid sequence such that one of the above-described tripeptide sequences (for N-linked glycosylation sites) is removed. The alteration may be made by substitution of an asparagine, serine or threonine residue within the glycosylation site another amino acid residue (e.g., glycine, alanine or a conservative substitution).

In any of the aspects herein, the isolated anti-PD-L1 antibody can bind to a human PD-L1 , for example a human PD-L1 as shown in UniProtKB/Swiss-Prot Accession No.Q9NZQ7.1 , or a variant thereof.

In a still further aspect, provided is an isolated nucleic acid encoding any of the antibodies described herein. In some aspects, the nucleic acid further comprises a vector suitable for expression of the nucleic acid encoding any of the previously described anti-PD-L1 antibodies. In a still further specific aspect, the vector is in a host cell suitable for expression of the nucleic acid. In a still further specific aspect, the host cell is a eukaryotic cell or a prokaryotic cell. In a still further specific aspect, the eukaryotic cell is a mammalian cell, such as Chinese hamster ovary (CHO) cell.

The antibody or antigen binding fragment thereof, may be made using methods known in the art, for example, by a process comprising culturing a host cell containing nucleic acid encoding any of the previously described anti-PD-L1 antibodies or antigen-binding fragments in a form suitable for expression, under conditions suitable to produce such antibody or fragment, and recovering the antibody or fragment.

It is expressly contemplated that such PD-L1 axis binding antagonist antibodies (e.g., anti-PD-L1 antibodies, anti-PD-1 antibodies, and anti-PD-L2 antibodies), or other antibodies described herein for use in any of the aspects enumerated above may have any of the features, singly or in combination. In some aspects, the immune checkpoint inhibitor is an antagonist directed against a co-inhibitory molecule (e.g., a CTLA-4 antagonist (e.g., an anti-CTLA-4 antibody), a TIM-3 antagonist (e.g., an anti- TIM-3 antibody), or a LAG-3 antagonist (e.g., an anti-LAG-3 antibody)), or any combination thereof.

In some aspects, the immune checkpoint inhibitor is an antagonist directed against TIGIT (e.g., an anti- TIGIT antibody). Exemplary anti-TIG IT antibodies are described in US Patent Application Publication No. 2018/0186875 and in International Patent Application Publication No. WO 2017/053748, which are incorporated herein by reference in their entirety.

IV. EXAMPLES

The following are examples of methods and compositions of the invention. It is understood that various other aspects may be practiced, given the general description provided above, and the examples are not intended to limit the scope of the claims.

Example 1. AVANT study design and sample collection

A. A VANT study design

AVANT (ClinicalTrials.gov identifier NCT001 12918) was a randomized, open-label, prospective, parallel three-arm, phase 3 trial sponsored by F. Hoffmann-La Roche and conducted in accordance with the Declaration of Helsinki. The study design was published previously (de Gramont et al. , J Clin Oncol.,

18: 2938-2947, 2000). Patients (age > 18 years with histologically confirmed stage III or high-risk (as classified by the AJCC/UICC-TNM) stage II colon carcinoma) were subject to surgery with curative intent 4-8 weeks before initiation of one of three treatment options (randomized in a 1 :1 :1 ratio): oxaliplatin infusion added to Fluorocil and Leucovorin (FOLFOX4) for 24 weeks followed by observation for 24 weeks; bevacizumab - FOLFOX4 for 24 weeks followed by bevacizumab monotherapy for 24 weeks; or bevacizumab - oxaliplatin infusion added to capecitabine (XELOX) for 24 weeks followed by

bevacizumab monotherapy for 24 weeks. Stratification factors included geographic region and disease stage (high-risk stage II vs stage III [N1 ] vs stage III [N2]). Disease-free survival (DFS) was the primary endpoint, and was defined as the time between randomization and recurrence of the colorectal cancer, new occurrence of colorectal cancer, or death from any cause.

B. FFPE tumor samples

Baseline formalin-fixed, paraffin-embedded (FFPE) tumor samples were collected from patients who consented to participate in exploratory translational research. Samples with sufficient tissue were selected for further analysis. Of 3451 patients enrolled, 1256 had sufficient material for analysis. Tumors were microdissected to minimize the amount of adjacent normal tissue RNA included in the gene expression analysis. FFPE tissue blocks were sectioned at a thickness of 4 to 6 microns and stored on slides at room temperature. After RNA extraction, samples were stored at -70°C.

Clinical characteristics in the biomarker evaluable population (BEP) were similar to those in the intent-to-treat population, as shown in Table 3. Table 3. Clinical characteristics in the Intent-to-Treat Population by treatment arm and the Biomarker Evaluable Population

a: Analysis has been conducted on all treatment arms jointly

b: ECOG- Eastern Co-operative Oncology Group.

c: fluorouracil, leucovorin, and oxaliplatin.

d: capecitabine (Xeloda) plus oxaliplatin.

Patient numbers across disease stage do not add up to total Intent-to-Treat Population since 1 1 patients had diseases across stages (I, II, IV). Example 2. AVANT Gene Expression Analysis and MSI analysis

A. NANOSTRING ^® gene expression analysis

The AVANT trial did not show a significant DFS difference among the arms after a minimum of 3 years follow-up (Fig. 5B), and also did not show a significant OS difference among the arms (Fig. 5A). Therefore, we combined all arms in the BEP for the purpose of identifying a prognostic gene signature in early stage colorectal cancer (CRC). We carried out transcriptional analysis of the FFPE tissues using a customized, CRC-focused NANOSTRING^® panel (Table 4). RNA was extracted from the FFPE patient samples and run on a customized CRC codeset comprised of 829 genes on the NANOSTRING^® gene expression platform (NanoString Technologies, Seattle, WA). The raw probe intensities were corrected for background using blank (water), and then normalized using the NanostringQCPro package in R. Raw counts for 1256 tumor samples were log2 transformed, normalized (common mean and standard deviation for all samples), and gene-wise expression scores were further standardized across all samples by transformation to z-scores. Quality control failures were flagged based on the first principal component of normalized counts; 67 outlier samples were identified. These yielded low overall counts, indicating insufficient input material or another source of assay failure and were removed from further analysis. 12 patients had 2 samples each, all of which were excluded. 1 165 samples were deemed biomarker-evaluable samples. For 102 subjects for whom gene expression data was available, no matching clinical annotations were available. The samples from these subjects were excluded from downstream analysis, leaving a final total of 1062 samples.

