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 (CMS) with distinguishing features: CMS1 (MSI Immune, 14%), hypermutated, microsatellite unstable, strong immune activation; CMS2 (Canonical, 37%), epithelial, chromosomally unstable, marked WNT and MYC signaling activation; CMS3 (Metabolic, 13%), epithelial, 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 intra-tumoral 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.

We introduce the Microenvironment Cell Populations-counter (MCP-counter) method, which allows the robust quantification of the absolute abundance of eight immune and two stromal cell populations in heterogeneous tissues from transcriptomic data. We present in vitro mRNA mixture and ex vivo immunohistochemical data that quantitatively support the validity of our method’s estimates. Additionally, we demonstrate that MCP-counter overcomes several limitations or weaknesses of previously proposed computational approaches. MCP-counter is applied to draw a global picture of immune infiltrates across human healthy tissues and non-hematopoietic human tumors and recapitulates microenvironment-based patient stratifications associated with overall survival in lung adenocarcinoma and colorectal and breast cancer.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1070-5) contains supplementary material, which is available to authorized users.

BackgroundColon cancer (CC) pathological staging fails to accurately predict recurrence, and to date, no gene expression signature has proven reliable for prognosis stratification in clinical practice, perhaps because CC is a heterogeneous disease. The aim of this study was to establish a comprehensive molecular classification of CC based on mRNA expression profile analyses.Methods and FindingsFresh-frozen primary tumor samples from a large multicenter cohort of 750 patients with stage I to IV CC who underwent surgery between 1987 and 2007 in seven centers were characterized for common DNA alterations, including BRAF, KRAS, and TP53 mutations, CpG island methylator phenotype, mismatch repair status, and chromosomal instability status, and were screened with whole genome and transcriptome arrays. 566 samples fulfilled RNA quality requirements. Unsupervised consensus hierarchical clustering applied to gene expression data from a discovery subset of 443 CC samples identified six molecular subtypes. These subtypes were associated with distinct clinicopathological characteristics, molecular alterations, specific enrichments of supervised gene expression signatures (stem cell phenotype–like, normal-like, serrated CC phenotype–like), and deregulated signaling pathways. Based on their main biological characteristics, we distinguished a deficient mismatch repair subtype, a KRAS mutant subtype, a cancer stem cell subtype, and three chromosomal instability subtypes, including one associated with down-regulated immune pathways, one with up-regulation of the Wnt pathway, and one displaying a normal-like gene expression profile. The classification was validated in the remaining 123 samples plus an independent set of 1,058 CC samples, including eight public datasets. Furthermore, prognosis was analyzed in the subset of stage II–III CC samples. The subtypes C4 and C6, but not the subtypes C1, C2, C3, and C5, were independently associated with shorter relapse-free survival, even after adjusting for age, sex, stage, and the emerging prognostic classifier Oncotype DX Colon Cancer Assay recurrence score (hazard ratio 1.5, 95% CI 1.1–2.1, p = 0.0097). However, a limitation of this study is that information on tumor grade and number of nodes examined was not available.ConclusionsWe describe the first, to our knowledge, robust transcriptome-based classification of CC that improves the current disease stratification based on clinicopathological variables and common DNA markers. The biological relevance of these subtypes is illustrated by significant differences in prognosis. This analysis provides possibilities for improving prognostic models and therapeutic strategies. In conclusion, we report a new classification of CC into six molecular subtypes that arise through distinct biological pathways. Please see later in the article for the Editors' Summary

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Hepatocellular carcinomas (HCCs) are a heterogeneous group of tumors that differ in risk factors and genetic alterations. We further investigated transcriptome-genotype-phenotype correlations in HCC. Global transcriptome analyses were performed on 57 HCCs and 3 hepatocellular adenomas and validated by quantitative RT-PCR using 63 additional HCCs. We determined loss of heterozygosity, gene mutations, promoter methylation of CDH1 and CDKN2A, and HBV DNA copy number for each tumor. Unsupervised transcriptome analysis identified 6 robust subgroups of HCC (G1-G6) associated with clinical and genetic characteristics. G1 tumors were associated with low copy number of HBV and overexpression of genes expressed in fetal liver and controlled by parental imprinting. G2 included HCCs infected with a high copy number of HBV and mutations in PIK3CA and TP53. In these first groups, we detected specific activation of the AKT pathway. G3 tumors were typified by mutation of TP53 and overexpression of genes controlling the cell cycle. G4 was a heterogeneous subgroup of tumors including TCF1-mutated hepatocellular adenomas and carcinomas. G5 and G6 were strongly related to ␤-catenin mutations that lead to Wnt pathway activation; in particular, G6 tumors were characterized by satellite nodules, higher activation of the Wnt pathway, and Ecadherin underexpression. Conclusion: These results have furthered our understanding of the genetic diversity of human HCC and have provided specific identifiers for classifying tumors. In addition, our classification has potential therapeutic implications because 50% of the tumors were related to WNT or AKT pathway activation, which potentially could be targeted by specific inhibiting therapies. (HEPATOLOGY 2007;45:42-52.) H epatocellular carcinoma (HCC) is one of the most frequently occurring solid tumors worldwide and is the third-leading cause of death from cancer. 1 Cirrhosis of any origin and dysplastic regenerative nodules have long been considered the likely precursors of HCC because of their frequent association with HCC occurrence. 2,3 As in other solid tumors, a large number of genetic alterations accumulate during the carcinogenetic process. Some of these genetic alterations are specific to HCC etiological risk factors, particularly HBV infection, which can induce chromosome instability or insertional mutagenesis. 4 Among the genetic alterations unrelated to HCC risk factors, microsatellite allelotypes and comparative genomic hybridization (CGH) studies have demonstrated recurrent chromosome aberrations. 5 Altogether, the principal carcinogenetic pathways known to be deregulated in HCC are inactivation of TP53, 6 Wnt/wingless activation mainly through CTNNB1 mutations activating ␤-catenin-and AXIN1-inactivating mutations, 7-9 retinoblastoma inactivation through RB1 and CDKN2A promoter methylation and rare gene mu-