Journal
JOURNAL OF PROTEOME RESEARCH
Volume 16, Issue 12, Pages 4523-4530Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.7b00362
Keywords
clinical proteomics; quantification; iTRAQ; tumor tissues; Cancer Biology and Disease Human Proteome Project
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Funding
- National Institutes of Health under National Cancer Institute, Clinical Proteomics Tumor Analysis Consortium [U24CA160036, U24CA210985]
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Clinical proteomics requires large-scale analysis of human specimens to achieve statistical significance. We evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomics strategy using one channel for reference across all samples in different iTRAQ sets. A total of 148 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating six 2D LC-MS/MS data sets for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assess the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we derived a quantification confidence score based on the quality of each peptide-spectrum match to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS data sets collected over a 7-month period. This study provides the first quality assessment on long-term stability and technical considerations for study design of a large-scale clinical proteomics project.
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