Literature DB >> 24124232

Connecting genomic alterations to cancer biology with proteomics: the NCI Clinical Proteomic Tumor Analysis Consortium.

Matthew J Ellis1, Michael Gillette, Steven A Carr, Amanda G Paulovich, Richard D Smith, Karin K Rodland, R Reid Townsend, Christopher Kinsinger, Mehdi Mesri, Henry Rodriguez, Daniel C Liebler.   

Abstract

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium is applying the latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and the National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA, and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biologic insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verification using targeted mass spectrometry methods. ©2013 AACR.

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Year:  2013        PMID： 24124232      PMCID： PMC3800055          DOI： 10.1158/2159-8290.CD-13-0219

Source DB:  PubMed          Journal:  Cancer Discov        ISSN： 2159-8274            Impact factor:   39.397


  20 in total

Review 1.  Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions.

Authors:  Paola Picotti; Ruedi Aebersold
Journal:  Nat Methods       Date:  2012-05-30       Impact factor: 28.547

2.  Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma.

Authors:  Terri A Addona; Susan E Abbatiello; Birgit Schilling; Steven J Skates; D R Mani; David M Bunk; Clifford H Spiegelman; Lisa J Zimmerman; Amy-Joan L Ham; Hasmik Keshishian; Steven C Hall; Simon Allen; Ronald K Blackman; Christoph H Borchers; Charles Buck; Helene L Cardasis; Michael P Cusack; Nathan G Dodder; Bradford W Gibson; Jason M Held; Tara Hiltke; Angela Jackson; Eric B Johansen; Christopher R Kinsinger; Jing Li; Mehdi Mesri; Thomas A Neubert; Richard K Niles; Trenton C Pulsipher; David Ransohoff; Henry Rodriguez; Paul A Rudnick; Derek Smith; David L Tabb; Tony J Tegeler; Asokan M Variyath; Lorenzo J Vega-Montoto; Asa Wahlander; Sofia Waldemarson; Mu Wang; Jeffrey R Whiteaker; Lei Zhao; N Leigh Anderson; Susan J Fisher; Daniel C Liebler; Amanda G Paulovich; Fred E Regnier; Paul Tempst; Steven A Carr
Journal:  Nat Biotechnol       Date:  2009-06-28       Impact factor: 54.908

3.  Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

Authors:  Brendan MacLean; Daniela M Tomazela; Nicholas Shulman; Matthew Chambers; Gregory L Finney; Barbara Frewen; Randall Kern; David L Tabb; Daniel C Liebler; Michael J MacCoss
Journal:  Bioinformatics       Date:  2010-02-09       Impact factor: 6.937

4.  Molecular pathways: extracting medical knowledge from high-throughput genomic data.

Authors:  Theodore C Goldstein; Evan O Paull; Matthew J Ellis; Joshua M Stuart
Journal:  Clin Cancer Res       Date:  2013-02-21       Impact factor: 12.531

5.  Quantification of beta-catenin signaling components in colon cancer cell lines, tissue sections, and microdissected tumor cells using reaction monitoring mass spectrometry.

Authors:  Yi Chen; Mike Gruidl; Elizabeth Remily-Wood; Richard Z Liu; Steven Eschrich; Mark Lloyd; Aejaz Nasir; Marilyn M Bui; Emina Huang; David Shibata; Timothy Yeatman; John M Koomen
Journal:  J Proteome Res       Date:  2010-08-06       Impact factor: 4.466

6.  iTRAQ labeling is superior to mTRAQ for quantitative global proteomics and phosphoproteomics.

Authors:  Philipp Mertins; Namrata D Udeshi; Karl R Clauser; D R Mani; Jinal Patel; Shao-en Ong; Jacob D Jaffe; Steven A Carr
Journal:  Mol Cell Proteomics       Date:  2011-12-30       Impact factor: 5.911

7.  Mass spectrometry mapping of epidermal growth factor receptor phosphorylation related to oncogenic mutations and tyrosine kinase inhibitor sensitivity.

Authors:  Guolin Zhang; Bin Fang; Richard Z Liu; Huiyi Lin; Fumi Kinose; Yun Bai; Umut Oguz; Elizabeth R Remily-Wood; Jiannong Li; Soner Altiok; Steven Eschrich; John Koomen; Eric B Haura
Journal:  J Proteome Res       Date:  2010-12-03       Impact factor: 4.466

8.  Ultra high resolution linear ion trap Orbitrap mass spectrometer (Orbitrap Elite) facilitates top down LC MS/MS and versatile peptide fragmentation modes.

Authors:  Annette Michalski; Eugen Damoc; Oliver Lange; Eduard Denisov; Dirk Nolting; Mathias Müller; Rosa Viner; Jae Schwartz; Philip Remes; Michael Belford; Jean-Jacques Dunyach; Juergen Cox; Stevan Horning; Matthias Mann; Alexander Makarov
Journal:  Mol Cell Proteomics       Date:  2011-12-09       Impact factor: 5.911

9.  Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomics analyses.

