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Characterization of the Extracellular Matrix of Normal and Diseased Tissues Using Proteomics

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Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, United Kingdom
§ Proteomics Core Facility, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
Bioinformatics and Computing Facility, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
*A.N.: E-mail: [email protected]. Tel: +1 312-355-5417.
*O.M.T.P.: E-mail: [email protected]. Tel: +44 (0) 207882 3591.
Cite this: J. Proteome Res. 2017, 16, 8, 3083–3091
Publication Date (Web):July 4, 2017
https://doi.org/10.1021/acs.jproteome.7b00191
Copyright © 2017 American Chemical Society

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    Abstract

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    The extracellular matrix (ECM) is a complex meshwork of insoluble fibrillar proteins and signaling factors interacting together to provide architectural and instructional cues to the surrounding cells. Alterations in ECM organization or composition and excessive ECM deposition have been observed in diseases such as fibrosis, cardiovascular diseases, and cancer. We provide here optimized protocols to solubilize ECM proteins from normal or tumor tissues, digest the proteins into peptides, analyze ECM peptides by mass spectrometry, and interpret the mass spectrometric data. In addition, we present here two novel R-script-based web tools allowing rapid annotation and relative quantification of ECM proteins, peptides, and intensity/abundance in mass spectrometric data output files. We illustrate this protocol with ECMs obtained from two pairs of tissues, which differ in ECM content and cellularity: triple-negative breast cancer and adjacent mammary tissue, and omental metastasis from high-grade serous ovarian cancer and normal omentum. The complete proteomics data set generated in this study has been deposited to the public repository ProteomeXchange with the data set identifier: PXD005554.

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    The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jproteome.7b00191.

    • Supplementary Figure S1: Composition of urea-insoluble protein samples. (PDF)

    • Supplementary Table S1: Complete mass spectrometry data set. (XLSX)

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