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  Quantitative mass spectrometric profiling of cancer-cell proteomes derived from liquid and solid tumors.

Bohnenberger, H., Ströbel, P., Mohr, S., Corso, J., Berg, T., Urlaub, H., et al. (2015). Quantitative mass spectrometric profiling of cancer-cell proteomes derived from liquid and solid tumors. Journal of Visualized Experiments, 96: e52435. doi:10.3791/52435.

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 Urheber:
Bohnenberger, H., Autor
Ströbel, P., Autor
Mohr, S., Autor
Corso, J.1, Autor           
Berg, T., Autor
Urlaub, H.1, Autor           
Lenz, C.1, Autor           
Serve, H., Autor
Oellerich, T., Autor
Affiliations:
1Research Group of Bioanalytical Mass Spectrometry, MPI for Biophysical Chemistry, Max Planck Society, ou_578613              

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 Zusammenfassung: In-depth analyses of cancer cell proteomes are needed to elucidate oncogenic pathomechanisms, as well as to identify potential drug targets and diagnostic biomarkers. However, methods for quantitative proteomic characterization of patient-derived tumors and in particular their cellular subpopulations are largely lacking. Here we describe an experimental set-up that allows quantitative analysis of proteomes of cancer cell subpopulations derived from either liquid or solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry followed by bioinformatic data analysis. To enrich specific cellular subsets, liquid tumors are first immunophenotyped by flow cytometry followed by FACS-sorting; for solid tumors, laser-capture microdissection is used to purify specific cellular subpopulations. In a second step, proteins are extracted from the purified cells and subsequently combined with a tumor-specific, SILAC-labeled spike-in standard that enables protein quantification. The resulting protein mixture is subjected to either gel electrophoresis or Filter Aided Sample Preparation (FASP) followed by tryptic digestion. Finally, tryptic peptides are analyzed using a hybrid quadrupole-orbitrap mass spectrometer, and the data obtained are processed with bioinformatic software suites including MaxQuant. By means of the workflow presented here, up to 8,000 proteins can be identified and quantified in patient-derived samples, and the resulting protein expression profiles can be compared among patients to identify diagnostic proteomic signatures or potential drug targets.

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Sprache(n): eng - English
 Datum: 2015-02-27
 Publikationsstatus: Online veröffentlicht
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 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.3791/52435
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Titel: Journal of Visualized Experiments
Genre der Quelle: Zeitschrift
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Seiten: 8 Band / Heft: 96 Artikelnummer: e52435 Start- / Endseite: - Identifikator: -