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The advantage of laser-capture microdissection over whole tissue analysis in proteomic profiling studies.

Authors :
De Marchi T
Braakman RB
Stingl C
van Duijn MM
Smid M
Foekens JA
Luider TM
Martens JW
Umar A
Source :
Proteomics [Proteomics] 2016 May; Vol. 16 (10), pp. 1474-85. Date of Electronic Publication: 2016 Apr 28.
Publication Year :
2016

Abstract

Laser-capture microdissection (LCM) offers a reliable cell population enrichment tool and has been successfully coupled to MS analysis. Despite this, most proteomic studies employ whole tissue lysate (WTL) analysis in the discovery of disease biomarkers and in profiling analyses. Furthermore, the influence of tissue heterogeneity in WTL analysis, nor its impact in biomarker discovery studies have been completely elucidated. In order to address this, we compared previously obtained high resolution MS data from a cohort of 38 breast cancer tissues, of which both LCM enriched tumor epithelial cells and WTL samples were analyzed. Label-free quantification (LFQ) analysis through MaxQuant software showed a significantly higher number of identified and quantified proteins in LCM enriched samples (3404) compared to WTLs (2837). Furthermore, WTL samples displayed a higher amount of missing data compared to LCM both at peptide and protein levels (p-value < 0.001). 2D analysis on co-expressed proteins revealed discrepant expression of immune system and lipid metabolisms related proteins between LCM and WTL samples. We hereby show that LCM better dissected the biology of breast tumor epithelial cells, possibly due to lower interference from surrounding tissues and highly abundant proteins. All data have been deposited in the ProteomeXchange with the dataset identifier PXD002381 (http://proteomecentral.proteomexchange.org/dataset/PXD002381).<br /> (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Details

Language :
English
ISSN :
1615-9861
Volume :
16
Issue :
10
Database :
MEDLINE
Journal :
Proteomics
Publication Type :
Academic Journal
Accession number :
27030549
Full Text :
https://doi.org/10.1002/pmic.201600004