B. Characterization of MSI , KRAS status. BRAF status, and CMS subtype

i. Gene expression-based assignment of published CMSs

The Cancer Genome Atlas (TCGA) RNAseq paired-end data for colon adenocarcinoma, breast carcinoma, lung adenocarcinoma and squamous carcinoma, head and neck squamous cell carcinoma, bladder carcinoma and ovarian carcinoma were downloaded from the National Cancer Institute Genomic Data Commons and analyzed using HTSeqGenie (Goldstein et al., Cell Rep, 16(10): 2605-2617, 2016). KRAS and BRAF mutation information for colon tumors was downloaded from cBioPortal for Cancer Genomics (project Colorectal Adenocarcinoma TCGA provisional) on 09/1 8/2018. The GSE39582 dataset was downloaded from Gene Expression Omnibus (GEO) (GEO accession: GSE39582) (Marisa et al., PLoS Med, 10: e1001453, 2013). RNAseq data for cell lines were obtained from Klijn et al., Nat Biotechnol, 33(3): 306-312, 2015). The random forest algorithm in the consensus molecular subtype (CMS) classifier R package (Guinney et al., Nat Med, 21 : 1350-1356, 2015) was used to assign CMS labels to TCGA, GSE39582 samples, and colon cell lines. Since the AVANT dataset is on a different platform, i.e. , NANOSTRING^®, we first trained a prediction analysis of microarrays (PAM) classifier on the TCGA CRC samples for the prediction of CMS, using expression of the 829 genes on the CRC

NANOSTRING^® panel and the pamr R package. The 132 genes highly predictive of the CMS subtypes in the TCGA subsetted dataset were then used to perform unsupervised hierarchical clustering and tree cutting to annotate the AVANT tumors. MSI, KRAS status, and BRAF status

Microsatellite instability (MSI), KRAS status, and BRAF status were obtained by qPCR. For our purposes, MSI-low and microsatellite stable (MSS) patients were merged into the MSS category.

BRAF status was assessed as the presence or absence of a c. 1799T>A nucleotide substitution mutation, e.g., a mutation resulting in a V600E mutation in the amino acid sequence of BRAF.

KRAS status was assessed as the presence or absence of at least one nucleotide substitution mutation resulting in a G12A, G12R, G12D, G12C, G12S, G12V, G12D, or G13D mutation in the amino acid sequence of KRAS, as described in Marisa et al ., PLoS Med, 10: e1 001453, 2013, Lievre et al ., J Clin Oncol, 26: 374-379, 2008, and Lievre et al., Cancer Res, 66(8): 3992-3995, 2006).

Hi. Comparison of A V ANT population to published datasets

The AVANT population was comparable to other early stage populations such as GSE39582 (Marisa et al., PLoS Med, 1 0: e1001453, 2013) and The Cancer Genome Atlas (TCGA) (Cancer Genome Atlas Network, Nature, 487: 330-337, 2012) in terms of prevalence of the four CMSs (Guinney et al., Nat. Med., 21 : 1350-1356, 2015), the predominant occurrence of microsatellite instability high (MSI-H) and BRAF mutations in the CMS1 group, and the predominant occurrence of KRAS mutations in the CMS3 group (Figs. 6A-6F and 7A-7F).

Example 3. Identification of a highly prognostic de novo gene signature

To interrogate the biological processes associated with survival in adjuvant CRC, we applied an elastic net Cox penalized regression model to the AVANT BEP NANOSTRING^® dataset to identify a gene signature associated with OS. We identified a highly prognostic de novo signature, referred to as the AVANT signature, where high expression of the signature conferred poor prognosis in AVANT for DFS and OS (Figs. 1 A and 17A). We validated the ability of this signature to identify a high-risk adjuvant CRC population in the independent GSE39582 cohort. We further compared the predictive ability of the AVANT signature to that of published prognostic signatures.

/^'. Prognostic signature analysis using elastic net regression

Using overall survival (OS) data from the AVANT BEP NANOSTRING^® dataset, we built a generalized Cox-regression model using the glmnet R package with alpha values of 0.1 -0.9 and seed reset in each run (Simon et al., J Stat Softw, 39: 1 -13, 201 1 ; Friedman et al., J Stat Softw, 33: 1 -22,

2010). Lower alpha values result in larger numbers of selected genes. All regression runs provided the same core set of genes that were significantly associated with OS. Additional genes were included at alpha values 0.3 and lower (Fig. 8). As a trade-off between being inclusive of novel biological functions beyond the core set of genes (lower alpha) and not including too many genes either (higher alpha), we settled on an alpha value of 0.2 to identify the AVANT gene signature.

/^'/^'. Validation of A VANT signature in an independent cohort

We next tested the AVANT signature's ability to identify a true high-risk adjuvant CRC population in an independent cohort. The independent cohort was the GSE39582 cohort of stage l-IV colon cancer (Marisa et al, PLoS Med 2013). For validation of the signature using the independent cohort

(GSE39582), we used the signs (positive or negative) of the coefficients for each gene of the AVANT signature to calculate an unweighted signature score per patient. Using the beta coefficients from the model to compute a weighted signature score per patient yielded similar results.

