Evidence map›Paper›PMID 28319088›Full record

ArticleNature genetics2017

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 and 7 more

Erratum issuedAbstract read
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In one paragraph

Article in Nature genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 662 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
662citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

662 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. scCADI: Cell-Aware Diffusion Model for Single-Cell RNA-seq Imputation.Interdisciplinary sciences, computational life sciences · 2026
    Article
  3. Article
  4. Review
  5. Adversarial random forests for omics synthesis.bioRxiv : the preprint server for biology · 2026
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602 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Huipeng LiComputational and Systems Biology, Genome Institute of Singapore, Singapore.
Elise T CourtoisComputational and Systems Biology, Genome Institute of Singapore, Singapore.ORCID http://orcid.org/0000-0002-8749-2719
Debarka SenguptaComputational and Systems Biology, Genome Institute of Singapore, Singapore.
Yuliana TanComputational and Systems Biology, Genome Institute of Singapore, Singapore.
Kok Hao ChenSynthetic Biology, Genome Institute of Singapore, Singapore.
Jolene Jie Lin GohSynthetic Biology, Genome Institute of Singapore, Singapore.
Say Li KongCancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore.
Clarinda ChuaDepartment of Medical Oncology, National Cancer Centre Singapore, Singapore.
Lim Kiat HonDepartment of Pathology, Singapore General Hospital, Singapore.
Wah Siew TanDepartment of Colorectal Surgery, Singapore General Hospital, Singapore.
Mark WongDepartment of Colorectal Surgery, Singapore General Hospital, Singapore.
Paul Jongjoon ChoiSynthetic Biology, Genome Institute of Singapore, Singapore.
Lawrence J K WeeData Analytics Department, Institute for Infocomm Research, Singapore.
Axel M HillmerCancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore.ORCID http://orcid.org/0000-0002-3381-7266
Iain Beehuat TanCancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore.
Paul RobsonDevelopmental Cellomics Laboratory, Genome Institute of Singapore, Singapore.ORCID http://orcid.org/0000-0002-0191-3958
Shyam PrabhakarComputational and Systems Biology, Genome Institute of Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Gene Expression Regulation, NeoplasticTranscriptomeA549 CellsAlgorithmsCell LineCell Line, TumorCluster AnalysisColorectal NeoplasmsEpithelial-Mesenchymal TransitionFibroblastsGene Expression ProfilingGenetic HeterogeneityHumansImmunohistochemistryIn Situ Hybridization, FluorescenceK562 Cells

Identifiers

PMID28319088

What OpenQuestion holds

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Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.