Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors
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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Macrophages and dendritic cells have similar transcriptomic profiles.
“Because macrophages and dendritic cells have similar transcriptomic profiles23–25, we repeated SingleR analysis using published RNA-seq datasets of mouse lung macrophages and dendritic cells26,27 to isolate the macrophages”
From Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage (2019) · cites this paper as [23]
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- Authors
- Li, H., Courtois, E. T., Sengupta, D., Tan, Y., Chen, K. H., Goh, J. J. L., Kong, S. L., Chua, C., Hon, L. K., Tan, W. S., Wong, M., Choi, P. J., Wee, L. J. K., Hillmer, A. M., Tan, I. B., Robson, P., & Prabhakar, S.
- Affiliations
- Genome Institute of Singapore (SG)
- Indraprastha Institute of Information Technology Delhi (IN)
- National Cancer Centre Singapore (SG)
- Singapore General Hospital (SG)
- Institute for Infocomm Research (SG)
- Duke-NUS Medical School (SG)
- University of Connecticut (US)
- Corresponding author
- Tan, Iain Beehuat
- Robson, Paul
- Prabhakar, Shyam
- ORCID
- Venue
- Nature Genetics
- Published
- 2017-03-20
- Volume
- 49
- Issue
- 5
- Pages
- 708-718
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- OpenAlex
- W2600453489
- Cited by
- 1,080
- References
- 55
- Citations by year
- 2026: 50 · 2025: 86 · 2024: 128 · 2023: 146 · 2022: 152 · 2021: 163 · 2020: 154 · 2019: 102 · 2018: 75 · 2017: 20 · 2014: 1
- FWCI
- 39.30
- Type
- journal article
- Language
- en
- Update notices
- Open access
- closed
- Licence
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- colorectal cancer, intratumoral heterogeneity, cancer-associated fibroblasts, tumor microenvironment, epithelial-mesenchymal transition, single-cell transcriptomics, tumor subtypes
- MeSH terms
- A549 Cells, Algorithms, Cell Line, Fibroblasts, Humans, Immunohistochemistry, Prognosis, Colorectal Neoplasms, Gene Expression Regulation, Neoplastic, Cluster Analysis, Survival Analysis, In Situ Hybridization, Fluorescence, Sequence Analysis, RNA, Genetic Heterogeneity, K562 Cells, Gene Expression Profiling, Principal Component Analysis, Cell Line, Tumor, Epithelial-Mesenchymal Transition, Single-Cell Analysis, Transcriptome
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