The AVANT signature accurately identified a high-risk adjuvant CRC population for recurrence- free survival (RFS) and OS in the GSE39582 cohort, thus validating the gene signature (Figs. 1 B and 17B).

Hi. Comparison of AV ANT signature to published prognostic signatures

The AVANT signature was significantly more effective at predicting survival, and thus at identifying a high-risk subpopulation, than other prognostic signatures (Oncotype Dx, T-effector, CAF, F- TBRS) (Calon et al. , Cancer Cell, 22: 571 -584, 2012; Bindea et al. , Immunity, 39: 782-795, 2013) and the molecular CMSs (Guinney et al., Nat Med, 21 : 1350-1356, 2015), not only in the AVANT population, as expected (Figs. 12 and 20), but more importantly in an independent dataset not selected to be high-risk (GSE39582; Marisa et al, PLoS Med 2013) (Figs. 1 G and 17F).

Notably, in the GSE39582 dataset, the AVANT signature conferred significant additional prognostic value when added to each of the previously published prognostic signatures we considered.

In contrast, the CMSs added prognostic value when combined with the AVANT signature; even here, adding CMS to the AVANT signature generated a less significant improvement than adding the AVANT signature to CMS subtype (Figs. 1 G and 17F). In addition, multivariate analysis of the AVANT signature with incorporation of clinical covariates that are prognostic in CRC (listed in Example 7) still showed prognostic value of the signature in AVANT as well as in the independent GSE39582 dataset (Figs. 13A- 13B and 21 A-21 B).

Example 4. Proliferative, stromal and immune signatures

Gene clustering revealed four clusters of genes in the AVANT signature that meaningfully capture three primary biological functions: stromal, proliferative, and immune signaling (Figs. 1 C, 9A-9I, and 10A- 10D). Although our elastic net approach integrated multiple biological functions by design, we were interested in their individual prognostic contributions. These findings indicate that both a tumor’s underlying biology and that of its microenvironment should be considered when managing early stage colon cancer.

/^'. Pathway and published signature analysis

Four gene clusters within the AVANT signature (proliferative signature, stromal signature, TGFp stromal signature, and immune signature; Fig. 1 C) were determined by correlation and hierarchical clustering analysis. Pathway signatures were obtained from literature: the T-effector signature

(Mariathasan et al., Nature, 554: 544-548, 2018), the natural killer cell (NK) signature (Crinier et al., Immunity, 49(5): 971 -986. e5, 2018; Mori et al., Int J Oncol, 12(5): 1 165-1 170, 1998; Victor et al., J Immunol, 200(2): 565-572, 2017), the plasmacytoid dendritic cell (pDC) signature (Cheng et al., Sci Rep, 5: 10752, 2015; Villani et al., Science, 356(6335): eaah4573, 2017), the stromal gene sets Fibroblast TGFb Response Signature (F-TBRS) (Calon et al. , Cancer Cell, 22: 571 -584, 2012) and cancer- associated fibroblast (CAF) signature (Isella et al., Nat Genet, 47: 312-319, 2015), and the 12-gene Oncotype Dx Colon Recurrence Score (Yamanaka et al., J Clin Oncol, 34(24): 2906-2913, 201 6).

Pathway signatures were calculated as the average Z-score of all the genes contained in each signature. In the context of GZMB, the T-effector signature was modified by removing GZMB and GZMA from the signature, which we refer to as the“modified T-effector” signature.

//^'. Proliferative signature

Genes in the proliferative signature are provided in Fig. 1 C and are as follows: RPL23, AXIN2, CDKN1B, DTX2, RPS6KA 1, KDM1A, RHOA, SP2, SHISA5, MLH1, CDCA5, E2F1, CENPM, CDK2, GMNN, and DNMT1. Expression of the proliferative genes did not associate significantly with DFS in the AVANT dataset (Fig. 1 D). In the GSE39582 dataset, the proliferative gene set was prognostic of RFS (Fig. 1 1 A). In both the AVANT dataset and the GSE39582 dataset, the proliferative gene set was prognostic of OS (Figs. 17C and 18A).

Hi. Stromal and TGFB stromal signature

Genes in the stromal and TGFp stromal signatures are provided in Fig. 1 C. Genes in the stromal signature are ANGPT1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, and FOS. Genes in the TGFp stromal signature are SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, and MAPK3. High expression of stromal genes (from the two stromal clusters) was correlated with lower DFS and OS in the AVANT dataset (Figs. 1 F and 1 7E). In the GSE39582 dataset, the stromal gene sets were prognostic of RFS (Fig. 1 1 C), but were not prognostic of OS (Fig. 18C). iv. Immune signature

Genes in the immune signature are provided in Fig. 1 C and are as follows: TP73, TAP1, GZMB, TNF, CXCL 1, PDCD1, FCRL5, CXCR4, and CD28. High expression of immune genes was correlated with higher DFS in the AVANT dataset (Fig. 1 E). Importantly, the association of immune gene expression with DFS was independent of MSI status (multivariate HR for the immune cluster = 0.68, p 0.013), even though the immune gene set was significantly more highly expressed in MSI-H patients (Fig. 10B). The immune gene signature was not prognostic of OS in the AVANT dataset (Fig. 17D).

In the GSE39582 dataset, the immune gene set was not prognostic of RFS or OS (Figs. 1 1 B and

18B).

Example 5. Prognostic implications of GZMB

Despite the broad therapeutic benefit of checkpoint inhibitor treatment across a variety of solid tumor indications, including MSI-high CRC (Overman et al., J. Clin. Oncol., 36: 773-779, 2018), checkpoint inhibitors have demonstrated little activity in MSS CRC tumors. We were therefore surprised to find a cluster of immune-related genes that are prognostic in MSS CRC tumors (Example 4/V).

