Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines
Summary: 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 prote...
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| Format: | Article |
| Language: | English |
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Elsevier
2019-11-01
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| Series: | iScience |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004219304407 |
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English |
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Article |
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DOAJ |
| author |
Tiannan Guo Augustin Luna Vinodh N. Rajapakse Ching Chiek Koh Zhicheng Wu Wei Liu Yaoting Sun Huanhuan Gao Michael P. Menden Chao Xu Laurence Calzone Loredana Martignetti Chiara Auwerx Marija Buljan Amir Banaei-Esfahani Alessandro Ori Murat Iskar Ludovic Gillet Ran Bi Jiangnan Zhang Huanhuan Zhang Chenhuan Yu Qing Zhong Sudhir Varma Uwe Schmitt Peng Qiu Qiushi Zhang Yi Zhu Peter J. Wild Mathew J. Garnett Peer Bork Martin Beck Kexin Liu Julio Saez-Rodriguez Fathi Elloumi William C. Reinhold Chris Sander Yves Pommier Ruedi Aebersold |
| spellingShingle |
Tiannan Guo Augustin Luna Vinodh N. Rajapakse Ching Chiek Koh Zhicheng Wu Wei Liu Yaoting Sun Huanhuan Gao Michael P. Menden Chao Xu Laurence Calzone Loredana Martignetti Chiara Auwerx Marija Buljan Amir Banaei-Esfahani Alessandro Ori Murat Iskar Ludovic Gillet Ran Bi Jiangnan Zhang Huanhuan Zhang Chenhuan Yu Qing Zhong Sudhir Varma Uwe Schmitt Peng Qiu Qiushi Zhang Yi Zhu Peter J. Wild Mathew J. Garnett Peer Bork Martin Beck Kexin Liu Julio Saez-Rodriguez Fathi Elloumi William C. Reinhold Chris Sander Yves Pommier Ruedi Aebersold Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines iScience |
| author_facet |
Tiannan Guo Augustin Luna Vinodh N. Rajapakse Ching Chiek Koh Zhicheng Wu Wei Liu Yaoting Sun Huanhuan Gao Michael P. Menden Chao Xu Laurence Calzone Loredana Martignetti Chiara Auwerx Marija Buljan Amir Banaei-Esfahani Alessandro Ori Murat Iskar Ludovic Gillet Ran Bi Jiangnan Zhang Huanhuan Zhang Chenhuan Yu Qing Zhong Sudhir Varma Uwe Schmitt Peng Qiu Qiushi Zhang Yi Zhu Peter J. Wild Mathew J. Garnett Peer Bork Martin Beck Kexin Liu Julio Saez-Rodriguez Fathi Elloumi William C. Reinhold Chris Sander Yves Pommier Ruedi Aebersold |
| author_sort |
Tiannan Guo |
| title |
Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines |
| title_short |
Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines |
| title_full |
Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines |
| title_fullStr |
Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines |
| title_full_unstemmed |
Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines |
| title_sort |
quantitative proteome landscape of the nci-60 cancer cell lines |
| publisher |
Elsevier |
| series |
iScience |
| issn |
2589-0042 |
| publishDate |
2019-11-01 |
| description |
Summary: 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. : Biological Sciences; Systems Biology; Proteomics; Cancer Systems Biology Subject Areas: Biological Sciences, Systems Biology, Proteomics, Cancer Systems Biology |
| url |
http://www.sciencedirect.com/science/article/pii/S2589004219304407 |
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doaj-ccb6206f1f4f4ccf946fcd290d879f5e2020-11-25T03:34:57ZengElsevieriScience2589-00422019-11-0121664680Quantitative Proteome Landscape of the NCI-60 Cancer Cell LinesTiannan Guo0Augustin Luna1Vinodh N. Rajapakse2Ching Chiek Koh3Zhicheng Wu4Wei Liu5Yaoting Sun6Huanhuan Gao7Michael P. Menden8Chao Xu9Laurence Calzone10Loredana Martignetti11Chiara Auwerx12Marija Buljan13Amir Banaei-Esfahani14Alessandro Ori15Murat Iskar16Ludovic Gillet17Ran Bi18Jiangnan Zhang19Huanhuan Zhang20Chenhuan Yu21Qing Zhong22Sudhir Varma23Uwe Schmitt24Peng Qiu25Qiushi Zhang26Yi Zhu27Peter J. Wild28Mathew J. Garnett29Peer Bork30Martin Beck31Kexin Liu32Julio Saez-Rodriguez33Fathi Elloumi34William C. Reinhold35Chris Sander36Yves Pommier37Ruedi Aebersold38Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, P. R. China; Guomics Laboratory of Proteomic Big Data, Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland; Corresponding authorcBio Center, Division of Biostatistics, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USADevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USADepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, SwitzerlandKey Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, P. R. China; Guomics