Literature DB >> 25724909

Multiplexed, Quantitative Workflow for Sensitive Biomarker Discovery in Plasma Yields Novel Candidates for Early Myocardial Injury.

Hasmik Keshishian1, Michael W Burgess2, Michael A Gillette3, Philipp Mertins2, Karl R Clauser2, D R Mani2, Eric W Kuhn2, Laurie A Farrell4, Robert E Gerszten3, Steven A Carr1.   

Abstract

We have developed a novel plasma protein analysis platform with optimized sample preparation, chromatography, and MS analysis protocols. The workflow, which utilizes chemical isobaric mass tag labeling for relative quantification of plasma proteins, achieves far greater depth of proteome detection and quantification while simultaneously having increased sample throughput than prior methods. We applied the new workflow to a time series of plasma samples from patients undergoing a therapeutic, "planned" myocardial infarction for hypertrophic cardiomyopathy, a unique human model in which each person serves as their own biologic control. Over 5300 proteins were confidently identified in our experiments with an average of 4600 proteins identified per sample (with two or more distinct peptides identified per protein) using iTRAQ four-plex labeling. Nearly 3400 proteins were quantified in common across all 16 patient samples. Compared with a previously published label-free approach, the new method quantified almost fivefold more proteins/sample and provided a six- to nine-fold increase in sample analysis throughput. Moreover, this study provides the largest high-confidence plasma proteome dataset available to date. The reliability of relative quantification was also greatly improved relative to the label-free approach, with measured iTRAQ ratios and temporal trends correlating well with results from a 23-plex immunoMRM (iMRM) assay containing a subset of the candidate proteins applied to the same patient samples. The functional importance of improved detection and quantification was reflected in a markedly expanded list of significantly regulated proteins that provided many new candidate biomarker proteins. Preliminary evaluation of plasma sample labeling with TMT six-plex and ten-plex reagents suggests that even further increases in multiplexing of plasma analysis are practically achievable without significant losses in depth of detection relative to iTRAQ four-plex. These results obtained with our novel platform provide clear demonstration of the value of using isobaric mass tag reagents in plasma-based biomarker discovery experiments.
© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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Year:  2015        PMID: 25724909      PMCID: PMC4563722          DOI: 10.1074/mcp.M114.046813

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  34 in total

1.  Interlaboratory evaluation of automated, multiplexed peptide immunoaffinity enrichment coupled to multiple reaction monitoring mass spectrometry for quantifying proteins in plasma.

Authors:  Eric Kuhn; Jeffrey R Whiteaker; D R Mani; Angela M Jackson; Lei Zhao; Matthew E Pope; Derek Smith; Keith D Rivera; N Leigh Anderson; Steven J Skates; Terry W Pearson; Amanda G Paulovich; Steven A Carr
Journal:  Mol Cell Proteomics       Date:  2011-12-22       Impact factor: 5.911

2.  Systematic comparison of label-free, metabolic labeling, and isobaric chemical labeling for quantitative proteomics on LTQ Orbitrap Velos.

Authors:  Zhou Li; Rachel M Adams; Karuna Chourey; Gregory B Hurst; Robert L Hettich; Chongle Pan
Journal:  J Proteome Res       Date:  2012-02-16       Impact factor: 4.466

3.  Addressing accuracy and precision issues in iTRAQ quantitation.

Authors:  Natasha A Karp; Wolfgang Huber; Pawel G Sadowski; Philip D Charles; Svenja V Hester; Kathryn S Lilley
Journal:  Mol Cell Proteomics       Date:  2010-04-10       Impact factor: 5.911

Review 4.  Protein biomarker discovery and validation: the long and uncertain path to clinical utility.

Authors:  Nader Rifai; Michael A Gillette; Steven A Carr
Journal:  Nat Biotechnol       Date:  2006-08       Impact factor: 54.908

5.  Measuring and managing ratio compression for accurate iTRAQ/TMT quantification.

Authors:  Mikhail M Savitski; Toby Mathieson; Nico Zinn; Gavain Sweetman; Carola Doce; Isabelle Becher; Fiona Pachl; Bernhard Kuster; Marcus Bantscheff
Journal:  J Proteome Res       Date:  2013-07-02       Impact factor: 4.466

6.  A pipeline that integrates the discovery and verification of plasma protein biomarkers reveals candidate markers for cardiovascular disease.

Authors:  Terri A Addona; Xu Shi; Hasmik Keshishian; D R Mani; Michael Burgess; Michael A Gillette; Karl R Clauser; Dongxiao Shen; Gregory D Lewis; Laurie A Farrell; Michael A Fifer; Marc S Sabatine; Robert E Gerszten; Steven A Carr
Journal:  Nat Biotechnol       Date:  2011-06-19       Impact factor: 54.908

7.  Integrated proteomic analysis of post-translational modifications by serial enrichment.

Authors:  Philipp Mertins; Jana W Qiao; Jinal Patel; Namrata D Udeshi; Karl R Clauser; D R Mani; Michael W Burgess; Michael A Gillette; Jacob D Jaffe; Steven A Carr
Journal:  Nat Methods       Date:  2013-06-09       Impact factor: 28.547

8.  Cardiac-specific troponin I levels to predict the risk of mortality in patients with acute coronary syndromes.

Authors:  E M Antman; M J Tanasijevic; B Thompson; M Schactman; C H McCabe; C P Cannon; G A Fischer; A Y Fung; C Thompson; D Wybenga; E Braunwald
Journal:  N Engl J Med       Date:  1996-10-31       Impact factor: 91.245

9.  Characterization of global yeast quantitative proteome data generated from the wild-type and glucose repression saccharomyces cerevisiae strains: the comparison of two quantitative methods.

