The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
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Hynes_The Matrisome.pdf
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Author(s)
Naba, Alexandra
Clauser, Karl R.
Hoersch, Sebastian
Liu, Hui
Carr, Steven A
Hynes, Richard O
Date Issued
December 2011
Journal
Molecular and Cellular Proteomics
Publisher
American Society for Biochemistry and Molecular Biology
Citation
Naba, A. et al. “The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices.” Molecular & Cellular Proteomics 11.4 (2011): M111.014647–M111.014647. Web.
Version
Final published version
Abstract
The extracellular matrix (ECM) is a complex meshwork of cross-linked proteins providing both biophysical and biochemical cues that are important regulators of cell proliferation, survival, differentiation, and migration. We present here a proteomic strategy developed to characterize the in vivo ECM composition of normal tissues and tumors using enrichment of protein extracts for ECM components and subsequent analysis by mass spectrometry. In parallel, we have developed a bioinformatic approach to predict the in silico “matrisome” defined as the ensemble of ECM proteins and associated factors. We report the characterization of the extracellular matrices of murine lung and colon, each comprising more than 100 ECM proteins and each presenting a characteristic signature. Moreover, using human tumor xenografts in mice, we show that both tumor cells and stromal cells contribute to the production of the tumor matrix and that tumors of differing metastatic potential differ in both the tumor- and the stroma-derived ECM components. The strategy we describe and illustrate here can be broadly applied and, to facilitate application of these methods by others, we provide resources including laboratory protocols, inventories of ECM domains and proteins, and instructions for bioinformatically deriving the human and mouse matrisome.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Koch Institute for Integrative Cancer Research at MIT
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1074/mcp.M111.014647
