Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors

Huipeng Li, Elise T Courtois, Debarka Sengupta, Yuliana Tan, Kok Hao Chen, Jolene Jie Lin Goh, Say Li Kong, Clarinda Chua, Lim Kiat Hon, Wah Siew Tan, Mark Wong, Paul Jongjoon Choi, Lawrence JK Wee, Axel M Hillmer, Iain Beehuat Tan, Paul Robson, Shyam Prabhakar, Nature Genetics 49 (5) :708 (2017).
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Abstract

Intratumoral heterogeneity is a major obstacle to cancer treatment and a significant confounding factor in bulk-tumor profiling. We performed an unbiased analysis of transcriptional heterogeneity in colorectal tumors and their microenvironments using single-cell RNA–seq from 11 primary colorectal tumors and matched normal mucosa. To robustly cluster single-cell transcriptomes, we developed reference component analysis (RCA), an algorithm that substantially improves clustering accuracy. Using RCA, we identified two distinct subtypes of cancer-associated fibroblasts (CAFs). Additionally, epithelial–mesenchymal transition (EMT)-related genes were found to be upregulated only in the CAF subpopulation of tumor samples. Notably, colorectal tumors previously assigned to a single subtype on the basis of bulk transcriptomics could be divided into subgroups with divergent survival probability by using single-cell signatures, thus underscoring the prognostic value of our approach. Overall, our results demonstrate that unbiased single-cell RNA–seq profiling of tumor and matched normal samples provides a unique opportunity to characterize aberrant cell states within a tumor.