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.
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Change history
12 November 2018
In the version of the article published, the author list is not accurate. Igor Cima and Min-Han Tan should have been authors, appearing after Mark Wong in the author list, while Paul Jongjoon Choi should not have been listed as an author. Igor Cima and Min-Han Tan vboth have the affiliation Institute of Bioengineering and Nanotechnology, Singapore, Singapore, and their contributions should have been noted in the Author Contributions section as "I.C. preprocessed Primary Cell Atlas data with inputs from M.-H.T." The following description of the contribution of Paul Jongjoon Choi should not have appeared: "P.J.C. supported the smFISH experiments.” In the 'RCA: global panel' section of the Online Methods, the following sentence should have appeared as the second sentence, "An expression atlas of human primary cells (the Primary Cell Atlas) was preprocessed similarly to in ref. 55," with new reference 55 (Cima, I. et al. Tumor-derived circulating endothelial cell clusters in colorectal cancer. Science Transl. Med. 8, 345ra89, 2016).
19 December 2022
A Correction to this paper has been published: https://doi.org/10.1038/s41588-022-01281-y
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Acknowledgements
We would like to thank L. Suteja, C. Kang, S. Sudhagar, J. Sheik and M.N. Ramalingam for technical assistance, A. Brichkina (Institute of Molecular and Cell Biology, A*STAR) for providing the antibody to SMA, V. Sivakamasundari for guidance on single-cell protocols, M.H. Chew, R. Ten, W.J. Lim, J.H. Lai, C.Y. Ng and D. Koh for assistance with clinical sample collection, and Y. Hu, S. Ghosh, H. Kitano and D. Tan for feedback and scientific discussions. This study was supported by core funds from the Agency for Science, Technology and Research (A*STAR) and also by grant JCO1331CFG080 from A*STAR's Joint Council Office. P.R. acknowledges support from Agency of Science, Technology and Research grants IAF111091 and IAF111128 and associated in-kind contributions from industry partners Fluidigm Singapore and Becton Dickinson Holdings, respectively. S.L.K. and A.M.H. acknowledge the Strategic Positioning Fund (SPF2012/003) from the Biomedical Research Council (BMRC).
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H.L., E.T.C., L.J.K.W. I.B.T., P.R. and S.P. conceived the idea and designed the study. H.L. developed the computational algorithms and performed the bioinformatic analysis. E.T.C. optimized and conducted the experiments. D.S. assisted with the data analysis. Y.T. assisted with the experiments. J.J.L.G. and K.H.C. performed the smFISH experiments. S.L.K. assisted with the initial protocol validation. W.S.T. and L.K.H. extracted and preprocessed clinical samples and guided patient selection. C.C. coordinated the clinical sample registration, preprocessing and logistics. P.J.C. supported the smFISH experiments. A.H. provided guidance in experimental protocol design. H.L. and E.T.C. analyzed the data and interpreted the results. S.P. guided the development of computational algorithms. I.B.T., P.R. and S.P. provided guidance in data analysis and interpretation of the results. H.L., E.T.C., I.B.T., P.R. and S.P. wrote the manuscript.
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Supplementary Text and Figures
Supplementary Figures 1–16, Supplementary Tables 2 and 6, and Supplementary Note. (PDF 32896 kb)
Supplementary Table 1
Cell type annotation for the melanoma data set. (CSV 302 kb)
Supplementary Table 3
Differentially expressed genes between epithelial subtypes in normal mucosa. (XLSX 29 kb)
Supplementary Table 4
Cell-type-specific differentially expression analysis between normal mucosa and tumor. (XLSX 2195 kb)
Supplementary Table 5
Differentially expressed genes between bulk tumor and matched normal tissue (TCGA data). (CSV 2359 kb)
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Li, H., Courtois, E., Sengupta, D. et al. Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors. Nat Genet 49, 708–718 (2017). https://doi.org/10.1038/ng.3818
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DOI: https://doi.org/10.1038/ng.3818
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