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.

Epithelial TGFβ engages growth-factor signalling to circumvent apoptosis and drive intestinal tumourigenesis with aggressive features

The pro-tumourigenic role of epithelial TGFβ signalling in colorectal cancer (CRC) is controversial. Here, we identify a cohort of born to be bad early-stage (T1) colorectal tumours, with aggressive features and a propensity to disseminate early, that are characterised by high epithelial cell-intrinsic TGFβ signalling. In the presence of concurrent Apc and Kras mutations, activation of epithelial TGFβ signalling rampantly accelerates tumourigenesis and share transcriptional signatures with those of the born to be bad T1 human tumours and predicts recurrence in stage II CRC. Mechanistically, epithelial TGFβ signalling induces a growth-promoting EGFR-signalling module that synergises with mutant APC and KRAS to drive MAPK signalling that re-sensitise tumour cells to MEK and/or EGFR inhibitors. Together, we identify epithelial TGFβ signalling both as a determinant of early dissemination and a potential therapeutic vulnerability of CRC's with born to be bad traits.

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.

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.

Molecular Subtyping Resource: a user-friendly tool for rapid biological discovery from transcriptional data

Generation of transcriptional data has dramatically increased in the past decade, driving the development of analytical algorithms that enable interrogation of the biology underpinning the profiled samples. However, these resources require users to have expertise in data wrangling and analytics, reducing opportunities for biological discovery by 'wet-lab' users with a limited programming skillset. Although commercial solutions exist, costs for software access can be prohibitive for academic research groups. To address these challenges, we have developed an open source and user-friendly data analysis platform for on-the-fly bioinformatic interrogation of transcriptional data derived from human or mouse tissue, called Molecular Subtyping Resource (MouSR). This internet-accessible analytical tool, https://mousr.qub.ac.uk/, enables users to easily interrogate their data using an intuitive 'point-and-click' interface, which includes a suite of molecular characterisation options including quality control, differential gene expression, gene set enrichment and microenvironmental cell population analyses from RNA sequencing. The MouSR online tool provides a unique freely available option for users to perform rapid transcriptomic analyses and comprehensive interrogation of the signalling underpinning transcriptional datasets, which alleviates a major bottleneck for biological discovery. This article has an associated First Person interview with the first author of the paper.

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning

OBJECTIVE

Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning.

DESIGN

Training and evaluation of a neural network were performed using a total of n=1206 tissue sections with comprehensive multi-omic data from three independent datasets (training on FOCUS trial, n=278 patients; test on rectal cancer biopsies, GRAMPIAN cohort, n=144 patients; and The Cancer Genome Atlas (TCGA), n=430 patients). Ground truth CMS calls were ascertained by matching random forest and single sample predictions from CMS classifier.

RESULTS

Image-based CMS (imCMS) accurately classified slides in unseen datasets from TCGA (n=431 slides, AUC)=0.84) and rectal cancer biopsies (n=265 slides, AUC=0.85). imCMS spatially resolved intratumoural heterogeneity and provided secondary calls correlating with bioinformatic prediction from molecular data. imCMS classified samples previously unclassifiable by RNA expression profiling, reproduced the expected correlations with genomic and epigenetic alterations and showed similar prognostic associations as transcriptomic CMS.

CONCLUSION

This study shows that a prediction of RNA expression classifiers can be made from H&E images, opening the door to simple, cheap and reliable biological stratification within routine workflows.

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.

Fibroblast-derived Gremlin1 localises to epithelial cells at the base of the intestinal crypt

Gremlin1 (GREM1) is a secreted glycoprotein member of the differential screening-selected gene in aberrant neuroblastoma (DAN) family of bone morphogenetic protein (BMP) antagonists, which binds to BMPs preventing their receptor engagement. Previous studies have identified that stage II colorectal cancer (CRC) patients with high levels of GREM1 gene expression in their tumour tissue have a poorer prognosis. Using a series of in silico and in situ methodologies, we demonstrate that GREM1 gene expression is significantly higher (p < 0.0001) in CRC consensus molecular subtype 4 (CMS4), compared to the other CMS subtypes and correlates (p < 0.0001) with levels of cancer-associated fibroblasts (CAFs) within the CRC tumour microenvironment (TME). Our optimised immunohistochemistry protocol identified endogenous GREM1 protein expression in both the muscularis mucosa and adjacent colonic crypt bases in mouse intestine, in contrast to RNA expression which was shown to localise specifically to the muscularis mucosa, as determined by in situ hybridisation. Importantly, we demonstrate that cells with high levels of GREM1 expression display low levels of phospho-Smad1/5, consistent with reduced BMP signalling. Taken together, these data highlight a novel paracrine signalling circuit, which involves uptake of mature GREM1 protein by colonic crypt cells following secretion from neighbouring fibroblasts in the TME.