It is well known that Perforin-, Granzyme A (GZMA)-, and Granzyme B (GZMB)-dependent cytolytic function is acquired during differentiation of naive CD8+ T cells into CD8+ T-effector cells in response to antigenic stimulation (Wherry et al Immunity, 27: 670-684, 2007; Hyrcza et al., J. Virol., 81 , 3477-3486, 2007; Wendt et al., J. Leucoc. Biol., 80, 1 529-1541 , 2006; Chtanova et al., J. Immunol., 175: 7837-7847, 2005; Doering et al., Immunity, 37: 1 130-1 144, 2012; Haining et al., J. Immunol., 181 : 1859- 1868, 2008). Importantly, several clinical studies have shown that high levels of baseline T-effector signatures correlate with improved outcome in patients treated with an immune checkpoint inhibitor (Mariathasan et al., Nature, 554: 544-548, 2018; McDermott et al., Nat. Med., 24: 749-757, 201 8), thus suggesting that immune checkpoint inhibitor activity requires pre-existent tumor T-effector immunity.

/^'. Prognostic implication of GZMB as a singleton

Given the evidence for a role of CD8+ T cells in early disease prognosis in CRC (Galon et al., Science, 313: 1960-1964, 2006; Zhang et al., N. Engl. J. Med., 348: 203-213, 2003; Fridman et al., Nat. Rev. Cancer, 12: 298-306, 2012; Nielsen et al., Clin. Cancer Res., 18: 3281 -3292, 2012) and the fact that GZMB, a key marker of T-effector cells, is part of our AVANT signature (Fig. 1 C), we explored the prognostic implication of GZMB as a singleton versus a CD8+ T-effector signature (Mariathasan et al., Nature, 554: 544-548, 2018) in the AVANT and GSE39582 studies.

Surprisingly, GZMB alone had a significant impact on prognosis: high expression of GZMB was associated with good prognosis in both the AVANT and GSE39582 datasets (Figs. 2A- 2B and 1 9A-19B). The T-effector signature as a whole with GZMB included (Figs. 2C-2D and 19C-19D) or individual T- effector genes were either not prognostic or were less prognostic than GZMB, and the T-effector signature without GZMB added no statistically prognostic value beyond that provided by GZMB alone (Figs. 2E- 2F and 19E-19F).

/^'/^'. Prognostic implication of GZMB with stromal and proliferative signatures

We next investigated the prognostic value of GZMB in the context of the stromal and proliferative biological functions captured by the AVANT signature. GZMB significantly added prognostic value to the proliferative and stromal gene sets (Figs. 2G- 2J and 1 9G-19J; likelihood ratio test for improvement of fit adding GZMB expression to the stromal set, p 4.1 e-5 or the proliferative set, p 1 .4e-5). In other words, concurrent high expression of GZMB and the proliferative gene set was associated with good prognosis in AVANT and GSE38592 (Figs. 2G-2H and 19G-1 9H). However, this benefit was lost in patients with a high proliferative gene set but low GZMB expression (Figs. 2G-2H and 19G-19H). Similarly, high expression of the stromal gene set with low GZMB had the poorest prognosis in both cohorts (Figs. 2I-2J and 191-1 9J). Yet, tumors with concurrent high stromal and GZMB expression were associated with better outcome despite the stromal gene set on its own being associated with poor survival (Figs. 2I-2J and 191-1 9J). The same was true for the prognostic impact of GZMB expression among tumors with a low stromal score. These results indicate that high expression of GZMB by itself is consistently associated with favorable outcomes, independent of the proliferative and stromal context.

Hi. GZMB expression in patient populations

Given the significant impact of this single gene on clinical outcome, we investigated how GZMB expression relates to established sources of patient heterogeneity in CRC. As expected the T-effector signature, including GZMB, was most highly expressed in CMS1 and MSI-H patients (Fig. 3A-3C). In CMS1 CRC patients and in all other cancer types considered, T-effector signature genes were highly correlated in expression (Fig. 3D). In contrast, GZMB was additionally expressed in CMS2 patients and in a fraction of MSS patients (Figs. 3E-3G). In CMS2 CRC patients, GZMB expression correlated poorly with the other T-effector signature genes (Fig. 3D), suggesting that its relevance and source may not be CD8+T cells in this subset of patients. In other words, while other T-effector genes— including GZMA— maintained their strong positive correlation across CMS subtypes and in both MSI-H and MSS CRC patients, GZMB was strongly correlated with the T-effector signature only in the CMS1 subtype and in MSI-H CRC patients (Fig. 3I). To ensure this was not an anomaly in AVANT, we confirmed these findings in the GSE39582 dataset (Figs. 3B, 3F, and 3J). Furthermore, GZMB expression is prognostic in CMS2 tumors (Figs. 3H and 14). Taken together, these data suggest that, while CD8+ T cells are a major source of GZMB in CMS1 and MSI-H patients, other cell types may be the source of GZMB in CMS2 patients.

Example 6. Identification of cell types expressing GZMB

To identify cell types that express GZMB, we conducted mass cytometry analysis in 12 procured, resected stage II or III CRC tumors using a comprehensive panel of 37 lineage and functional markers of immune populations (Tables 5 and 6).

To identify cell populations that express GZMB in an unbiased manner, we applied t-distributed stochastic neighbor embedding (tSNE) analysis on the CD45+ viable singlet gated immune cell populations from all 12 CRC patients combined, followed by unsupervised density-based clustering (Fig. 4A). The markers that helped define each of the immune populations in the tSNE map are shown in Fig. 15A.

