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Gene Expression Programs of Human Smooth Muscle Cells: Tissue-Specific Differentiation and Prognostic Significance in Breast Cancers

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  • Jen-Tsan Chi
  • Edwin H Rodriguez
  • Zhen Wang
  • Dimitry S A Nuyten
  • Sayan Mukherjee
  • Matt van de Rijn
  • Marc J van de Vijver
  • Trevor Hastie
  • Patrick O Brown

Abstract

Smooth muscle is present in a wide variety of anatomical locations, such as blood vessels, various visceral organs, and hair follicles. Contraction of smooth muscle is central to functions as diverse as peristalsis, urination, respiration, and the maintenance of vascular tone. Despite the varied physiological roles of smooth muscle cells (SMCs), we possess only a limited knowledge of the heterogeneity underlying their functional and anatomic specializations. As a step toward understanding the intrinsic differences between SMCs from different anatomical locations, we used DNA microarrays to profile global gene expression patterns in 36 SMC samples from various tissues after propagation under defined conditions in cell culture. Significant variations were found between the cells isolated from blood vessels, bronchi, and visceral organs. Furthermore, pervasive differences were noted within the visceral organ subgroups that appear to reflect the distinct molecular pathways essential for organogenesis as well as those involved in organ-specific contractile and physiological properties. Finally, we sought to understand how this diversity may contribute to SMC-involving pathology. We found that a gene expression signature of the responses of vascular SMCs to serum exposure is associated with a significantly poorer prognosis in human cancers, potentially linking vascular injury response to tumor progression.: It has been estimated that the human body contains approximately 200–400 distinct cell types. These estimates are largely based on the morphological characteristics of cells and have yielded, among many others, the category of smooth muscle cells, which have a distinct appearance and are present in a wide variety of tissues. By using DNA microarrays to interrogate the gene expression of anatomically varying smooth muscle cells, we were able to accurately tease apart many of the distinct cell subtypes that are classically categorized as smooth muscle cells. Remarkably, genes expressed by these newly identified, distinct subtypes corroborate many of their known biological properties and give clues about their susceptibility to specific disease states, retained developmental programs, and potential drugable targets. Additionally, from a smooth muscle cell model of vascular injury, we were able to extract a gene expression signature that provides prognostic information for human breast cancers. Of particular interest for modeling tumor progression was the finding that this gene expression signature was associated with tumor hypoxia. This study adds much to our ever-growing depth of understanding of cellular diversity and the contributions of this diversity to normal physiology and disease.

Suggested Citation

  • Jen-Tsan Chi & Edwin H Rodriguez & Zhen Wang & Dimitry S A Nuyten & Sayan Mukherjee & Matt van de Rijn & Marc J van de Vijver & Trevor Hastie & Patrick O Brown, 2007. "Gene Expression Programs of Human Smooth Muscle Cells: Tissue-Specific Differentiation and Prognostic Significance in Breast Cancers," PLOS Genetics, Public Library of Science, vol. 3(9), pages 1-15, September.
  • Handle: RePEc:plo:pgen00:0030164
    DOI: 10.1371/journal.pgen.0030164
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    1. Beatriz Estrada & Sung E Choe & Stephen S Gisselbrecht & Sebastien Michaud & Lakshmi Raj & Brian W Busser & Marc S Halfon & George M Church & Alan M Michelson, 2006. "An Integrated Strategy for Analyzing the Unique Developmental Programs of Different Myoblast Subtypes," PLOS Genetics, Public Library of Science, vol. 2(2), pages 1-12, February.
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    Cited by:

    1. Ying Li & Nan Wang & Edward J Perkins & Chaoyang Zhang & Ping Gong, 2010. "Identification and Optimization of Classifier Genes from Multi-Class Earthworm Microarray Dataset," PLOS ONE, Public Library of Science, vol. 5(10), pages 1-9, October.

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