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

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Abstract

Shyam Prabhakar, Paul Robson, Iain Beehuat Tan and colleagues characterize the cellular heterogeneity of colorectal tumors and their microenvironment on the basis of single-cell RNA–seq data analyzed with their newly developed clustering algorithm, reference component analysis (RCA). Their analyses identify two subtypes of cancer-associated fibroblasts and further divide tumors into subgroups with divergent survival probabilities.

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Dependency of colorectal cancer on a TGF-β-driven program in stromal cells for metastasis initiation.

Alexandre Calon, Elisa Espinet, Sergio Palomo-Ponce … (2012)

A large proportion of colorectal cancers (CRCs) display mutational inactivation of the TGF-β pathway, yet, paradoxically, they are characterized by elevated TGF-β production. Here, we unveil a prometastatic program induced by TGF-β in the microenvironment that associates with a high risk of CRC relapse upon treatment. The activity of TGF-β on stromal cells increases the efficiency of organ colonization by CRC cells, whereas mice treated with a pharmacological inhibitor of TGFBR1 are resilient to metastasis formation. Secretion of IL11 by TGF-β-stimulated cancer-associated fibroblasts (CAFs) triggers GP130/STAT3 signaling in tumor cells. This crosstalk confers a survival advantage to metastatic cells. The dependency on the TGF-β stromal program for metastasis initiation could be exploited to improve the diagnosis and treatment of CRC. Copyright © 2012 Elsevier Inc. All rights reserved.

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Single-cell dissection of transcriptional heterogeneity in human colon tumors

Piero Dalerba, Tomer Kalisky, Debashis Sahoo … (2011)

Cancer is often viewed as a caricature of normal developmental processes, but the extent by which its cellular heterogeneity truly recapitulates multi-lineage differentiation processes of normal tissues remains unknown. Here, we implement “single-cell PCR gene-expression analysis” (SINCE-PCR) to dissect the cellular composition of primary human normal colon and colon cancer epithelia. We show that human colon cancer tissues contain distinct cell populations whose transcriptional identities mirror those of the different cellular lineages of normal colon. By creating monoclonal tumor xenografts from injection of a single-cell (n = 1), we show that transcriptional diversity of cancer tissues is largely explained by in vivo multi-lineage differentiation, not only by clonal genetic heterogeneity. Finally, we show that perturbations in gene-expression programs linked to multi-lineage differentiation strongly associate with patient survival. Guided by SINCE-PCR data, we develop two-gene classifier systems (KRT20 vs CA1, MS4A12, CD177, SLC26A3) that predict clinical outcomes with hazard-ratios superior to pathological grade and comparable to microarray-derived multi-gene expression signatures.

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Exploring TCGA Pan-Cancer Data at the UCSC Cancer Genomics Browser

Melissa Cline, Brian Craft, Teresa Swatloski … (2013)

The UCSC Cancer Genomics Browser (https://genome-cancer.ucsc.edu) offers interactive visualization and exploration of TCGA genomic, phenotypic, and clinical data, as produced by the Cancer Genome Atlas Research Network. Researchers can explore the impact of genomic alterations on phenotypes by visualizing gene and protein expression, copy number, DNA methylation, somatic mutation and pathway inference data alongside clinical features, Pan-Cancer subtype classifications and genomic biomarkers. Integrated Kaplan–Meier survival analysis helps investigators to assess survival stratification by any of the information.