Disaggregated CRC tumor samples (stage II or III, pre-treated) were procured from an external vendor (Conversant Bio) and analyzed by mass cytometry as previously described (Takahashi et al ., Cytometry A, 91 (1 ), 39-47, 2016). In short, CRC single-cell suspensions were incubated with a cisplatin- based viability dye (Fluidigm) and Human TRUSTAIN FCX™ block (Biolegend) prior to staining with a 37 parameter isotope conjugated panel of monoclonal antibodies (mABs) (see Tables 5 and 6 for clones and vendors). Initial staining of cell surface markers was conducted on live cells, and intracellular targets were probed following fixation and permeabilization with the Human Foxp3 Staining Buffer Set

(eBioscience). Following intracellular staining, cells were fixed with 1 .6% paraformaldehyde (Electron Microscopy Sciences) and treated with CELL-ID™ Intercalator (Fluidigm). Cells were resuspended in water containing EQ™ Calibration Beads prior to acquisition on a Helios upgraded CyTOF 2 Mass Cytometer (Fluidigm). Signal normalization was conducted as previously described (Finck et al., Cytometry A, 83(5): 483-494, 2013).

For each sample, CD45+ viable singlet cells were exported into new .FCS files using FlowJo software. Using 37 immune markers (excluding pan-markers like EPCAM and CD45; markers with broad signal like CD66 and Foxp3) and singlet viable CD45+ populations across the 12 CRC patients, the tSNE dimensionality reduction algorithm (adjClust package) was used to obtain the tSNE map shown in Fig.

4A. Density-based spatial clustering of applications with noise (DBSCAN) via the DBSCAN package (downloaded from The Comprehensive R Archive Network) and literature-based knowledge was used to annotate the clusters in the tSNE space. The average of each protein marker was calculated per immune cell type for correlation analysis and heatmaps. In fluorescence-based cytometry experiments, fresh healthy human peripheral blood mononuclear cells (PBMCs) were procured from the Genentech Blood Donors program and processed with a similar protocol as that used for mass cytometry with the exception that fluorophore conjugated mABs were used and data were acquired on a BD FACS Canto II instrument (BD Biosciences).

The prevalence of the distinct immune cell populations highly varied in these CRC patients: B cells and CD4+ T cells were most prevalent, followed by CD8+ T cells and monocytes (Fig. 15B). Novel cell types found to express more GZMB than GZMA were CD1 6+ natural killer (NK) cells and plasmacytoid dendritic cells (pDCs) (Fig. 1 5A). These cell types concordantly had low CD8 expression (Figs. 4B- 4C). These data suggest that infiltration from multiple cell types beyond T-effector cells, namely, CD16+ NK cells and pDCs, contribute to total GZMB expression in the 12 CRC patients, and this is consistent with an earlier observation of GZMB expression by the above cell types in the absence of detectable Perforin (Hagn et al. , J. Immunol ., 183: 1 838-1845, 2009; Rissoan et al ., Blood, 100: 3295- 3303, 2002; Facchetti et al., A. J. Surg. Pathol., 27: 1489-1492; author reply 1492-1493 (2003); Cao et al., J. Am. Soc. Nephrol., 27: 1344-1360, 2016).

Next, we sought to confirm that the GZMB signal in CMS2 CRC patients comes from pDCs and CD16+ NK cells. However, GZMB expression strongly correlated with transcriptional signatures of NK and pDC cells, in all cancers except for CRC CMS2 (Figs. 4D and 15C), similar to our observation for the T-effector signature (Fig. 3D). Furthermore, expression of the NK signature was restricted to CMS1 tumors, and the pDC signature was not expressed in CMS2 tumors from the GSE39582 cohort (Figs. 4E and 15D). These results suggest that T-effector cells, NK cells, and pDCs are a source of GZMB expression in CMS1 tumors, but not in CMS2 tumors.

As we extensively profiled immune cell populations in Fig. 4A, these findings led us to hypothesize that the source of GZMB expression in CMS2 tumors is endogenous. Indeed, in a cohort of 72 colon cancer cell lines, GZMB is primarily expressed in CMS2 cell lines (Fig. 4F). On the contrary, GZMA is not expressed in the colon cancer cell lines (Fig. 15E), supporting the hypothesis that GZMB is produced by tumor cells in CMS2 tumors, while GZMB, similar to GZMA, is produced by immune cells in CMS1 tumors. Here, we show across a cell line panel covering 12 cancer types that CMS2 CRC and melanoma are the only tumor cells that express GZMB (Figs. 4F and 16A-16B). As a potent extracellular matrix (ECM) remodeling agent, GZMB efficiently cleaves vitronectin, fibronectin, and laminin. GZMB pretreatment of a laminin matrix significantly inhibited cell spreading of colon cancer cell line LIM1215 in vitro (Buzza et al., J. Biol. Chem., 280: 23549-23558, 2005). Thus, via disruption of integrin-dependent adhesion, GZMB has been shown to inhibit tumor cell spreading, migration, and invasion on ECM, thereby potentially inhibiting tumorigenesis. Beyond the relevance to the matrix, the impact of GZMB expression on invasion varied across a panel of CRC cell lines in the same matrix (D’Eliseo et al., J. Exp. Clin. Cancer Res., 35: 24, 2016), indicating interference from additional factors. Here, we identified the CMS2 subtype as one context in which GZMB plays a non-cytolytic role, established in both CRC cell lines and multiple, independent cohorts of CRC tissues. GZMB' s putative role in inhibiting tumorigenesis is consistent with our observation that endogenous GZMB expression associates with favorable outcome in adjuvant CRC (Figs. 3H and 14). The fact that we observe endogenous GZMB in CMS2 CRC and melanoma cell lines, the latter which extends beyond the previously established contribution of GZMB in keratinocytes to skin pathogenesis (Turner et al. , Matrix Biol., 75-76: 126-140, 2019), emphasizes the need for new research on GZMB function in tumors.

