Abstract
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.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Andre, T. et al. CPT-11 (irinotecan) addition to bimonthly, high-dose leucovorin and bolus and continuous-infusion 5-fluorouracil (FOLFIRI) for pretreated metastatic colorectal cancer. GERCOR. Eur. J. Cancer 35, 1343–1347 (1999).
Verhaak, R.G. et al. Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 17, 98–110 (2010).
Markert, E.K., Mizuno, H., Vazquez, A. & Levine, A.J. Molecular classification of prostate cancer using curated expression signatures. Proc. Natl. Acad. Sci. USA 108, 21276–21281 (2011).
Perou, C.M. et al. Molecular portraits of human breast tumours. Nature 406, 747–752 (2000).
Collisson, E.A. et al. Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy. Nat. Med. 17, 500–503 (2011).
The Cancer Genome Atlas Research Network. Integrated genomic analyses of ovarian carcinoma. Nature 474, 609–615 (2011).
Alizadeh, A.A. et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 403, 503–511 (2000).
Tothill, R.W. et al. Novel molecular subtypes of serous and endometrioid cancer linked to clinical outcome. Clin. Cancer Res. 14, 5198–5208 (2008).
The Cancer Genome Atlas Research Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature 487, 330–337 (2012).
Perez Villamil, B. et al. Colon cancer molecular subtypes identified by expression profiling and associated to stroma, mucinous type and different clinical behavior. BMC Cancer 12, 260 (2012).
Brunet, J.P., Tamayo, P., Golub, T.R. & Mesirov, J.P. Metagenes and molecular pattern discovery using matrix factorization. Proc. Natl. Acad. Sci. USA 101, 4164–4169 (2004).
Jorissen, R.N. et al. DNA copy-number alterations underlie gene expression differences between microsatellite stable and unstable colorectal cancers. Clin. Cancer Res. 14, 8061–8069 (2008).
Jorissen, R.N. et al. Metastasis-associated gene expression changes predict poor outcomes in patients with Dukes stage B and C colorectal cancer. Clin. Cancer Res. 15, 7642–7651 (2009).
Benito, M. et al. Adjustment of systematic microarray data biases. Bioinformatics 20, 105–114 (2004).
Rousseeuw, P.J. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53–65 (1987).
Tusher, V.G., Tibshirani, R. & Chu, G. Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. USA 98, 5116–5121 (2001).
Tibshirani, R., Hastie, T., Narasimhan, B. & Chu, G. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc. Natl. Acad. Sci. USA 99, 6567–6572 (2002).
Dalerba, P. et al. Single-cell dissection of transcriptional heterogeneity in human colon tumors. Nat. Biotechnol. 29, 1120–1127 (2011).
Greshock, J. et al. Molecular target class is predictive of in vitro response profile. Cancer Res. 70, 3677–3686 (2010).
Barretina, J. et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483, 603–607 (2012).
Van Cutsem, E. & Oliveira, J. Primary colon cancer: ESMO clinical recommendations for diagnosis, adjuvant treatment and follow-up. Ann. Oncol. 20 (suppl. 4), 49–50 (2009).
Banerjea, A. et al. Colorectal cancers with microsatellite instability display mRNA expression signatures characteristic of increased immunogenicity. Mol. Cancer 3, 21 (2004).
Hoshida, Y. Nearest template prediction: a single-sample-based flexible class prediction with confidence assessment. PLoS ONE 5, e15543 (2010).
Humphries, A. & Wright, N.A. Colonic crypt organization and tumorigenesis. Nat. Rev. Cancer 8, 415–424 (2008).
Shih, I.M. et al. Top-down morphogenesis of colorectal tumors. Proc. Natl. Acad. Sci. USA 98, 2640–2645 (2001).
Schwitalla, S. et al. Intestinal tumorigenesis initiated by dedifferentiation and acquisition of stem-cell-like properties. Cell 152, 25–38 (2013).
Kosinski, C. et al. Gene expression patterns of human colon tops and basal crypts and BMP antagonists as intestinal stem cell niche factors. Proc. Natl. Acad. Sci. USA 104, 15418–15423 (2007).
Vermeulen, L. et al. Wnt activity defines colon cancer stem cells and is regulated by the microenvironment. Nat. Cell Biol. 12, 468–476 (2010).
Cunningham, D. et al. Cetuximab monotherapy and cetuximab plus irinotecan in irinotecan-refractory metastatic colorectal cancer. N. Engl. J. Med. 351, 337–345 (2004).
De Roock, W. et al. KRAS wild-type state predicts survival and is associated to early radiological response in metastatic colorectal cancer treated with cetuximab. Ann. Oncol. 19, 508–515 (2008).
Ogino, S. et al. KRAS mutation in stage III colon cancer and clinical outcome following intergroup trial CALGB 89803. Clin. Cancer Res. 15, 7322–7329 (2009).
Khambata-Ford, S. et al. Expression of epiregulin and amphiregulin and K-ras mutation status predict disease control in metastatic colorectal cancer patients treated with cetuximab. J. Clin. Oncol. 25, 3230–3237 (2007).
Zhou, A.X. et al. Filamin a mediates HGF/c-MET signaling in tumor cell migration. Int. J. Cancer 128, 839–846 (2011).
Del Rio, M. et al. Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan. J. Clin. Oncol. 25, 773–780 (2007).
Graudens, E. et al. Deciphering cellular states of innate tumor drug responses. Genome Biol. 7, R19 (2006).
Heiser, L.M. et al. Subtype and pathway specific responses to anticancer compounds in breast cancer. Proc. Natl. Acad. Sci. USA 109, 2724–2729 (2012).
Van Cutsem, E. et al. Randomized phase III trial comparing biweekly infusional fluorouracil/leucovorin alone or with irinotecan in the adjuvant treatment of stage III colon cancer: PETACC-3. J. Clin. Oncol. 27, 3117–3125 (2009).
Pao, W. & Girard, N. New driver mutations in non-small-cell lung cancer. Lancet Oncol. 12, 175–180 (2011).
Acknowledgements
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.
Author information
Authors and Affiliations
Contributions
A.S. conceived of the hypothesis, designed and performed experiments, interpreted results and co-wrote the manuscript. C.A.L., K.H., S.W., L.C.G.O., W.A.L. and C.G. performed experiments. M.D.R. provided CRC microarray data with FOLFIRI response data. B.L. provided pathology expertise, and A.B.O. provided statistical expertise. C.A.L., K.H., E.A.C., W.J.G., L.C.C. and B.W. participated in critical discussions and helped edit the manuscript. J.W.G. interpreted results, helped edit the manuscript, and co-supervised the project. D.H. co-supervised the project, interpreted results and co-wrote the manuscript.
Corresponding authors
Ethics declarations
Competing interests
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 information
Supplementary Text and Figures
Supplementary Figures 1–8, Supplementary Discussion and Supplementary Methods (PDF 26895 kb)
Supplementary Table 1
Results from SAM and PAM analysis, the list of genes associated with each subtype and qRT-PCR and IHC assays (XLS 163 kb)
Supplementary Table 2
Summary of gene expression profile data sets used (XLS 274 kb)
Supplementary Table 3
Clinical/histopathological, subtype and statistical information for GSE14333 samples (XLS 88 kb)
Supplementary Table 4
Khambata-Ford data set liver genes and PCR primers (XLSX 54 kb)
Supplementary Data
R scripts (PDF 32 kb)
Rights and permissions
About this article
Cite this article
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
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/nm.3175
