Gene Expression Signature of Fibroblast Serum Response Predicts Human Cancer Progression: Similarities between Tumors and Wounds

By Howard Y. Chang, Julie B. Sneddon, Ash A. Alizadeh, R. Sood, Robert B. West, K. Montgomery, J. Chi, M. van de Rijn, David Botstein, Patrick O. Brown. PLoS Biology, 2004

979 citations recorded by the source corpus.

Cancer invasion and metastasis have been likened to wound healing gone awry. Despite parallels in cellular behavior between cancer progression and wound healing, the molecular relationships between these two processes and their prognostic implications are unclear. In this study, based on gene expression profiles of fibroblasts from ten anatomic sites, we identify a stereotyped gene expression program in response to serum exposure that appears to reflect the multifaceted role of fibroblasts in wound healing. The genes comprising this fibroblast common serum response are coordinately regulated in many human tumors, allowing us to identify tumors with gene expression signatures suggestive of active wounds. Genes induced in the fibroblast serum-response program are expressed in tumors by the tumor cells themselves, by tumor-associated fibroblasts, or both. The molecular features that define this wound-like phenotype are evident at an early clinical stage, persist during treatment, and predict increased risk of metastasis and death in breast, lung, and gastric carcinomas. Thus, the transcriptional signature of the response of fibroblasts to serum provides a possible link between cancer progression and wound healing, as well as a powerful predictor of the clinical course in several common carcinomas.

Subfields: Biotechnology, Oncology, Rehabilitation

View Paper: https://www.semanticscholar.org/paper/04104a9e607ffa615dc5163af2a52ed925c0bf9f

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Citations in the corpus

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Module map of stem cell genes guides creation of epithelial cancer stem cells. (2008, background): “We therefore determined the contribution of genes directly related to proliferation as well as exposure to serum in culture (Chang et al., 2004; Whitfield et al., 2002).”
Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer (2018, methodology): “, 2014), and wound healing (Chang et al., 2004), robustly reproduced co-clustering of the immune signature sets, and were selected to perform cluster analysis of all cancer types, with the exception of hematologic neoplasias (acute myeloid leukemia, LAML; diffuse large B cell lymphoma, DLBC; and thy”
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