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J Proteome Res DOI:10.1021/acs.jproteome.5b00859

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts.

Publication TypeJournal Article
Year of Publication2016
AuthorsTabb, DL, Wang, X, Carr, SA, Clauser, KR, Mertins, P, Chambers, MC, Holman, JD, Wang, J, Zhang, B, Zimmerman, LJ, Chen, X, Gunawardena, HP, Davies, SR, Ellis, MJC, Li, S, R Townsend, R, Boja, ES, Ketchum, KA, Kinsinger, CR, Mesri, M, Rodriguez, H, Liu, T, Kim, S, McDermott, JE, Payne, SH, Petyuk, VA, Rodland, KD, Smith, RD, Yang, F, Chan, DW, Zhang, B, Zhang, H, Zhang, Z, Zhou, J-Y, Liebler, DC
JournalJ Proteome Res
Volume15
Issue3
Pages691-706
Date Published2016 Mar 04
ISSN1535-3907
KeywordsBreast Neoplasms, Chromatography, Liquid, Data Interpretation, Statistical, Female, Gene Expression Profiling, Heterografts, Humans, Metabolic Networks and Pathways, Observer Variation, Proteome, Proteomics, Quality Control, Reproducibility of Results, Tandem Mass Spectrometry
Abstract

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm ). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

URLhttp://dx.doi.org/10.1021/acs.jproteome.5b00859
DOI10.1021/acs.jproteome.5b00859
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/26653538?dopt=Abstract

Alternate JournalJ. Proteome Res.
PubMed ID26653538
PubMed Central IDPMC4779376
Grant ListU24-CA-160034 / CA / NCI NIH HHS / United States
U24 CA160034 / CA / NCI NIH HHS / United States
U24-CA-159988 / CA / NCI NIH HHS / United States
U24 CA159988 / CA / NCI NIH HHS / United States
U24-CA-160019 / CA / NCI NIH HHS / United States
P30 CA016086 / CA / NCI NIH HHS / United States
UL1 RR024992 / RR / NCRR NIH HHS / United States
HHSN261201100106C / CA / NCI NIH HHS / United States
U24 CA160036 / CA / NCI NIH HHS / United States
P30 CA091842 / CA / NCI NIH HHS / United States
U24-CA-160036 / CA / NCI NIH HHS / United States
U24 CA160019 / CA / NCI NIH HHS / United States
UL1 TR000448 / TR / NCATS NIH HHS / United States
U24 CA160035 / CA / NCI NIH HHS / United States
HHSN261201100106C / / PHS HHS / United States
U24-CA-160035 / CA / NCI NIH HHS / United States