Epithelial-to-mesenchymal transition signature assessment in colorectal cancer quantifies tumour stromal content rather than true transition

Stromal Signals Dominate Gene Expression Signature Scores That Aim to Describe Cancer Cell-intrinsic Stemness or Mesenchymality Characteristics

Epithelial-to-mesenchymal transition (EMT) in cancer cells confers migratory abilities, a crucial aspect in the metastasis of tumors that frequently leads to death. In multiple studies, authors proposed gene expression signatures for EMT, stemness, or mesenchymality of tumors based on bulk tumor expression profiling. However, recent studies suggested that noncancerous cells from the microenvironment or macroenvironment heavily influence such signature profiles. Here, we strengthen these findings by investigating 11 published and frequently referenced gene expression signatures that were proposed to describe EMT-related (EMT, mesenchymal, or stemness) characteristics in various cancer types. By analyses of bulk, single-cell, and pseudobulk expression data, we show that the cell type composition of a tumor sample frequently dominates scores of these EMT-related signatures. A comprehensive, integrated analysis of bulk RNA sequencing (RNA-seq) and single-cell RNA-seq data shows that stromal cells, most often fibroblasts, are the main drivers of EMT-related signature scores. We call attention to the risk of false conclusions about tumor properties when interpreting EMT-related signatures, especially in a clinical setting: high patient scores of EMT-related signatures or calls of "stemness subtypes" often result from low cancer cell content in tumor biopsies rather than cancer cell-specific stemness or mesenchymal/EMT characteristics.

SIGNIFICANCE

Cancer self-renewal and migratory abilities are often characterized via gene module expression profiles, also called EMT or stemness gene expression signatures. Using published clinical tumor samples, cancer cell lines, and single cancer cells, we highlight the dominating influence of noncancer cells in low cancer cell content biopsies on their scores. We caution on their application for low cancer cell content clinical cancer samples with the intent to assign such characteristics or subtypes.

Mesenchymal ovarian cancer cells promote CD8+ T cell exhaustion through the LGALS3-LAG3 axis

Cancer cells often metastasize by undergoing an epithelial-mesenchymal transition (EMT). Although abundance of CD8+ T-cells in the tumor microenvironment correlates with improved survival, mesenchymal cancer cells acquire greater resistance to antitumor immunity in some cancers. We hypothesized the EMT modulates the immune response to ovarian cancer. Here we show that cancer cells from infiltrated/inflamed tumors possess more mesenchymal cells, than excluded and desert tumors. We also noted high expression of LGALS3 is associated with EMT in vivo, a finding validated with in vitro EMT models. Dissecting the cellular communications among populations in the tumor revealed that mesenchymal cancer cells in infiltrated tumors communicate through LGALS3 to LAG3 receptor expressed by CD8+ T cells. We found CD8+ T cells express high levels of LAG3, a marker of T cell exhaustion. The results indicate that EMT in ovarian cancer cells promotes interactions between cancer cells and T cells through the LGALS3 - LAG3 axis, which could increase T cell exhaustion in infiltrated tumors, dampening antitumor immunity.

Role of epithelial-mesenchymal transition factor SNAI1 and its targets in ovarian cancer aggressiveness

Ovarian cancer remains the most lethal gynecologic malignancy in the USA. For over twenty years, epithelial-mesenchymal transition (EMT) has been characterized extensively in development and disease. The dysregulation of this process in cancer has been identified as a mechanism by which epithelial tumors become more aggressive, allowing them to survive and invade distant tissues. This occurs in part due to the increased expression of the EMT transcription factor, SNAI1 (Snail). In the case of epithelial ovarian cancer, Snail has been shown to contribute to cancer invasion, stemness, chemoresistance, and metabolic changes. Thus, in this review, we focus on summarizing current findings on the role of EMT (specifically, factors downstream of Snail) in determining ovarian cancer aggressiveness.

Tumor heterogeneity: preclinical models, emerging technologies, and future applications

Heterogeneity describes the differences among cancer cells within and between tumors. It refers to cancer cells describing variations in morphology, transcriptional profiles, metabolism, and metastatic potential. More recently, the field has included the characterization of the tumor immune microenvironment and the depiction of the dynamics underlying the cellular interactions promoting the tumor ecosystem evolution. Heterogeneity has been found in most tumors representing one of the most challenging behaviors in cancer ecosystems. As one of the critical factors impairing the long-term efficacy of solid tumor therapy, heterogeneity leads to tumor resistance, more aggressive metastasizing, and recurrence. We review the role of the main models and the emerging single-cell and spatial genomic technologies in our understanding of tumor heterogeneity, its contribution to lethal cancer outcomes, and the physiological challenges to consider in designing cancer therapies. We highlight how tumor cells dynamically evolve because of the interactions within the tumor immune microenvironment and how to leverage this to unleash immune recognition through immunotherapy. A multidisciplinary approach grounded in novel bioinformatic and computational tools will allow reaching the integrated, multilayered knowledge of tumor heterogeneity required to implement personalized, more efficient therapies urgently required for cancer patients.

