Proteomics

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Quantitative proteomic analysis of breast cancer tissues


ABSTRACT: We compared label-free and SILAC based quantative methods in combination with shotgun, directed and targeted MS methods in laser capture microdissected breast cancer tissues (biological replicates) as well as whole tissue lysates (technical replicates). We aim to recommend a quantitative method for biomarker discovery and validation in laser capture microdissected tissues. Recorded MS files were analyzed using MaxQuant soft ware (version 1.1.1.36). An initial search was set at a precursor mass window of 7 ppm. The search followed an enzymatic cleavage rule of Trypsin/P and allowed maximal 2 missed cleavage sites. Carbamidomethylati on of cysteines was defined as fixed modification, while protein N;terminal acetylation and methionine oxidation were defined as variable modifications for database searching. To construct the MS/MS peak list file, up to top 8 peaks per 100 Da window were extracted and submitted to search against a concatenated forward and reverse version of the UniProtKB/Swiss;Prot human database (generated from version 2011_03). The cutoff of global false discovery rate (FDR) for peptide and protein identification was set to 0.01, and only peptides with greater than or equal to 7 amino acid residues were allowed for identification. Minimally one unique peptide was required for protein identification

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Ning Qing Liu  

LAB HEAD: Ning Qing Liu

PROVIDER: PXD000278 | Pride | 2013-08-23

REPOSITORIES: Pride

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Quantitative proteomic analysis of microdissected breast cancer tissues: comparison of label-free and SILAC-based quantification with shotgun, directed, and targeted MS approaches.

Liu Ning Qing NQ   Dekker Lennard J M LJ   Stingl Christoph C   Güzel Coşkun C   De Marchi Tommaso T   Martens John W M JW   Foekens John A JA   Luider Theo M TM   Umar Arzu A  

Journal of proteome research 20130913 10


Quantitative proteomics plays an important role in validation of breast-cancer-related biomarkers. In this study, we systematically compared the performance of label-free quantification (LFQ) and SILAC with shotgun and directed methods for quantifying breast-cancer-related markers in microdissected tissues. We show that LFQ leads to slightly higher coefficient of variation (CV) for protein quantification (median CV = 16.3%) than SILAC quantification (median CV = 13.7%) (P < 0.0001), but LFQ meth  ...[more]

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