Title |
Stable Isotope Dynamic Labeling of Secretomes (SIDLS) Identifies Authentic Secretory Proteins Released by Cancer and Stromal Cells*
|
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Published in |
Molecular and Cellular Proteomics, June 2018
|
DOI | 10.1074/mcp.tir117.000516 |
Pubmed ID | |
Authors |
Dean E. Hammond, J. Dinesh Kumar, Lorna Raymond, Deborah M. Simpson, Robert J. Beynon, Graham J. Dockray, Andrea Varro |
Abstract |
Analysis of secretomes critically underpins the capacity to understand the mechanisms determining interactions between cells and between cells and their environment. In the context of cancer cell micro-environments, the relevant interactions are recognised to be an important determinant of tumor progression. Global proteomic analyses of secretomes are often performed at a single time point and frequently identify both classical secreted proteins (possessing an N-terminal signal sequence), as well as many intracellular proteins, the release of which is of uncertain biological significance. Here, we describe a mass spectrometry-based method for stable isotope dynamic labeling of secretomes (SIDLS) that, by dynamic SILAC, discriminates the secretion kinetics of classical secretory proteins and intracellular proteins released from cancer and stromal cells in culture. SIDLS is a robust classifier of the different cellular origins of proteins within the secretome and should be broadly applicable to non-proliferating cells and cells grown in short term culture. |
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Geographical breakdown
Country | Count | As % |
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United Kingdom | 5 | 22% |
United States | 3 | 13% |
India | 2 | 9% |
Canada | 1 | 4% |
Myanmar | 1 | 4% |
France | 1 | 4% |
Spain | 1 | 4% |
Unknown | 9 | 39% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 15 | 65% |
Scientists | 6 | 26% |
Science communicators (journalists, bloggers, editors) | 1 | 4% |
Practitioners (doctors, other healthcare professionals) | 1 | 4% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 31 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 4 | 13% |
Student > Bachelor | 3 | 10% |
Researcher | 3 | 10% |
Student > Ph. D. Student | 3 | 10% |
Student > Postgraduate | 2 | 6% |
Other | 3 | 10% |
Unknown | 13 | 42% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 7 | 23% |
Agricultural and Biological Sciences | 6 | 19% |
Medicine and Dentistry | 2 | 6% |
Chemistry | 1 | 3% |
Unknown | 15 | 48% |