Example 7. Statistical Analysis

Survival analysis with Cox models for genes and pathway signatures were performed in R using the survival package with either continuous values, binarized at median (high vs low expression) or cut into quartiles. Kaplan-Meier curves were generated using the survminer package in R. To test the additive effect of GZMB expression to the gene subsets of the AVANT signature, likelihood ratio test p values were calculated using ANOVA on nested models. Multivariate analysis in AVANT was performed by adding the clinical covariates age, levels of Cancer Embryonic Antigen (CEA) in the blood, Eastern Cooperative Oncology Group (ECOG) status, sex, and a combination of American Joint Committee on Cancer (AJCC) tumor status (II and III) and lymph node status (N1 and N2), referred to as strata. These covariates were individually found to be prognostic in both overall survival (OS) and DFS. Multivariate analysis in GSE39582 was performed by adding the clinical covariates age, sex, tumor stage (0-4), and lymph node status. These covariates were individually found to be prognostic in both OS and recurence- free survival (RFS). Note that in GSE39582, we did not have data for ECOG status and CEA blood levels. In GSE39582, the type of adjuvant therapy as well as stage of metastasis were also prognostic clinical covariates. Including them into the multivariate analysis for the AVANT signature yielded similar results as above, hence they were excluded from the model for consistency with the covariates in the AVANT dataset. Correlation plots were generated using the corrplot R package. Pairwise T-test was used to compute nominal p-values displayed in the insert tables for boxplots. Chi-square test was used to compute the enrichment of clinical characteristics in CMS subtypes in Fig. 7A-7I. Most plots were generated using the ggplot2 R package.

Table 4. Overview of the customized NANOSTRING^® panel with 829 CRC-associated genes, 7 negative controls, and 6 positive controls

Table 5. Overview of clones and vendors of a 37 parameter isotope conjugated panel of monoclonal antibodies for lineage and functional markers of immune populations

Table 6. Overview of clones and vendors of a 37 parameter isotope conjugated panel of monoclonal antibodies for lineage and functional markers of immune populations

Although the foregoing invention has been described in some detail by way of illustration and example for purposes of clarity of understanding, the descriptions and examples should not be construed as limiting the scope of the invention. The disclosures of all patent and scientific literature cited herein are expressly incorporated in their entirety by reference.

Claims

WHAT IS CLAIMED IS:

1 . A method of predicting disease progression in an individual having a colorectal cancer (CRC), the method comprising determining an AVANT score from a sample from the individual, wherein an AVANT score that is above a reference AVANT score identifies the individual as one who is at high risk of CRC recurrence following surgical resection.

2. A method of predicting disease recurrence in an individual who has had surgical resection of a CRC, the method comprising determining an AVANT score from a sample from the individual, wherein an AVANT score that is above a reference AVANT score indicates that the individual is at high risk of CRC recurrence.

3. The method of claim 1 or 2, wherein the AVANT score determined from the sample is above the reference AVANT score, and the method further comprises administering to the individual an adjuvant treatment comprising a chemotherapy.

4. The method of any one of claims 1 -3, wherein the AVANT score is calculated based on the expression levels of CDCA5, DTX2, E2F1, GMNN, KDM1A, ABCC9, CRYAB, DTX1, HEYL, RGS2,

SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, TCF12, CD28, CXCL 1, and GZMB.

5. The method of claim 4, wherein the AVANT score is calculated based on the expression levels of CDCA5, DTX2, E2F1, GMNN, KDM1A, ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, TCF12, CD28, CXCL 1, GZMB, RPLN23, AXIN2, CDKN1B, RPS6KA 1, RHOA, SP2, SHISA5, MLH1, CENPM, CDK2, DNMT1, ANGPT1, IGFBP3, CD36, HBEGF, FOS, SERPINB13, APCDD1, SCD5, POU5F1, EPHA4, FLT1, CDK6, MAPK3, TP73, TAP1,

TNF, PDCD 1, FCRL5, and CXCR4.

6. The method of any one of claims 1 -5, further comprising determining a consensus molecular subtype (CMS) of the sample from the individual.

7. The method of claim 6, wherein the AVANT score determined from the sample is above the reference AVANT score and the CMS of the sample is CMS4.

8. The method of any one of claims 1 -7, wherein the reference AVANT score is a score in a reference population of individuals who have had surgical resection of a CRC.

9. The method of claim 8, wherein the reference population of individuals has been administered an adjuvant treatment comprising a chemotherapy.

10. The method of claim 9, wherein the sample is obtained from the individual prior to the administration of any adjuvant treatment.

1 1 . The method of any one of claims 1 -10, wherein the reference AVANT score significantly separates a first and a second subset of individuals based on responsiveness to treatment.

12. The method of claim 1 1 , wherein responsiveness to treatment is an increase in disease-free survival (DFS), recurrence-free survival (RFS), or overall survival (OS).

13. The method of any one of claims 1 -12, wherein the reference AVANT score is a pre-assigned score.

14. The method of any one of claims 1 -13, wherein the reference AVANT score is the 25^th percentile of AVANT scores in the reference population.

15. The method of any one of claims 1 -13, wherein the reference AVANT score is the 50^th percentile of AVANT scores in the reference population.

16. The method of any one of claims 1 -13, wherein the reference AVANT score is the 75^th percentile of AVANT scores in the reference population.

17. A method of predicting disease progression in an individual having a CRC, the method comprising determining an AVANT stromal score and the expression level of GZMB in a sample from the individual, wherein an AVANT stromal score that is above a reference AVANT stromal score and an expression level of GZMB that is below a reference expression level of GZMB identifies the individual as one who is at a high risk of CRC recurrence following surgical resection.