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.

Patients with mesenchymal tumours and high Fusobacteriales prevalence have worse prognosis in colorectal cancer (CRC)

OBJECTIVES

Transcriptomic-based subtyping, consensus molecular subtyping (CMS) and colorectal cancer intrinsic subtyping (CRIS) identify a patient subpopulation with mesenchymal traits (CMS4/CRIS-B) and poorer outcome. Here, we investigated the relationship between prevalence of Fusobacterium nucleatum (Fn) and Fusobacteriales, CMS/CRIS subtyping, cell type composition, immune infiltrates and host contexture to refine patient stratification and to identify druggable context-specific vulnerabilities.

DESIGN

We coupled cell culture experiments with characterisation of Fn/Fusobacteriales prevalence and host biology/microenviroment in tumours from two independent colorectal cancer patient cohorts (Taxonomy: n=140, colon and rectal cases of The Cancer Genome Atlas (TCGA-COAD-READ) cohort: n=605).

RESULTS

In vitro, Fn infection induced inflammation via nuclear factor kappa-light-chain-enhancer of activated B cells/tumour necrosis factor alpha in HCT116 and HT29 cancer cell lines. In patients, high Fn/Fusobacteriales were found in CMS1, microsatellite unstable () tumours, with infiltration of M1 macrophages, reduced M2 macrophages, and high interleukin (IL)-6/IL-8/IL-1β signalling. Analysis of the Taxonomy cohort suggested that Fn was prognostic for CMS4/CRIS-B patients, despite having lower Fn load than CMS1 patients. In the TCGA-COAD-READ cohort, we likewise identified a differential association between Fusobacteriales relative abundance and outcome when stratifying patients in mesenchymal (either CMS4 and/or CRIS-B) versus non-mesenchymal (neither CMS4 nor CRIS-B). Patients with mesenchymal tumours and high Fusobacteriales had approximately twofold higher risk of worse outcome. These associations were null in non-mesenchymal patients. Modelling the three-way association between Fusobacteriales prevalence, molecular subtyping and host contexture with logistic models with an interaction term disentangled the pathogen-host signalling relationship and identified aberrations (including NOTCH, CSF1-3 and IL-6/IL-8) as candidate targets.

CONCLUSION

This study identifies CMS4/CRIS-B patients with high Fn/Fusobacteriales prevalence as a high-risk subpopulation that may benefit from therapeutics targeting mesenchymal biology.

Cancer-Associated Fibroblasts and Squamous Epithelial Cells Constitute a Unique Microenvironment in a Mouse Model of Inflammation-Induced Colon Cancer

The tumor microenvironment plays a key role in the pathogenesis of colorectal tumors and contains various cell types including epithelial, immune, and mesenchymal cells. Characterization of the interactions between these cell types is necessary for revealing the complex nature of tumors. In this study, we used single-cell RNA-seq (scRNA-seq) to compare the tumor microenvironments between a mouse model of sporadic colorectal adenoma (Lrig1^CreERT2/+;Apc^2lox14/+) and a mouse model of inflammation-driven colorectal cancer induced by azoxymethane and dextran sodium sulfate (AOM/DSS). While both models develop tumors in the distal colon, we found that the two tumor types have distinct microenvironments. AOM/DSS tumors have an increased abundance of two populations of cancer-associated fibroblasts (CAFs) compared with APC tumors, and we revealed their divergent spatial association with tumor cells using multiplex immunofluorescence (MxIF) imaging. We also identified a unique squamous cell population in AOM/DSS tumors, whose origins were distinct from anal squamous epithelial cells. These cells were in higher proportions upon administration of a chemotherapy regimen of 5-Fluorouracil/Irinotecan. We used computational inference algorithms to predict cell-cell communication mediated by ligand-receptor interactions and downstream pathway activation, and identified potential mechanistic connections between CAFs and tumor cells, as well as CAFs and squamous epithelial cells. This study provides important preclinical insight into the microenvironment of two distinct models of colorectal tumors and reveals unique roles for CAFs and squamous epithelial cells in the AOM/DSS model of inflammation-driven cancer.

