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 FOLFIRI1 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.
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We thank P. Schulz (Charité, Universitätsmedizin) for providing RNA from xenograft tumors and for comments of the manuscript. We thank R.A. Du Pasquier (CHUV) for providing the HT29 cell line, P. Depeille (University of California–San Francisco) for the SW480, SW48, HCT8, LS174T and SW948 cell lines, and H. Ying (MD Anderson Medical Center) for the NCI-H508, LS1034, SW620, COLO320, SW1417, HCT116, RKO and DLD1 cell lines. The TOP/FOP-flash and Renilla constructs were a generous gift from S. Kobayashi (Beth Israel Deaconess Medical Center). We particularly acknowledge G. Poulogiannis for insightful feedback and assistance with statistical analysis of survival data. We also thank C. Fuerer, S.S. Sidhu, J. Yun and N. Divorne-Formenton for advice on the experimental design, C.R. Thomas for help with editing the manuscript, the Histology Core Facility of EPFL for help with immunohistochemistry. A.S. was partially supported by a US Department of Defense Postdoctoral Fellowship (BC087768). C.A.L. is the Amgen Fellow of the Damon Runyon Cancer Research Foundation (DRG-2056-10). J.W.G. is supported by the US National Institutes of Health grant U54 CA 112970 and by the Stand Up To Cancer–AACR Dream Team Translational Cancer Research Grant SU2C-AACR-DT0409. This work was supported by a Swiss National Science Foundation project grant awarded to D.H.
A.S., C.A.L., J.W.G. and D.H. have filed a priority patent application (PCT/IB2012/056728) entitled "Colorectal cancer classification with differential prognosis and personalized therapeutic responses" at the EPFL Technology Transfer Office, and the priority patent is on the CRCassigner signatures and their use for decision making for colorectal cancer therapy. W.J.G. is an employee of Genomic Health. L.C.C. owns equity in, receives compensation from Agios Pharmaceuticals, and serves on the Board of Directors and Scientific Advisory Board of Agios Pharmaceuticals. Agios Pharmaceuticals is identifying metabolic pathways of cancer cells and developing drugs to inhibit such enzymes in order to disrupt tumor cell growth and survival.
Supplementary Figures 1–8, Supplementary Discussion and Supplementary Methods (PDF 26895 kb)
Results from SAM and PAM analysis, the list of genes associated with each subtype and qRT-PCR and IHC assays (XLS 163 kb)
Summary of gene expression profile data sets used (XLS 274 kb)
Clinical/histopathological, subtype and statistical information for GSE14333 samples (XLS 88 kb)
Khambata-Ford data set liver genes and PCR primers (XLSX 54 kb)
R scripts (PDF 32 kb)
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Sadanandam, A., Lyssiotis, C., Homicsko, K. et al. A colorectal cancer classification system that associates cellular phenotype and responses to therapy. Nat Med 19, 619–625 (2013). https://doi.org/10.1038/nm.3175