Pathway level subtyping identifies a slow-cycling biological phenotype associated with poor clinical outcomes in colorectal cancer.

Molecular stratification using gene-level transcriptional data has identified subtypes with distinctive genotypic and phenotypic traits, as exemplified by the consensus molecular subtypes (CMS) in colorectal cancer (CRC). Here, rather than gene-level data, we make use of gene ontology and biological activation state information for initial molecular class discovery. In doing so, we defined three pathway-derived subtypes (PDS) in CRC: PDS1 tumors, which are canonical/LGR5+ stem-rich, highly proliferative and display good prognosis; PDS2 tumors, which are regenerative/ANXA1+ stem-rich, with elevated stromal and immune tumor microenvironmental lineages; and PDS3 tumors, which represent a previously overlooked slow-cycling subset of tumors within CMS2 with reduced stem populations and increased differentiated lineages, particularly enterocytes and enteroendocrine cells, yet display the worst prognosis in locally advanced disease. These PDS3 phenotypic traits are evident across numerous bulk and single-cell datasets, and demark a series of subtle biological states that are currently under-represented in pre-clinical models and are not identified using existing subtyping classifiers.

MmCMS: mouse models' consensus molecular subtypes of colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) primary tumours are molecularly classified into four consensus molecular subtypes (CMS1-4). Genetically engineered mouse models aim to faithfully mimic the complexity of human cancers and, when appropriately aligned, represent ideal pre-clinical systems to test new drug treatments. Despite its importance, dual-species classification has been limited by the lack of a reliable approach. Here we utilise, develop and test a set of options for human-to-mouse CMS classifications of CRC tissue. METHODS: Using transcriptional data from established collections of CRC tumours, including human (TCGA cohort; n = 577) and mouse (n = 57 across n = 8 genotypes) tumours with combinations of random forest and nearest template prediction algorithms, alongside gene ontology collections, we comprehensively assess the performance of a suite of new dual-species classifiers. RESULTS: We developed three approaches: MmCMS-A; a gene-level classifier, MmCMS-B; an ontology-level approach and MmCMS-C; a combined pathway system encompassing multiple biological and histological signalling cascades. Although all options could identify tumours associated with stromal-rich CMS4-like biology, MmCMS-A was unable to accurately classify the biology underpinning epithelial-like subtypes (CMS2/3) in mouse tumours. CONCLUSIONS: When applying human-based transcriptional classifiers to mouse tumour data, a pathway-level classifier, rather than an individual gene-level system, is optimal. Our R package enables researchers to select suitable mouse models of human CRC subtype for their experimental testing.

Biological Misinterpretation of Transcriptional Signatures in Tumor Samples Can Unknowingly Undermine Mechanistic Understanding and Faithful Alignment with Preclinical Data.

PURPOSE: Precise mechanism-based gene expression signatures (GES) have been developed in appropriate in vitro and in vivo model systems, to identify important cancer-related signaling processes. However, some GESs originally developed to represent specific disease processes, primarily with an epithelial cell focus, are being applied to heterogeneous tumor samples where the expression of the genes in the signature may no longer be epithelial-specific. Therefore, unknowingly, even small changes in tumor stroma percentage can directly influence GESs, undermining the intended mechanistic signaling. EXPERIMENTAL DESIGN: Using colorectal cancer as an exemplar, we deployed numerous orthogonal profiling methodologies, including laser capture microdissection, flow cytometry, bulk and multiregional biopsy clinical samples, single-cell RNA sequencing and finally spatial transcriptomics, to perform a comprehensive assessment of the potential for the most widely used GESs to be influenced, or confounded, by stromal content in tumor tissue. To complement this work, we generated a freely-available resource, ConfoundR; https://confoundr.qub.ac.uk/, that enables users to test the extent of stromal influence on an unlimited number of the genes/signatures simultaneously across colorectal, breast, pancreatic, ovarian and prostate cancer datasets. RESULTS: Findings presented here demonstrate the clear potential for misinterpretation of the meaning of GESs, due to widespread stromal influences, which in-turn can undermine faithful alignment between clinical samples and preclinical data/models, particularly cell lines and organoids, or tumor models not fully recapitulating the stromal and immune microenvironment. CONCLUSIONS: Efforts to faithfully align preclinical models of disease using phenotypically-designed GESs must ensure that the signatures themselves remain representative of the same biology when applied to clinical samples.

Activation of innate-adaptive immune machinery by poly(I:C) exposes a therapeutic vulnerability to prevent relapse in stroma-rich colon cancer.