Overcoming Resistance to Targeted Therapies in Cancer

The recent discovery of oncogenic drivers and subsequent development of novel targeted strategies has significantly added to the therapeutic armamentarium of anti-cancer therapies. Targeting BCR-ABL in chronic myeloid leukemia (CML) or HER2 in breast cancer has led to practice-changing clinical benefits, while promising therapeutic responses have been achieved by precision medicine approaches in EGFR mutant lung cancer, colorectal cancer and BRAF mutant melanoma. However, although initial therapeutic responses to targeted therapies can be substantial, many patients will develop disease progression within 6-12 months. An increasing application of powerful omics-based approaches and improving preclinical models have enabled the rapid identification of secondary resistance mechanisms. Herein, we discuss how this knowledge has translated into rational, novel treatment strategies for relapsed patients in genomically selected cancer populations.

EphA2 Expression Is a Key Driver of Migration and Invasion and a Poor Prognostic Marker in Colorectal Cancer

PURPOSE

EphA2, a member of the Eph receptor tyrosine kinases family, is an important regulator of tumor initiation, neovascularization, and metastasis in a wide range of epithelial and mesenchymal cancers; however, its role in colorectal cancer recurrence and progression is unclear.

EXPERIMENTAL DESIGN

EphA2 expression was determined by immunohistochemistry in stage II/III colorectal tumors (N = 338), and findings correlated with clinical outcome. The correlation between EphA2 expression and stem cell markers CD44 and Lgr5 was examined. The role of EphA2 in migration/invasion was assessed using a panel of KRAS wild-type (WT) and mutant (MT) parental and invasive colorectal cancer cell line models.

RESULTS

Colorectal tumors displayed significantly higher expression levels of EphA2 compared with matched normal tissue, which positively correlated with high CD44 and Lgr5 expression levels. Moreover, high EphA2 mRNA and protein expression were found to be associated with poor overall survival in stage II/III colorectal cancer tissues, in both univariate and multivariate analyses. Preclinically, we found that EphA2 was highly expressed in KRASMT colorectal cancer cells and that EphA2 levels are regulated by the KRAS-driven MAPK and RalGDS-RalA pathways. Moreover, EphA2 levels were elevated in several invasive daughter cell lines, and downregulation of EphA2 using RNAi or recombinant EFNA1 suppressed migration and invasion of KRASMT colorectal cancer cells.

CONCLUSIONS

These data show that EpHA2 is a poor prognostic marker in stage II/III colorectal cancer, which may be due to its ability to promote cell migration and invasion, providing support for the further investigation of EphA2 as a novel prognostic biomarker and therapeutic target.

ADAM17-dependent c-MET-STAT3 signaling mediates resistance to MEK inhibitors in KRAS mutant colorectal cancer

There are currently no approved targeted therapies for advanced KRAS mutant (KRASMT) colorectal cancer (CRC). Using a unique systems biology approach, we identified JAK1/2-dependent activation of STAT3 as the key mediator of resistance to MEK inhibitors in KRASMT CRC in vitro and in vivo. Further analyses identified acute increases in c-MET activity following treatment with MEK inhibitors in KRASMT CRC models, which was demonstrated to promote JAK1/2-STAT3-mediated resistance. Furthermore, activation of c-MET following MEK inhibition was found to be due to inhibition of the ERK-dependent metalloprotease ADAM17, which normally inhibits c-MET signaling by promoting shedding of its endogenous antagonist, soluble "decoy" MET. Most importantly, pharmacological blockade of this resistance pathway with either c-MET or JAK1/2 inhibitors synergistically increased MEK-inhibitor-induced apoptosis and growth inhibition in vitro and in vivo in KRASMT models, providing clear rationales for the clinical assessment of these combinations in KRASMT CRC patients.

Differential affinity of FLIP and procaspase 8 for FADD's DED binding surfaces regulates DISC assembly

Death receptor activation triggers recruitment of FADD, which via its death effector domain (DED) engages the DEDs of procaspase 8 and its inhibitor FLIP to form death-inducing signalling complexes (DISCs). The DEDs of FADD, FLIP and procaspase 8 interact with one another using two binding surfaces defined by α1/α4 and α2/α5 helices, respectively. Here we report that FLIP has preferential affinity for the α1/α4 surface of FADD, whereas procaspase 8 has preferential affinity for FADD's α2/α5 surface. These relative affinities contribute to FLIP being recruited to the DISC at comparable levels to procaspase 8 despite lower cellular expression. Additional studies, including assessment of DISC stoichiometry and functional assays, suggest that following death receptor recruitment, the FADD DED preferentially engages FLIP using its α1/α4 surface and procaspase 8 using its α2/α5 surface; these tripartite intermediates then interact via the α1/α4 surface of FLIP DED1 and the α2/α5 surface of procaspase 8 DED2.