Pan-cancer quantitation of epithelial-mesenchymal transition dynamics using parallel reaction monitoring-based targeted proteomics approach

Epithelial–mesenchymal transition (EMT) is a dynamic and complex cellular process that is known to be hijacked by cancer cells to facilitate invasion, metastasis and therapeutic resistance. Several quantitative measures to assess the interplay between EMT and cancer progression are available, based on large scale genome and transcriptome data. However, these large scale multi-omics studies have repeatedly illustrated a lack of correlation in mRNA and protein abundances that may be influenced by diverse post-translational regulation. Hence, it is imperative to understand how changes in the EMT proteome are associated with the process of oncogenic transformation. To this effect, we developed a parallel reaction monitoring-based targeted proteomics method for quantifying abundances of EMT-associated proteins across cancer cell lines. Our study revealed that quantitative measurement of EMT proteome which enabled a more accurate assessment than transcriptomics data and revealed specific discrepancies against a backdrop of generally strong concordance between proteomic and transcriptomic data. We further demonstrated that changes in our EMT proteome panel might play a role in tumor transformation across cancer types. In future, this EMT panel assay has the potential to be used for clinical samples to guide treatment choices and to congregate functional information for the development and advancing novel therapeutics.

Subtyping of sarcomas based on pathway enrichment scores in bulk and single cell transcriptomes

Background

Sarcomas are highly heterogeneous in molecular, pathologic, and clinical features. However, a classification of sarcomas by integrating different types of pathways remains mostly unexplored.

Methods

We performed hierarchical clustering analysis of sarcomas based on the enrichment scores of 14 pathways involved in immune, stromal, DNA damage repair (DDR), and oncogenic signatures in three bulk tumor transcriptome datasets.

Results

Consistently in the three datasets, sarcomas were classified into three subtypes: Immune Class (Imm-C), Stromal Class (Str-C), and DDR Class (DDR-C). Imm-C had the strongest anti-tumor immune signatures and the lowest intratumor heterogeneity (ITH); Str-C showed the strongest stromal signatures, the highest genomic stability and global methylation levels, and the lowest proliferation potential; DDR-C had the highest DDR activity, expression of the cell cycle pathway, tumor purity, stemness scores, proliferation potential, and ITH, the most frequent TP53 mutations, and the worst survival. We further validated the stability and reliability of our classification method by analyzing a single cell RNA-Seq (scRNA-seq) dataset. Based on the expression levels of five genes in the pathways of T cell receptor signaling, cell cycle, mismatch repair, focal adhesion, and calcium signaling, we built a linear risk scoring model (ICMScore) for sarcomas. We demonstrated that ICMScore was an adverse prognostic factor for sarcomas and many other cancers.

Conclusions

Our classification method provides novel insights into tumor biology and clinical implications for sarcomas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03248-3.

Stromal scoring in advanced colon and rectal cancer: Stroma-rich tumors and their association with aggressive phenotypes

Background: Our aim was to explore relevance of the proportion between neoplastic cell component and tumor-associated stroma in order to assess its association with confirmed aggressive phenotypes of right/left colon and rectum cancers in a large series of patients. Methods: The quantification of stroma component was performed in patients diagnosed with colorectal adenocarcinoma who underwent surgical resection. The analyzed variables were age, gender, anatomical/pathological features, and tumor-stroma proportion. Tumor-stroma proportion was estimated based on slides used in routine pathology for determination of T status and was described as low, with a stromal percentage ?50% or high, with a stromal percentage >50%. The tumor-stroma proportion was estimated by two observers, and the inter-observer agreement was assessed. Results: The sample included 390 colorectal adenocarcinoma patients. Stroma-rich tumors were observed in 53.3% of cases. Well-differentiated tumors had the lowest stromal proportions (p = 0.028). Stroma-poor tumors showed less depth of invasion (p<0.001). High stromal content was observed in association with tumor budding, perineural, angiolymphatic, and lymph node involvement, and distant metastasis (p?0.001). Colorectal adenocarcinoma without lymph node or distant metastasis involvement had lower stromal proportion, while metastatic ones exhibited high stromal content (p <0.001). The inter-rater reliability (concordance) between the estimations of pathologists for tumor-stroma proportions was high (?=0.746). Conclusion: The tumorstroma proportion in colorectal adenocarcinoma was associated with adverse prognostic factors, reflecting the stage of the disease. Stroma-rich tumors showed a significant correlation with advancement of the disease and its aggressiveness. Due to its availability tumor-stroma proportion evaluation has high application potential and can complement current staging system for colorectal adenocarcinoma.

