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Quantitative proteome landscape of the NCI-60 cancer cell lines

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Item Type:Article
Title:Quantitative proteome landscape of the NCI-60 cancer cell lines
Creators Name:Guo, T. and Luna, A. and Rajapakse, V.N. and Koh, C.C. and Wu, Z. and Liu, W. and Sun, Y. and Gao, H. and Menden, M.P. and Xu, C. and Calzone, L. and Martignetti, L. and Auwerx, C. and Buljan, M. and Banaei-Esfahani, A. and Ori, A. and Iskar, M. and Gillet, L. and Bi, R. and Zhang, J. and Zhang, H. and Yu, C. and Zhong, Q. and Varma, S. and Schmitt, U. and Qiu, P. and Zhang, Q. and Zhu, Y. and Wild, P.J. and Garnett, M.J. and Bork, P. and Beck, M. and Liu, K. and Saez-Rodriguez, J. and Elloumi, F. and Reinhold, W.C. and Sander, C. and Pommier, Y. and Aebersold, R.
Abstract:Here we describe a proteomic data resource for the NCI-60 cell lines generated by pressure cycling technology and SWATH mass spectrometry. We developed the DIA-expert software to curate and visualize the SWATH data, leading to reproducible detection of over 3,100 SwissProt proteotypic proteins and systematic quantification of pathway activities. Stoichiometric relationships of interacting proteins for DNA replication, repair, the chromatin remodeling NuRD complex, β-catenin, RNA metabolism, and prefoldins are more evident than that at the mRNA level. The data are available in CellMiner (discover.nci.nih.gov/cellminercdb and discover.nci.nih.gov/cellminer), allowing casual users to test hypotheses and perform integrative, cross-database analyses of multi-omic drug response correlations for over 20,000 drugs. We demonstrate the value of proteome data in predicting drug response for over 240 clinically relevant chemotherapeutic and targeted therapies. In summary, we present a novel proteome resource for the NCI-60, together with relevant software tools, and demonstrate the benefit of proteome analyses.
Keywords:Biological Sciences, Systems Biology, Proteomics, Cancer Systems Biology
Publisher:Cell Press
Page Range:664-680
Date:31 October 2019
Official Publication:https://doi.org/10.1016/j.isci.2019.10.059
PubMed:View item in PubMed

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