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Item Type: | Article |
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Title: | Quantitative proteome landscape of the NCI-60 cancer cell lines |
Creators Name: | Guo, T., Luna, A., Rajapakse, V.N., Koh, C.C., Wu, Z., Liu, W., Sun, Y., Gao, H., Menden, M.P., Xu, C., Calzone, L., Martignetti, L., Auwerx, C., Buljan, M., Banaei-Esfahani, A., Ori, A., Iskar, M., Gillet, L., Bi, R., Zhang, J., Zhang, H., Yu, C., Zhong, Q., Varma, S., Schmitt, U., Qiu, P., Zhang, Q., Zhu, Y., Wild, P.J., Garnett, M.J., Bork, P., Beck, M., Liu, K., Saez-Rodriguez, J., Elloumi, F., Reinhold, W.C., Sander, C., 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 |
Source: | iScience |
ISSN: | 2589-0042 |
Publisher: | Cell Press |
Volume: | 21 |
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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