OBJECTIVE: Stroma-rich tumours represent a poor prognostic subtype in stage II/III colon cancer (CC), with high relapse rates and limited response to standard adjuvant chemotherapy. DESIGN: To address the lack of efficacious therapeutic options for patients with stroma-rich CC, we stratified our human tumour cohorts according to stromal content, enabling identification of the biology underpinning relapse and potential therapeutic vulnerabilities specifically within stroma-rich tumours that could be exploited clinically. Following human tumour-based discovery and independent clinical validation, we use a series of in vitro and stroma-rich in vivo models to test and validate the therapeutic potential of elevating the biology associated with reduced relapse in human tumours. RESULTS: By performing our analyses specifically within the stroma-rich/high-fibroblast (HiFi) subtype of CC, we identify and validate the clinical value of a HiFi-specific prognostic signature (HPS), which stratifies tumours based on STAT1-related signalling (High-HPS v Low-HPS=HR 0.093, CI 0.019 to 0.466). Using in silico, in vitro and in vivo models, we demonstrate that the HPS is associated with antigen processing and presentation within discrete immune lineages in stroma-rich CC, downstream of double-stranded RNA and viral response signalling. Treatment with the TLR3 agonist poly(I:C) elevated the HPS signalling and antigen processing phenotype across in vitro and in vivo models. In an in vivo model of stroma-rich CC, poly(I:C) treatment significantly increased systemic cytotoxic T cell activity (p<0.05) and reduced liver metastases (p<0.0002). CONCLUSION: This study reveals new biological insight that offers a novel therapeutic option to reduce relapse rates in patients with the worst prognosis CC.

The amino acid transporter SLC7A5 is required for efficient growth of KRAS-mutant colorectal cancer.

Oncogenic KRAS mutations and inactivation of the APC tumor suppressor co-occur in colorectal cancer (CRC). Despite efforts to target mutant KRAS directly, most therapeutic approaches focus on downstream pathways, albeit with limited efficacy. Moreover, mutant KRAS alters the basal metabolism of cancer cells, increasing glutamine utilization to support proliferation. We show that concomitant mutation of Apc and Kras in the mouse intestinal epithelium profoundly rewires metabolism, increasing glutamine consumption. Furthermore, SLC7A5, a glutamine antiporter, is critical for colorectal tumorigenesis in models of both early- and late-stage metastatic disease. Mechanistically, SLC7A5 maintains intracellular amino acid levels following KRAS activation through transcriptional and metabolic reprogramming. This supports the increased demand for bulk protein synthesis that underpins the enhanced proliferation of KRAS-mutant cells. Moreover, targeting protein synthesis, via inhibition of the mTORC1 regulator, together with Slc7a5 deletion abrogates the growth of established Kras-mutant tumors. Together, these data suggest SLC7A5 as an attractive target for therapy-resistant KRAS-mutant CRC.

In-depth Clinical and Biological Exploration of DNA Damage Immune Response as a Biomarker for Oxaliplatin Use in Colorectal Cancer.

PURPOSE: The DNA damage immune response (DDIR) assay was developed in breast cancer based on biology associated with deficiencies in homologous recombination and Fanconi anemia pathways. A positive DDIR call identifies patients likely to respond to platinum-based chemotherapies in breast and esophageal cancers. In colorectal cancer, there is currently no biomarker to predict response to oxaliplatin. We tested the ability of the DDIR assay to predict response to oxaliplatin-based chemotherapy in colorectal cancer and characterized the biology in DDIR-positive colorectal cancer. EXPERIMENTAL DESIGN: Samples and clinical data were assessed according to DDIR status from patients who received either 5-fluorouracil (5-FU) or 5FUFA (bolus and infusion 5-FU with folinic acid) plus oxaliplatin (FOLFOX) within the FOCUS trial (n = 361, stage IV), or neoadjuvant FOLFOX in the FOxTROT trial (n = 97, stage II/III). Whole transcriptome, mutation, and IHC data of these samples were used to interrogate the biology of DDIR in colorectal cancer. RESULTS: Contrary to our hypothesis, DDIR-negative patients displayed a trend toward improved outcome for oxaliplatin-based chemotherapy compared with DDIR-positive patients. DDIR positivity was associated with microsatellite instability (MSI) and colorectal molecular subtype 1. Refinement of the DDIR signature, based on overlapping IFN-related chemokine signaling associated with DDIR positivity across colorectal cancer and breast cancer cohorts, further confirmed that the DDIR assay did not have predictive value for oxaliplatin-based chemotherapy in colorectal cancer. CONCLUSIONS: DDIR positivity does not predict improved response following oxaliplatin treatment in colorectal cancer. However, data presented here suggest the potential of the DDIR assay in identifying immune-rich tumors that may benefit from immune checkpoint blockade, beyond current use of MSI status.