18. A method of predicting disease recurrence in an individual who has had surgical resection of a CRC, the method comprising determining an AVANT stromal score and the expression level of GZMB in a sample from the individual, wherein an AVANT stromal score that is above a reference AVANT stromal score and an expression level of GZMB that is below a reference expression level of GZMB indicates that the individual is at high risk of CRC recurrence.

19. The method of claim 17 or 18, wherein the AVANT stromal score is above a reference AVANT stromal score and the expression level of GZMB is below a reference expression level of GZMB, and the method further comprises administering to the individual an adjuvant treatment comprising a

chemotherapy.

20. The method of claim 17 or 18, wherein an AVANT stromal score that is below a reference AVANT stromal score and an expression level of GZMB that is above a reference expression level of GZMB identifies the individual as one who is at low risk of CRC recurrence following surgical resection.

21 . The method of any one of claims 17-20, further comprising determining a CMS of the sample from the individual.

22. The method of claim 21 , wherein the AVANT stromal score determined from the sample is above the reference AVANT stromal score and the CMS of the sample is CMS4.

23. The method of any one of claims 17-22, wherein the AVANT stromal score is calculated based on the expression levels of ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12.

24. The method of claim 23, wherein the AVANT stromal score is calculated based on the expression levels of ANGPT1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, and MAPK3.

25. The method of any one of claims 17-24, wherein the reference AVANT stromal score is a score in a reference population of individuals who have had surgical resection of a CRC.

26. The method of claim 25, wherein the reference population of individuals has been administered an adjuvant treatment comprising a chemotherapy.

27. The method of claim 26, wherein the sample is obtained from the individual prior to the administration of any adjuvant treatment.

28. The method of any one of claims 17-27, wherein the reference AVANT stromal score significantly separates a first and a second subset of individuals based on responsiveness to treatment.

29. The method of claim 28, wherein responsiveness to treatment is an increase in DFS, RFS, or OS.

30. The method of any one of claims 17-29, wherein the reference AVANT stromal score is a pre assigned score.

31 . The method of any one of claims 17-30, wherein the reference AVANT stromal score is the median AVANT stromal score in the reference population.

32. The method of any one of claims 17-31 , wherein the reference expression level of GZMB is a pre-assigned expression level.

33. The method of any one of claims 17-32, wherein the reference expression level of GZMB is the median expression level of GZMB in the reference population.

34. A method of treating an individual having a CRC, the method comprising:

(a) determining an AVANT score from a sample from the individual, wherein the AVANT score is above a reference AVANT score; and

(b) administering to the individual an adjuvant treatment comprising a chemotherapy.

35. A method of treating an individual having a CRC, the method comprising administering an adjuvant treatment comprising a chemotherapy to the individual, for whom an AVANT score from a sample from the individual has been determined to be above a reference AVANT score.

36. The method of claim 34 or 35, wherein the AVANT score is calculated based on the expression levels of CDCA5, DTX2, E2F1, GMNN, KDM1A, ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, TCF12, CD28, CXCL 1, and GZMB.

37. The method of claim 36, wherein the AVANT score is calculated based on the expression levels of CDCA5, DTX2, E2F1, GMNN, KDM1A, ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1,

WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, TCF12, CD28, CXCL 1, GZMB, RPLN23, AXIN2, CDKN1B, RPS6KA 1, RHOA, SP2, SHISA5, MLH1, CENPM, CDK2, DNMT1, ANGPT1, IGFBP3, CD36, HBEGF, FOS, SERPINB13, APCDD1, SCD5, POU5F1, EPHA4, FLT1, CDK6, MAPK3, TP73, TAP1, TNF, PDCD1, FCRL5, and CXCR4.

38. The method of any one of claims 34-37, further comprising determining a consensus molecular subtype (CMS) of the sample from the individual.

39. The method of claim 38, wherein the CMS of the CRC is CMS4.

40. The method of any one of claims 34-39, wherein the reference AVANT score is a score in a reference population of individuals who have had surgical resection of a CRC.

41 . The method of claim 40, wherein the reference population of individuals has been administered an adjuvant treatment comprising a chemotherapy.

42. The method of claim 41 , wherein the sample is obtained from the individual prior to the administration of any adjuvant treatment.

43. The method of any one of claims 34-42, wherein the reference AVANT score significantly separates a first and a second subset of individuals based on responsiveness to treatment.

44. The method of claim 43, wherein responsiveness to treatment is an increase in disease-free survival (DFS), recurrence-free survival (RFS), or overall survival (OS).

45. The method of any one of claims 34-44, wherein the reference AVANT score is a pre-assigned score.

46. The method of any one of claims 34-45, wherein the reference AVANT score is the 25^th percentile of AVANT scores in the reference population.

47. The method of any one of claims 34-45, wherein the reference AVANT score is the 50^th percentile of AVANT scores in the reference population.

48. The method of any one of claims 34-45, wherein the reference AVANT score is the 75^th percentile of AVANT scores in the reference population.

49. A method of treating an individual having a CRC, the method comprising:

(a) determining an AVANT stromal score and the expression level of GZMB in a sample from the individual, wherein the AVANT stromal score is above a reference AVANT stromal score and the expression level of GZMB is below a reference expression level of GZMB ; and

50. A method of treating an individual having a CRC, the method comprising administering an adjuvant treatment comprising a chemotherapy to the individual, for whom an AVANT stromal score from a sample from the individual has been determined to be above a reference AVANT stromal score and an expression level of GZMB has been determined to be below a reference expression level of GZMB.

51 . The method of claim 49 or 50, further comprising determining a CMS of the sample from the individual.

