OBJECTIVES: The aim of this study was to develop high-throughput, quantitative and highly selective mass spectrometric, targeted immunoassays for clinically important proteins in human plasma or serum. DESIGN AND METHODS: The described method coupled mass spectrometric immunoassay (MSIA), a previously developed technique for immunoenrichment on a monolithic microcolumn activated with an anti-protein antibody and fixed in a pipette tip, to selected reaction monitoring (SRM) detection and accurate quantification of targeted peptides, including clinically relevant sequence or truncated variants. RESULTS: In this report, we demonstrate the rapid development of MSIA-SRM assays for sixteen different target proteins spanning seven different clinically important areas (including neurological, Alzheimer's, cardiovascular, endocrine function, cancer and other diseases) and ranging in concentration from pg/mL to mg/mL. The reported MSIA-SRM assays demonstrated high sensitivity (within published clinical ranges), precision, robustness and high-throughput as well as specific detection of clinically relevant isoforms for many of the target proteins. Most of the assays were tested with bona-fide clinical samples. In addition, positive correlations, (R2 0.67-0.87, depending on the target peptide), were demonstrated for MSIA-SRM assay data with clinical analyzer measurements of parathyroid hormone (PTH) and insulin growth factor 1 (IGF1) in clinical sample cohorts. CONCLUSIONS: We have presented a practical and scalable method for rapid development and deployment of MS-based SRM assays for clinically relevant proteins and measured levels of the target analytes in bona fide clinical samples. The method permits the specific quantification of individual protein isoforms and addresses the difficult problem of protein heterogeneity in clinical proteomics applications.
OBJECTIVES: The aim of this study was to develop high-throughput, quantitative and highly selective mass spectrometric, targeted immunoassays for clinically important proteins in human plasma or serum. DESIGN AND METHODS: The described method coupled mass spectrometric immunoassay (MSIA), a previously developed technique for immunoenrichment on a monolithic microcolumn activated with an anti-protein antibody and fixed in a pipette tip, to selected reaction monitoring (SRM) detection and accurate quantification of targeted peptides, including clinically relevant sequence or truncated variants. RESULTS: In this report, we demonstrate the rapid development of MSIA-SRM assays for sixteen different target proteins spanning seven different clinically important areas (including neurological, Alzheimer's, cardiovascular, endocrine function, cancer and other diseases) and ranging in concentration from pg/mL to mg/mL. The reported MSIA-SRM assays demonstrated high sensitivity (within published clinical ranges), precision, robustness and high-throughput as well as specific detection of clinically relevant isoforms for many of the target proteins. Most of the assays were tested with bona-fide clinical samples. In addition, positive correlations, (R2 0.67-0.87, depending on the target peptide), were demonstrated for MSIA-SRM assay data with clinical analyzer measurements of parathyroid hormone (PTH) and insulin growth factor 1 (IGF1) in clinical sample cohorts. CONCLUSIONS: We have presented a practical and scalable method for rapid development and deployment of MS-based SRM assays for clinically relevant proteins and measured levels of the target analytes in bona fide clinical samples. The method permits the specific quantification of individual protein isoforms and addresses the difficult problem of protein heterogeneity in clinical proteomics applications.
Authors: A Prakash; T Rezai; B Krastins; D Sarracino; M Athanas; P Russo; M M Ross; H Zhang; Y Tian; V Kulasingam; A P Drabovich; C Smith; I Batruch; L Liotta; E Petricoin; E P Diamandis; D W Chan; M F Lopez Journal: J Proteome Res Date: 2010-11-02 Impact factor: 4.466
Authors: José López-Miranda; Pablo Pérez-Martínez; Carmen Marín; Juan A Moreno; Purificación Gómez; Francisco Pérez-Jiménez Journal: Curr Opin Lipidol Date: 2006-04 Impact factor: 4.776
Authors: Anne K Callesen; Jonna S Madsen; Werner Vach; Torben A Kruse; Ole Mogensen; Ole N Jensen Journal: Proteomics Date: 2009-03 Impact factor: 3.984
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
Authors: Paul E Oran; Jason W Jarvis; Chad R Borges; Nisha D Sherma; Randall W Nelson Journal: Proteomics Clin Appl Date: 2011-06-08 Impact factor: 3.494
Authors: Mario Di Napoli; Mitchell S V Elkind; Daniel Agustin Godoy; Puneetpal Singh; Francesca Papa; Aurel Popa-Wagner Journal: Expert Rev Cardiovasc Ther Date: 2011-12
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
Authors: Becky C Carlyle; Robert R Kitchen; Jing Zhang; Rashaun S Wilson; Tukiet T Lam; Joel S Rozowsky; Kenneth R Williams; Nenad Sestan; Mark B Gerstein; Angus C Nairn Journal: J Proteome Res Date: 2018-09-06 Impact factor: 4.466
Authors: Clark M Henderson; James G Bollinger; Jessica O Becker; Jennifer M Wallace; Thomas J Laha; Michael J MacCoss; Andrew N Hoofnagle Journal: Proteomics Clin Appl Date: 2017-03-06 Impact factor: 3.494
Authors: Hussein Yassine; Chad R Borges; Matthew R Schaab; Dean Billheimer; Craig Stump; Peter Reaven; Serrine S Lau; Randall Nelson Journal: Proteomics Clin Appl Date: 2013-07-09 Impact factor: 3.494
Authors: Olgica Trenchevska; Nisha D Sherma; Paul E Oran; Peter D Reaven; Randall W Nelson; Dobrin Nedelkov Journal: J Proteomics Date: 2014-12-27 Impact factor: 4.044