Radiation and drug resistance are significant challenges in the treatment of locally advanced, recurrent and metastatic breast cancer that contribute to mortality. Clinically, radiotherapy requires oxygen to generate cytotoxic free radicals that cause DNA damage and allow that damage to become fixed in the genome rather than repaired. However, approximately 40% of all breast cancers have hypoxic tumor microenvironments that render cancer cells significantly more resistant to irradiation. Hypoxic stimuli trigger changes in the cell death/survival pathway that lead to increased cellular radiation resistance. As a result, the development of noninvasive strategies to assess tumor hypoxia in breast cancer has recently received considerable attention. Exosomes are secreted nanovesicles that have roles in paracrine signaling during breast tumor progression, including tumor-stromal interactions, activation of proliferative pathways and immunosuppression. The recent development of protocols to isolate and purify exosomes, as well as advances in mass spectrometry-based proteomics have facilitated the comprehensive analysis of exosome content and function. Using these tools, studies have demonstrated that the proteome profiles of tumor-derived exosomes are indicative of the oxygenation status of patient tumors. They have also demonstrated that exosome signaling pathways are potentially targetable drivers of hypoxia-dependent intercellular signaling during tumorigenesis. This article provides an overview of how proteomic tools can be effectively used to characterize exosomes and elucidate fundamental signaling pathways and survival mechanisms underlying hypoxia-mediated radiation resistance in breast cancer.
Exosomal Proteome Profiling: A Potential Multi-Marker Cellular Phenotyping Tool to Characterize Hypoxia-Induced Radiation Resistance in Breast Cancer
Stefani N. Thomas,Zhongping Liao,David Clark,Yangyi Chen,R. Samadani,L. Mao,D. Ann,J. Baulch,P. Shapiro,A. Yang
Published 2013 in Proteomes
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- Publication year
2013
- Venue
Proteomes
- Publication date
2013-08-09
- Fields of study
Biology, Medicine
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- External record
- Source metadata
Semantic Scholar, PubMed
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