Laboratory of Proteomic Big Data, Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, ChinaKey Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, P. R. China; Guomics Laboratory of Proteomic Big Data, Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China; Department of Clinical Pharmacology, College of Pharmacy, Dalian Medical University, Dalian, Liaoning, ChinaKey Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, P. R. China; Guomics Laboratory of Proteomic Big Data, Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, ChinaKey Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, P. R. China; Guomics Laboratory of Proteomic Big Data, Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, ChinaRWTH Aachen University, Faculty of Medicine, Joint Research Centre for Computational Biomedicine (JRC-COMBINE), Aachen, Germany; Bioscience, Oncology, IMED Biotech Unit, AstraZeneca, Cambridge, UKFaculty of Software, Fujian Normal University, Fuzhou, ChinaInstitut Curie, PSL Research University, INSERM, U900, Mines Paris Tech 75005, Paris, FranceInstitut Curie, PSL Research University, INSERM, U900, Mines Paris Tech 75005, Paris, FranceDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, SwitzerlandDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, SwitzerlandDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland; PhD Program in Systems Biology, Life Science Zurich Graduate School, University of Zurich and ETH Zurich, Zurich, SwitzerlandLeibniz Institute on Aging, Fritz Lipmann Institute (FLI), Beutenbergstrasse 11, 07745 Jena, GermanyStructural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, GermanyDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, SwitzerlandDepartment of Clinical Pharmacology, College of Pharmacy, Dalian Medical University, Dalian, Liaoning, ChinaDepartment of Clinical Pharmacology, College of Pharmacy, Dalian Medical University, Dalian, Liaoning, ChinaKey Laboratory of Experimental Animal and Safety Evaluation, Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, ChinaKey Laboratory of Experimental Animal and Safety Evaluation, Zhejiang Academy of Medical Sciences, Hangzhou, Zhejiang, ChinaInstitute of Surgical Pathology, University Hospital Zurich, Zurich, Switzerland; Cancer Data Science Group, Children's Medical Research Institute, University of Sydney, Sydney, NSW, AustraliaHiThru Analytics, Laurel, MD 20707, USAScientific IT Services, ETH Zurich, Zurich, SwitzerlandDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, 313 Ferst Dr., Atlanta, GA 30332, USAKey Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, P. R. China; Guomics Laboratory of Proteomic Big Data, Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, ChinaKey Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, P. R. China; Guomics Laboratory of Proteomic Big Data, Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, SwitzerlandInstitute of Surgical Pathology, University Hospital Zurich, Zurich, SwitzerlandSanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UKStructural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany; Molecular Medicine Partnership Unit, University of Heidelberg and European Molecular Biology Laboratory, 69120 Heidelberg, Germany; Max Delbrück Centre for Molecular Medicine, 13125 Berlin, Germany; Department of Bioinformatics, Biocenter, University of Würzburg, 97074 Würzburg, GermanyStructural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany; Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, 69117 Heidelberg, GermanyDepartment of Clinical Pharmacology, College of Pharmacy, Dalian Medical University, Dalian, Liaoning, ChinaRWTH Aachen University, Faculty of Medicine, Joint Research Centre for Computational Biomedicine (JRC-COMBINE), Aachen, GermanyDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USADevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USAcBio Center, Division of Biostatistics, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USADevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA; Corresponding authorDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland; Faculty of Science, University of Zurich, Zurich, Switzerland; Corresponding authorSummary: 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. : Biological Sciences; Systems Biology; Proteomics; Cancer Systems Biology Subject Areas: Biological Sciences, Systems Biology, Proteomics, Cancer Systems Biologyhttp://www.sciencedirect.com/science/article/pii/S2589004219304407 |