Quantitative proteomic profiling of the extracellular matrix of pancreatic islets during the angiogenic switch and insulinoma progression
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Quantitative proteomic.pdf
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Author(s)
Clauser, Karl R.
Mani, D. R.
Carr, Steven A.
Naba, Alexandra
Hynes, Richard O.
Date Issued
January 2017
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Naba, Alexandra et al. “Quantitative Proteomic Profiling of the Extracellular Matrix of Pancreatic Islets during the Angiogenic Switch and Insulinoma Progression.” Scientific Reports 7 (2017): 40495.
Version
Final published version
Abstract
The angiogenic switch, the time at which a tumor becomes vascularized, is a critical step in tumor progression. Indeed, without blood supply, tumors will fail to grow beyond 1mm[superscript 3] and are unlikely to disseminate. The extracellular matrix (ECM), a major component of the tumor microenvironment, is known to undergo significant changes during angiogenesis and tumor progression. However the extent of these changes remains unknown. In this study, we used quantitative proteomics to profile the composition of the ECM of pancreatic islets in a mouse model of insulinoma characterized by a precisely timed angiogenic switch. Out of the 120 ECM proteins quantified, 35 were detected in significantly different abundance as pancreatic islets progressed from being hyperplastic to angiogenic to insulinomas. Among these, the core ECM proteins, EFEMP1, fibrillin 1, and periostin were found in higher abundance, and decorin, Dmbt1, hemicentin, and Vwa5 in lower abundance. The angiogenic switch being a common feature of solid tumors, we propose that some of the proteins identified represent potential novel anti-angiogenic targets. In addition, we report the characterization of the ECM composition of normal pancreatic islets and propose that this could be of interest for the design of tissue-engineering strategies for treatment of diabetes.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Koch Institute for Integrative Cancer Research at MIT
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Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1038/srep40495