Authors:  Paul A Rudnick; Karl R Clauser; Lisa E Kilpatrick; Dmitrii V Tchekhovskoi; Pedatsur Neta; Niksa Blonder; Dean D Billheimer; Ronald K Blackman; David M Bunk; Helene L Cardasis; Amy-Joan L Ham; Jacob D Jaffe; Christopher R Kinsinger; Mehdi Mesri; Thomas A Neubert; Birgit Schilling; David L Tabb; Tony J Tegeler; Lorenzo Vega-Montoto; Asokan Mulayath Variyath; Mu Wang; Pei Wang; Jeffrey R Whiteaker; Lisa J Zimmerman; Steven A Carr; Susan J Fisher; Bradford W Gibson; Amanda G Paulovich; Fred E Regnier; Henry Rodriguez; Cliff Spiegelman; Paul Tempst; Daniel C Liebler; Stephen E Stein
Journal:  Mol Cell Proteomics       Date:  2009-10-16       Impact factor: 5.911

10.  Integrative omics analysis reveals the importance and scope of translational repression in microRNA-mediated regulation.

Authors:  Qi Liu; Patrick J Halvey; Yu Shyr; Robbert J C Slebos; Daniel C Liebler; Bing Zhang
Journal:  Mol Cell Proteomics       Date:  2013-04-02       Impact factor: 5.911
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  92 in total

1.  QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues.

Authors:  Harsha P Gunawardena; Jonathon O'Brien; John A Wrobel; Ling Xie; Sherri R Davies; Shunqiang Li; Matthew J Ellis; Bahjat F Qaqish; Xian Chen
Journal:  Mol Cell Proteomics       Date:  2015-11-23       Impact factor: 5.911

2.  Peptide Immunoaffinity Enrichment and Targeted Mass Spectrometry Enables Multiplex, Quantitative Pharmacodynamic Studies of Phospho-Signaling.

Authors:  Jeffrey R Whiteaker; Lei Zhao; Ping Yan; Richard G Ivey; Uliana J Voytovich; Heather D Moore; Chenwei Lin; Amanda G Paulovich
Journal:  Mol Cell Proteomics       Date:  2015-05-18       Impact factor: 5.911

3.  Proteogenomics: emergence and promise.

Authors:  Sam Faulkner; Matthew D Dun; Hubert Hondermarck
Journal:  Cell Mol Life Sci       Date:  2015-01-22       Impact factor: 9.261

4.  An Integrative Analysis of Tumor Proteomic and Phosphoproteomic Profiles to Examine the Relationships Between Kinase Activity and Phosphorylation.

Authors:  Osama A Arshad; Vincent Danna; Vladislav A Petyuk; Paul D Piehowski; Tao Liu; Karin D Rodland; Jason E McDermott
Journal:  Mol Cell Proteomics       Date:  2019-06-21       Impact factor: 5.911

Review 5.  Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics.

Authors:  Eric W Deutsch; Luis Mendoza; David Shteynberg; Joseph Slagel; Zhi Sun; Robert L Moritz
Journal:  Proteomics Clin Appl       Date:  2015-04-02       Impact factor: 3.494

6.  CanProVar 2.0: An Updated Database of Human Cancer Proteome Variation.

Authors:  Menghuan Zhang; Bo Wang; Jia Xu; Xiaojing Wang; Lu Xie; Bing Zhang; Yixue Li; Jing Li
Journal:  J Proteome Res       Date:  2016-12-15       Impact factor: 4.466

7.  Statistical Methods in Integrative Genomics.

Authors:  Sylvia Richardson; George C Tseng; Wei Sun
Journal:  Annu Rev Stat Appl       Date:  2016-04-18       Impact factor: 5.810

8.  Targeted Proteomic Analyses of Histone H4 Acetylation Changes Associated with Homologous-Recombination-Deficient High-Grade Serous Ovarian Carcinomas.

Authors:  Stefani N Thomas; Lijun Chen; Yang Liu; Naseruddin Höti; Hui Zhang
Journal:  J Proteome Res       Date:  2017-09-14       Impact factor: 4.466

Review 9.  Clinical potential of mass spectrometry-based proteogenomics.

Authors:  Bing Zhang; Jeffrey R Whiteaker; Andrew N Hoofnagle; Geoffrey S Baird; Karin D Rodland; Amanda G Paulovich
Journal:  Nat Rev Clin Oncol       Date:  2019-04       Impact factor: 66.675

Review 10.  How Machine Learning Will Transform Biomedicine.

Authors:  Jeremy Goecks; Vahid Jalili; Laura M Heiser; Joe W Gray
Journal:  Cell       Date:  2020-04-02       Impact factor: 41.582
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