Authors:  Renata Usaite; James Wohlschlegel; John D Venable; Sung K Park; Jens Nielsen; Lisbeth Olsson; John R Yates Iii
Journal:  J Proteome Res       Date:  2008-01       Impact factor: 4.466

10.  Targeted peptide measurements in biology and medicine: best practices for mass spectrometry-based assay development using a fit-for-purpose approach.

Authors:  Steven A Carr; Susan E Abbatiello; Bradley L Ackermann; Christoph Borchers; Bruno Domon; Eric W Deutsch; Russell P Grant; Andrew N Hoofnagle; Ruth Hüttenhain; John M Koomen; Daniel C Liebler; Tao Liu; Brendan MacLean; D R Mani; Elizabeth Mansfield; Hendrik Neubert; Amanda G Paulovich; Lukas Reiter; Olga Vitek; Ruedi Aebersold; Leigh Anderson; Robert Bethem; Josip Blonder; Emily Boja; Julianne Botelho; Michael Boyne; Ralph A Bradshaw; Alma L Burlingame; Daniel Chan; Hasmik Keshishian; Eric Kuhn; Christopher Kinsinger; Jerry S H Lee; Sang-Won Lee; Robert Moritz; Juan Oses-Prieto; Nader Rifai; James Ritchie; Henry Rodriguez; Pothur R Srinivas; R Reid Townsend; Jennifer Van Eyk; Gordon Whiteley; Arun Wiita; Susan Weintraub
Journal:  Mol Cell Proteomics       Date:  2014-01-17       Impact factor: 5.911

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  62 in total

1.  Small and Large Ribosomal Subunit Deficiencies Lead to Distinct Gene Expression Signatures that Reflect Cellular Growth Rate.

Authors:  Ze Cheng; Christopher Frederick Mugler; Abdurrahman Keskin; Stefanie Hodapp; Leon Yen-Lee Chan; Karsten Weis; Philipp Mertins; Aviv Regev; Marko Jovanovic; Gloria Ann Brar
Journal:  Mol Cell       Date:  2018-11-29       Impact factor: 17.970

2.  The MaxQuant computational platform for mass spectrometry-based shotgun proteomics.

Authors:  Stefka Tyanova; Tikira Temu; Juergen Cox
Journal:  Nat Protoc       Date:  2016-10-27       Impact factor: 13.491

3.  Integrated Cellular and Plasma Proteomics of Contrasting B-cell Cancers Reveals Common, Unique and Systemic Signatures.

Authors:  Harvey E Johnston; Matthew J Carter; Kerry L Cox; Melanie Dunscombe; Antigoni Manousopoulou; Paul A Townsend; Spiros D Garbis; Mark S Cragg
Journal:  Mol Cell Proteomics       Date:  2017-01-04       Impact factor: 5.911

4.  Targeted Proteomics for Multiplexed Verification of Markers of Colorectal Tumorigenesis.

Authors:  Anuli Christiana Uzozie; Nathalie Selevsek; Asa Wahlander; Paolo Nanni; Jonas Grossmann; Achim Weber; Federico Buffoli; Giancarlo Marra
Journal:  Mol Cell Proteomics       Date:  2017-01-04       Impact factor: 5.911

Review 5.  Advances in targeted proteomics and applications to biomedical research.

Authors:  Tujin Shi; Ehwang Song; Song Nie; Karin D Rodland; Tao Liu; Wei-Jun Qian; Richard D Smith
Journal:  Proteomics       Date:  2016-08       Impact factor: 3.984

6.  Temporal profiles of plasma proteome during childhood development.

Authors:  Chih-Wei Liu; Lisa Bramer; Bobbie-Jo Webb-Robertson; Kathleen Waugh; Marian J Rewers; Qibin Zhang
Journal:  J Proteomics       Date:  2016-11-23       Impact factor: 4.044

Review 7.  Emerging Affinity-Based Proteomic Technologies for Large-Scale Plasma Profiling in Cardiovascular Disease.

Authors:  J Gustav Smith; Robert E Gerszten
Journal:  Circulation       Date:  2017-04-25       Impact factor: 29.690

8.  Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms.

Authors:  Jacob D Jaffe; Caitlin M Feeney; Jinal Patel; Xiaodong Lu; D R Mani
Journal:  J Am Soc Mass Spectrom       Date:  2016-08-25       Impact factor: 3.109

9.  Dioxin-like and non-dioxin-like PCBs differentially regulate the hepatic proteome and modify diet-induced nonalcoholic fatty liver disease severity.

Authors:  Jian Jin; Banrida Wahlang; Hongxue Shi; Josiah E Hardesty; K Cameron Falkner; Kimberly Z Head; Sudhir Srivastava; Michael L Merchant; Shesh N Rai; Matthew C Cave; Russell A Prough
Journal:  Med Chem Res       Date:  2020-06-07       Impact factor: 1.965

10.  Aptamer-Based Proteomic Profiling Reveals Novel Candidate Biomarkers and Pathways in Cardiovascular Disease.

Authors:  Debby Ngo; Sumita Sinha; Dongxiao Shen; Eric W Kuhn; Michelle J Keyes; Xu Shi; Mark D Benson; John F O'Sullivan; Hasmik Keshishian; Laurie A Farrell; Michael A Fifer; Ramachandran S Vasan; Marc S Sabatine; Martin G Larson; Steven A Carr; Thomas J Wang; Robert E Gerszten
Journal:  Circulation       Date:  2016-07-26       Impact factor: 29.690

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