Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines

被引:45
作者
Guo, Tiannan [1 ,2 ,3 ]
Luna, Augustin [4 ,5 ]
Rajapakse, Vinodh N. [6 ]
Koh, Ching Chiek [3 ,19 ]
Wu, Zhicheng [1 ,2 ]
Liu, Wei [1 ,2 ,28 ]
Sun, Yaoting [1 ,2 ]
Gao, Huanhuan [1 ,2 ]
Menden, Michael P. [7 ,27 ]
Xu, Chao [8 ]
Calzone, Laurence [9 ]
Martignetti, Loredana [9 ]
Auwerx, Chiara [3 ]
Buljan, Marija [3 ]
Banaei-Esfahani, Amir [3 ,10 ,11 ]
Ori, Alessandro [12 ]
Iskar, Murat [13 ,30 ]
Gillet, Ludovic [3 ]
Bi, Ran [28 ]
Zhang, Jiangnan [28 ]
Zhang, Huanhuan [29 ]
Yu, Chenhuan [29 ]
Zhong, Qing [14 ,26 ]
Varma, Sudhir [15 ]
Schmitt, Uwe [16 ]
Qiu, Peng [17 ,18 ]
Zhang, Qiushi [1 ,2 ]
Zhu, Yi [1 ,2 ,3 ]
Wild, Peter J. [14 ]
Garnett, Mathew J. [19 ]
Bork, Peer [13 ,20 ,21 ,22 ,23 ]
Beck, Martin [13 ,24 ]
Liu, Kexin [28 ]
Saez-Rodriguez, Julio [7 ]
Elloumi, Fathi [6 ]
Reinhold, William C. [6 ]
Sander, Chris [4 ,5 ]
Pommier, Yves [6 ]
Aebersold, Ruedi [3 ,25 ]
机构
[1] Westlake Univ, Sch Life Sci, Key Lab Struct Biol Zhejiang Prov, Hangzhou, Zhejiang, Peoples R China
[2] Westlake Inst Adv Study, Inst Basic Med Sci, Guom Lab Prote Big Data, 18 Shilongshan Rd, Hangzhou 310024, Zhejiang, Peoples R China
[3] Swiss Fed Inst Technol, Dept Biol, Inst Mol Syst Biol, Zurich, Switzerland
[4] Dana Farber Canc Inst, cBio Ctr, Dept Data Sci, Div Biostat, Boston, MA 02115 USA
[5] Harvard Med Sch, Dept Cell Biol, Boston, MA 02115 USA
[6] NCI, Dev Therapeut Branch, Ctr Canc Res, NIH, Bethesda, MD 20892 USA
[7] Rhein Westfal TH Aachen, Fac Med, Joint Res Ctr Computat Biomed JRC COMBINE, Aachen, Germany
[8] Fujian Normal Univ, Fac Software, Fuzhou, Fujian, Peoples R China
[9] PSL Res Univ, Inst Curie, Mines Paris Tech, U900,INSERM, F-75005 Paris, France
[10] Univ Zurich, Life Sci Zurich Grad Sch, PhD Program Syst Biol, Zurich, Switzerland
[11] Swiss Fed Inst Technol, Zurich, Switzerland
[12] FLI, Leibniz Inst Aging, Beutenbergstr 11, D-07745 Jena, Germany
[13] European Mol Biol Lab, Struct & Computat Biol Unit, D-69117 Heidelberg, Germany
[14] Univ Hosp Zurich, Inst Surg Pathol, Zurich, Switzerland
[15] HiThru Analyt, Laurel, MD 20707 USA
[16] Swiss Fed Inst Technol, Sci IT Serv, Zurich, Switzerland
[17] Georgia Inst Technol, Dept Biomed Engn, 313 Ferst Dr, Atlanta, GA 30332 USA
[18] Emory Univ, 313 Ferst Dr, Atlanta, GA 30332 USA
[19] Sanger Inst, Wellcome Trust Genome Campus, Cambridge CB10 1SA, England
[20] Heidelberg Univ, Mol Med Partnership Unit, D-69120 Heidelberg, Germany
[21] European Mol Biol Lab, D-69120 Heidelberg, Germany
[22] Max Delbruck Ctr Mol Med, D-13125 Berlin, Germany
[23] Univ Wurzburg, Bioctr, Dept Bioinformat, D-97074 Wurzburg, Germany
[24] European Mol Biol Lab, Cell Biol & Biophys Unit, D-69117 Heidelberg, Germany
[25] Univ Zurich, Fac Sci, Zurich, Switzerland
[26] Univ Sydney, Childrens Med Res Inst, Canc Data Sci Grp, Sydney, NSW, Australia
[27] AstraZeneca, IMED Biotech Unit, Biosci, Oncol, Cambridge, England
[28] Dalian Med Univ, Coll Pharm, Dept Clin Pharmacol, Dalian, Liaoning, Peoples R China
[29] Zhejiang Acad Med Sci, Key Lab Expt Anim & Safety Evaluat, Hangzhou, Zhejiang, Peoples R China
[30] German Canc Res Ctr, Div Mol Genet, Neuenheimer Feld 280, D-69120 Heidelberg, Germany
基金
中国国家自然科学基金; 英国惠康基金; 美国国家卫生研究院; 欧洲研究理事会; 瑞士国家科学基金会;
关键词
PROTEOGENOMIC CHARACTERIZATION; DRUG-SENSITIVITY; KINASE-C; IDENTIFICATION; CELLMINER; MAP; INTEGRATION; PROFILES; GROWTH; TISSUE;
D O I
10.1016/j.isci.2019.10.059
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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, beta-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-omit 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.
引用
收藏
页码:664 / +
页数:80
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