Insights into the Role of Matrix Metalloproteinases in Precancerous Conditions and in Colorectal Cancer

Simple Summary

Colorectal cancer (CRC) is one of the most common cancer worldwide. CRC is derived from polyps and many factors, such as Matrix Metalloproteinases (MMPs) can gain the progression of colorectal carcinogenesis. Many investigations have indicated the role of MMPs in CRC development while there is not enough knowledge about the function of MMPs in precancerous conditions. This review summarizes the current information about the role of MMPs in polyps and CRC progression.

Abstract

Colorectal cancer (CRC) is the third and second cancer for incidence and mortality worldwide, respectively, and is becoming prevalent in developing countries. Most CRCs derive from polyps, especially adenomatous polyps, which can gradually transform into CRC. The family of Matrix Metalloproteinases (MMPs) plays a critical role in the initiation and progression of CRC. Prominent MMPs, including MMP-1, MMP-2, MMP-7, MMP-8, MMP-9, MMP-12, MMP-13, MMP-14, and MMP-21, have been detected in CRC patients, and the expression of most of them correlates with a poor prognosis. Moreover, many studies have explored the inhibition of MMPs and targeted therapy for CRC, but there is not enough information about the role of MMPs in polyp malignancy. In this review, we discuss the role of MMPs in colorectal cancer and its pathogenesis

Isolation of Circulating Tumor Cells from Peripheral Blood Samples of Cancer Patients Using Microfluidic Technology

The aim of the investigation was to study the potential of an innovative microfluidic technology for the isolation of circulating tumor cells (CTCs) from the peripheral blood samples of cancer patients.

AKT3 Expression in Mesenchymal Colorectal Cancer Cells Drives Growth and Is Associated with Epithelial-Mesenchymal Transition

Simple Summary

Colorectal cancer can be subdivided into four distinct subtypes that are characterised by different clinical features and responses to therapies currently used in the clinic to treat this disease. One of those subtypes, called CMS4, is associated with a worse prognosis and poor response to therapies compared to other subtypes. We therefore set out to explore what proteins are differentially expressed and used in CMS4 to find potential new targets for therapy. We found that protein AKT3 is highly expressed in CMS4, and that active AKT3 inhibits a protein that stalls growth of cancer cells (p27^KIP1). We can target AKT3 with inhibitors which leads to strongly reduced growth of cancer cell lines that are categorised as CMS4. Furthermore, our data suggests that high AKT3 expression in tumour cells may be used to identify poor prognosis colorectal cancer patients. Future research should point out if high AKT3 expression can be used to select colorectal cancer patients that have a poor prognosis but that could benefit from AKT3-targeted treatment.

Abstract

Colorectal cancer (CRC) is a heterogeneous disease that can currently be subdivided into four distinct consensus molecular subtypes (CMS) based on gene expression profiling. The CMS4 subtype is marked by high expression of mesenchymal genes and is associated with a worse overall prognosis compared to other CMSs. Importantly, this subtype responds poorly to the standard therapies currently used to treat CRC. We set out to explore what regulatory signalling networks underlie the CMS4 phenotype of cancer cells, specifically, by analysing which kinases were more highly expressed in this subtype compared to others. We found AKT3 to be expressed in the cancer cell epithelium of CRC specimens, patient derived xenograft (PDX) models and in (primary) cell cultures representing CMS4. Importantly, chemical inhibition or knockout of this gene hampers outgrowth of this subtype, as AKT3 controls expression of the cell cycle regulator p27^KIP1. Furthermore, high AKT3 expression was associated with high expression of epithelial-mesenchymal transition (EMT) genes, and this observation could be expanded to cell lines representing other carcinoma types. More importantly, this association allowed for the identification of CRC patients with a high propensity to metastasise and an associated poor prognosis. High AKT3 expression in the tumour epithelial compartment may thus be used as a surrogate marker for EMT and may allow for a selection of CRC patients that could benefit from AKT3-targeted therapy.

Exploring and modelling colon cancer inter-tumour heterogeneity: opportunities and challenges

Colon cancer inter-tumour heterogeneity is installed on multiple levels, ranging from (epi)genetic driver events to signalling pathway rewiring reflected by differential gene expression patterns. Although the existence of heterogeneity in colon cancer has been recognised for a longer period of time, it is sparingly incorporated as a determining factor in current clinical practice. Here we describe how unsupervised gene expression-based classification efforts, amongst which the consensus molecular subtypes (CMS), can stratify patients in biological subgroups associated with distinct disease outcome and responses to therapy. We will discuss what is needed to extend these subtyping efforts to the clinic and we will argue that preclinical models recapitulate CMS subtypes and can be of vital use to increase our understanding of treatment response and resistance and to discover novel targets for therapy.

