Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMSs) with distinguishing features: CMS1 (microsatellite instability immune, 14%), hypermutated, microsatellite unstable and strong immune activation; CMS2 (canonical, 37%), epithelial, marked WNT and MYC signaling activation; CMS3 (metabolic, 13%), epithelial and evident metabolic dysregulation; and CMS4 (mesenchymal, 23%), prominent transforming growth factor-β activation, stromal invasion and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intratumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC-with clear biological interpretability-and the basis for future clinical stratification and subtype-based targeted interventions.

https://serval.unil.ch/resource/serval:BIB_6206DC2BFE0E.P001/REF.pdf

The consensus molecular subtypes of colorectal cancer

Prospective Derivation of a Living Organoid Biobank of Colorectal Cancer Patients

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA 'microsatellite instability/CpG island methylation phenotype' transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

Proteogenomic characterization of human colon and rectal cancer

The American Joint Committee on Cancer/Union Internationale Contre le Cancer (AJCC/UICC) TNM staging system provides the most reliable guidelines for the routine prognostication and treatment of colorectal carcinoma. This traditional tumour staging summarizes data on tumour burden (T), the presence of cancer cells in draining and regional lymph nodes (N) and evidence for distant metastases (M). However, it is now recognized that the clinical outcome can vary significantly among patients within the same stage. The current classification provides limited prognostic information and does not predict response to therapy. Multiple ways to classify cancer and to distinguish different subtypes of colorectal cancer have been proposed, including morphology, cell origin, molecular pathways, mutation status and gene expression-based stratification. These parameters rely on tumour-cell characteristics. Extensive literature has investigated the host immune response against cancer and demonstrated the prognostic impact of the in situ immune cell infiltrate in tumours. A methodology named 'Immunoscore' has been defined to quantify the in situ immune infiltrate. In colorectal cancer, the Immunoscore may add to the significance of the current AJCC/UICC TNM classification, since it has been demonstrated to be a prognostic factor superior to the AJCC/UICC TNM classification. An international consortium has been initiated to validate and promote the Immunoscore in routine clinical settings. The results of this international consortium may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

https://dash.harvard.edu/bitstream/handle/1/13581037/4255306.pdf?sequence=1

Towards the introduction of the 'Immunoscore' in the classification of malignant tumours.

Epithelial organoids recapitulate multiple aspects of real organs, making them promising models of organ development, function and disease. However, the full potential of organoids in research and therapy has remained unrealized, owing to the poorly defined animal-derived matrices in which they are grown. Here we used modular synthetic hydrogel networks to define the key extracellular matrix (ECM) parameters that govern intestinal stem cell (ISC) expansion and organoid formation, and show that separate stages of the process require different mechanical environments and ECM components. In particular, fibronectin-based adhesion was sufficient for ISC survival and proliferation. High matrix stiffness significantly enhanced ISC expansion through a yes-associated protein 1 (YAP)-dependent mechanism. ISC differentiation and organoid formation, on the other hand, required a soft matrix and laminin-based adhesion. We used these insights to build a fully defined culture system for the expansion of mouse and human ISCs. We also produced mechanically dynamic matrices that were initially optimal for ISC expansion and subsequently permissive to differentiation and intestinal organoid formation, thus creating well-defined alternatives to animal-derived matrices for the culture of mouse and human stem-cell-derived organoids. Our approach overcomes multiple limitations of current organoid cultures and greatly expands their applicability in basic and clinical research. The principles presented here can be extended to identify designer matrices that are optimal for long-term culture of other types of stem cells and organoids.

https://www.nature.com/articles/nature20168.pdf?proof=t

Designer matrices for intestinal stem cell and organoid culture

�Colorectal cancer (CRC) is a major cause of cancer mortality. Whereas some patients respond well to therapy, others do not, and thus more precise, individualized treatment strategies are needed. To that end, we analyzed gene expression profiles from 1,290 CRC tumors using consensus-based unsupervised clustering. The resultant clusters were then associated with therapeutic response data to the epidermal growth factor receptor–targeted drug cetuximab in 80 patients. The results of these studies define six clinically relevant CRC subtypes. Each subtype shares similarities to distinct cell types within the normal colon crypt and shows differing degrees of ‘stemness’ and Wnt signaling. Subtype-specific gene signatures are proposed to identify these subtypes. Three subtypes have markedly better disease-free survival (DFS) after surgical resection, suggesting these patients might be spared from the adverse effects of chemotherapy when they have localized disease. One of these three subtypes, identified by filamin A expression, does not respond to cetuximab but may respond to cMET receptor tyrosine kinase inhibitors in the metastatic setting. Two other subtypes, with poor and intermediate DFS, associate with improved response to the chemotherapy regimen FOLFIRI 1 in adjuvant or metastatic settings. Development of clinically deployable assays for these subtypes and of subtype-specific therapies may contribute to more effective management of this challenging disease. Previous studies have identified molecular subtypes of various human cancers by gene expression profiling 2–8 , including CRC subtypes 9,10 . However, these subtypes have not been associated with outcomes in patients treated with specific therapeutic interventions. Therefore, we sought to refine the approach of molecular classification of CRC by associating gene expression profiles of CRC tumors with corresponding clinical response to cetuximab. We first used consensusbased non-negative matrix factorization (NMF) 11 to cluster two published gene expression data sets (GSE13294 (ref. 12) and GSE14333 (ref. 13)) derived from resected primary CRCs (core data sets, n = 445). These data were corrected for batch effects and merged using the distance-weighted discrimination method 5,14 before clustering. This analysis defined five distinct high-consensus molecular subtypes of CRC (Supplementary Fig. 1a–e and Supplementary Results and

/pdf/a-colorectal-cancer-classification-system-that-associates-1u2ps2l7mt.pdf

Liliane C Gonzalez Ostos

Papers

A colorectal cancer classification system that associates cellular phenotype and responses to therapy