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Proteomic workflow for analysis of archival formalin-fixed and paraffin-embedded clinical samples to a depth of 10 000 proteins

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons78895

Wisniewski,  Jacek R.
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons77918

Dus,  Kamila
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons78356

Mann,  Matthias
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Zitation

Wisniewski, J. R., Dus, K., & Mann, M. (2013). Proteomic workflow for analysis of archival formalin-fixed and paraffin-embedded clinical samples to a depth of 10 000 proteins. PROTEOMICS - Clinical Applications. Special Issue: Proteomic Analysis of Formalin Fixed Tissue, 7(3-4), 225-233. doi:10.1002/prca.201200046.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0014-113E-9
Zusammenfassung
Purpose: Archival formalin-fixed and paraffin-embedded clinical samples represent a very diverse source of material for proteomic investigation of diseases, often with follow-up patient information. Here, we describe an analytical workflow for analysis of laser-capture microdissected formalin-fixed and paraffin-embedded samples that allows studying proteomes to a depth of 10 000 proteins per sample. Experimental design: The workflow involves lysis of tissue in SDS-containing buffer, detergent removal, and consecutive digestion of the proteins with two enzymes by the multienzyme digestion filter-aided sample preparation method. Resulting peptides are fractionated by pipette-tip based strong anion exchange into six fractions and analyzed by LC-MS/MS on a bench top quadrupole Orbitrap mass spectrometer. Results: Analysis of the data using the MaxQuant software resulted in the identification of 9502 +/- 28 protein groups per a 110 nL sample of microdissected cells from human colonic adenoma. This depth of proteome analysis enables systemic insights into the organization of the adenoma cells and an estimation of the abundances of known biomarkers. It also allows the identification of proteins expressed from tumor suppressors, oncogenes, and other key players in the development and progression of the colorectal cancer. Conclusion and clinical relevance: Our proteomic platform can be used for quantitative comparisons between samples representing different stages of diseases and thus can be applied to the discovery of biomarkers or drug targets.