Context specificity of the EMT transcriptional response

Epithelial–mesenchymal plasticity contributes to many biological processes, including tumor progression. Various epithelial–mesenchymal transition (EMT) responses have been reported and no common, EMT-defining gene expression program has been identified. Here, we have performed a comparative analysis of the EMT response, leveraging highly multiplexed single-cell RNA sequencing (scRNA-seq) to measure expression profiles of 103,999 cells from 960 samples, comprising 12 EMT time course experiments and independent kinase inhibitor screens for each. We demonstrate that the EMT is vastly context specific, with an average of only 22% of response genes being shared between any two conditions, and over half of all response genes were restricted to 1–2 time course experiments. Further, kinase inhibitor screens revealed signaling dependencies and modularity of these responses. These findings suggest that the EMT is not simply a single, linear process, but is highly variable and modular, warranting quantitative frameworks for understanding nuances of the transition.

It is unclear if a common EMT expression program exists. Here, the authors perform multiplexed single-cell RNA sequencing across 12 EMT time courses and 16 kinase inhibitor screens, and find that EMT transcriptional responses are context specific and EMT is not a single, linear transition.

Genomics and precision surgery for head and neck squamous cell carcinoma

The identification of the biological determinants that shape the response of tumors to medical therapies offers perspectives for better patient stratification and therapeutic targeting. Here, we discuss how genomics could help to improve the surgical treatment of head and neck squamous cell carcinoma (HNSCC). We examine the potential use of genomic analyses for: i) refining and standardizing the indications for surgery, ii) the choice of surgical procedure, and iii) the follow-up of patients with resected tumors. We highlight the studies that used genomics to explore the contribution of tumor biology to the outcome of surgery. We discuss the important developments that are challenging current surgical practice in HNSCC, such as neoadjuvant immunotherapy and the analysis of circulating DNA. Genomic analyses provide practical tools that could help improve the pathological diagnosis and staging of HNSCC, and increase the appreciation of the importance of tumor biology in the outcome of surgery. Identification of biomarkers will likely contribute to a move toward precision surgery of HNSCC, i.e. the personalization of surgical practice based on tumor biology.

Epithelial NOTCH Signaling Rewires the Tumor Microenvironment of Colorectal Cancer to Drive Poor-Prognosis Subtypes and Metastasis

The metastatic process of colorectal cancer (CRC) is not fully understood and effective therapies are lacking. We show that activation of NOTCH1 signaling in the murine intestinal epithelium leads to highly penetrant metastasis (100% metastasis; with >80% liver metastases) in KrasG12D-driven serrated cancer. Transcriptional profiling reveals that epithelial NOTCH1 signaling creates a tumor microenvironment (TME) reminiscent of poorly prognostic human CRC subtypes (CMS4 and CRIS-B), and drives metastasis through transforming growth factor (TGF) β-dependent neutrophil recruitment. Importantly, inhibition of this recruitment with clinically relevant therapeutic agents blocks metastasis. We propose that NOTCH1 signaling is key to CRC progression and should be exploited clinically.

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.

ROCK2 inhibition triggers the collective invasion of colorectal adenocarcinomas

The metastatic progression of cancer is a multi-step process initiated by the local invasion of the peritumoral stroma. To identify the mechanisms underlying colorectal carcinoma (CRC) invasion, we collected live human primary cancer specimens at the time of surgery and monitored them ex vivo. This revealed that conventional adenocarcinomas undergo collective invasion while retaining their epithelial glandular architecture with an inward apical pole delineating a luminal cavity. To identify the underlying mechanisms, we used microscopy-based assays on 3D organotypic cultures of Caco-2 cysts as a model system. We performed two siRNA screens targeting Rho-GTPases effectors and guanine nucleotide exchange factors. These screens revealed that ROCK2 inhibition triggers the initial leader/follower polarization of the CRC cell cohorts and induces collective invasion. We further identified FARP2 as the Rac1 GEF necessary for CRC collective invasion. However, FARP2 activation is not sufficient to trigger leader cell formation and the concomitant inhibition of Myosin-II is required to induce invasion downstream of ROCK2 inhibition. Our results contrast with ROCK pro-invasive function in other cancers, stressing that the molecular mechanism of metastatic spread likely depends on tumour types and invasion mode.