52. The method of claim 51 , wherein the CMS of the sample is CMS4.

53. The method of any one of claims 49-52, wherein the AVANT stromal score is calculated based on the expression levels of ABCC9, CRYAB, DTX1, HEYL, RGS2, SPP1, TLL 1, WBSCR17, IGFBP1, KDM5D, PCSK1, REG4, SMAD3, SMAD9, and TCF12.

54. The method of claim 53, wherein the AVANT stromal score is calculated based on the expression levels of ANGPT1, WBSCR17, TLL 1, CRYAB, ABCC9, IGFBP3, HEYL, DTX1, CD36, SPP1, RGS2, HBEGF, FOS, SERPINB13, IGFBP1, APCDD1, SCD5, KDM5D, POU5F1, EPHA4, REG4, PCSK1, SMAD9, FLT1, TCF12, SMAD3, CDK6, and MAPK3.

55. The method of any one of claims 49-54, wherein the reference AVANT stromal score is a score in a reference population of individuals who have had surgical resection of a CRC.

56. The method of claim 55, wherein the reference population of individuals has been administered an adjuvant treatment comprising a chemotherapy.

57. The method of claim 56, wherein the sample is obtained from the individual prior to the administration of any adjuvant treatment.

58. The method of any one of claims 49-57, wherein the reference AVANT stromal score significantly separates a first and a second subset of individuals based on responsiveness to treatment.

59. The method of claim 58, wherein responsiveness to treatment is an increase in DFS, RFS, or OS.

60. The method of any one of claims 49-59, wherein the reference AVANT stromal score is a pre assigned score.

61 . The method of any one of claims 49-60, wherein the reference AVANT stromal score is the median AVANT stromal score in the reference population.

62. The method of any one of claims 49-61 , wherein the reference expression level of GZMB is a pre-assigned expression level.

63. The method of any one of claims 49-62, wherein the reference expression level of GZMB is the median expression level of GZMB in the reference population.

64. The method of any one of claims 1 -63, wherein the sample is a tissue biopsy, a whole blood sample, a buccal swab, a plasma sample, a serum sample, or a combination thereof.

65. The method of claim 64, wherein the sample is a tissue biopsy.

66. The method of claim 64 or 65, wherein the sample is an archival sample, a fresh sample, or a frozen sample.

67. The method of any one of claims 64-66, wherein the sample is a formalin-fixed paraffin- embedded sample.

68. The method of any one of claims 1 -67, wherein the expression level is a nucleic acid expression level.

69. The method of claim 68, wherein the nucleic acid expression level is a mFtNA expression level.

70. The method of claim 69, wherein the mFtNA expression level is determined by direct digital counting of nucleic acids, RNA-seq, RT-qPCR, qPCR, multiplex qPCR or RT-qPCR, microarray analysis, or a combination thereof.

71 . The method of claim 70, wherein the digital counting of nucleic acids is by NANOSTRING^® NCOUNTER^® analysis.

72. The method of any one of claims 1 -71 , wherein the expression level is a protein expression level.

73. The method of claim 72, wherein the protein expression level is determined by an immunoassay, liquid chromatography-mass spectrometry (LC-MS) technology, nephelometry, aptamer technology, or a combination thereof.

74. The method of any one of claims 1 -73, wherein the CRC is a stage I, stage II, or stage III CRC according to the TNM classification system at the onset of treatment.

75. The method of any one of claims 3, 9, 1 0, 19, 26, 27, and 34-63, wherein the chemotherapy comprises oxaliplatin, fluorouracil, or leucovorin.

76. The method of claim 75, wherein the chemotherapy comprises oxaliplatin, fluorouracil, and leucovorin.

77. The method of claim 76, wherein the chemotherapy consists of oxaliplatin, fluorouracil, and leucovorin.

78. The method of any one of claims 3, 9, 1 0, 19, 26, 27, and 34-63, wherein the chemotherapy comprises oxaliplatin and capecitabine.

79. The method of claim 78, wherein the chemotherapy consists of oxaliplatin and capecitabine.

80. The method of any one of claims 3, 9, 1 0, 19, 26, 27, 34-63, and 75-79, wherein the adjuvant treatment further comprises bevacizumab.

81 . The method of any one of claims 3, 9, 1 0, 19, 26, 27, 34-63, and 75-80, wherein the method further comprises administering to the individual one or more additional therapeutic agents.

82. The method of claim 81 , wherein the one or more additional therapeutic agents comprise an immunomodulatory agent.

83. The method of claim 82, wherein the immunomodulatory agent is a PD-1 axis binding antagonist.

84. The method of claim 83, wherein the PD-1 axis binding antagonist is a PD-L1 binding antagonist, a PD-1 binding antagonist, or a PD-L2 binding antagonist.

85. The method of claim 84, wherein the PD-1 axis binding antagonist is a PD-L1 binding antagonist.

86. The method of claim 85, wherein the PD-L1 binding antagonist is MPDL3280A (atezolizumab), YW243.55.S70, MDX-1 105, MEDI4736 (durvalumab), or MSB0010718C (avelumab).

87. The method of claim 86, wherein the PD-L1 binding antagonist is MPDL3280A (atezolizumab).

88. The method of claim 84, wherein the PD-1 axis binding antagonist is a PD-1 binding antagonist.

89. The method of claim 88, wherein the PD-1 binding antagonist is MDX-1 106 (nivolumab), MK- 3475 (pembrolizumab), MEDI-0680 (AMP-514), PDR001 , REGN2810, or BGB-108.

90. The method of claim 84, wherein the PD-1 axis binding antagonist is a PD-L2 binding antagonist.

91 . The method of claim 90, wherein the PD-L2 binding antagonist is an antibody or an

immunoadhesin.

92. The method of any one of claims 1 -91 , wherein the individual is a human.