Literature DB >> 16104056

Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.

Gilbert S Omenn1, David J States, Marcin Adamski, Thomas W Blackwell, Rajasree Menon, Henning Hermjakob, Rolf Apweiler, Brian B Haab, Richard J Simpson, James S Eddes, Eugene A Kapp, Robert L Moritz, Daniel W Chan, Alex J Rai, Arie Admon, Ruedi Aebersold, Jimmy Eng, William S Hancock, Stanley A Hefta, Helmut Meyer, Young-Ki Paik, Jong-Shin Yoo, Peipei Ping, Joel Pounds, Joshua Adkins, Xiaohong Qian, Rong Wang, Valerie Wasinger, Chi Yue Wu, Xiaohang Zhao, Rong Zeng, Alexander Archakov, Akira Tsugita, Ilan Beer, Akhilesh Pandey, Michael Pisano, Philip Andrews, Harald Tammen, David W Speicher, Samir M Hanash.   

Abstract

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

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Year:  2005        PMID: 16104056     DOI: 10.1002/pmic.200500358

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  224 in total

1.  Combining ultracentrifugation and peptide termini group-specific immunoprecipitation for multiplex plasma protein analysis.

Authors:  Sonja Volk; Thomas D Schreiber; David Eisen; Calvin Wiese; Hannes Planatscher; Christopher J Pynn; Dieter Stoll; Markus F Templin; Thomas O Joos; Oliver Pötz
Journal:  Mol Cell Proteomics       Date:  2012-04-23       Impact factor: 5.911

Review 2.  Proteomics and systems biology: current and future applications in the nutritional sciences.

Authors:  J Bernadette Moore; Mark E Weeks
Journal:  Adv Nutr       Date:  2011-06-28       Impact factor: 8.701

Review 3.  Comparative human salivary and plasma proteomes.

Authors:  J A Loo; W Yan; P Ramachandran; D T Wong
Journal:  J Dent Res       Date:  2010-08-25       Impact factor: 6.116

Review 4.  The grand challenge to decipher the cancer proteome.

Authors:  Samir Hanash; Ayumu Taguchi
Journal:  Nat Rev Cancer       Date:  2010-09       Impact factor: 60.716

5.  Proteomic analysis identification of a pattern of shared alterations in the secretome of dermal fibroblasts from systemic sclerosis and nephrogenic systemic fibrosis.

Authors:  Francesco Del Galdo; M Alexander Shaw; Sergio A Jimenez
Journal:  Am J Pathol       Date:  2010-08-19       Impact factor: 4.307

Review 6.  The application of mass-spectrometry-based protein biomarker discovery to theragnostics.

Authors:  Jonathan M Street; James W Dear
Journal:  Br J Clin Pharmacol       Date:  2010-04       Impact factor: 4.335

7.  A proteomic approach for plasma biomarker discovery with 8-plex iTRAQ labeling and SCX-LC-MS/MS.

Authors:  Haige Ye; Li Sun; Xiaojun Huang; Ping Zhang; Xiaoshu Zhao
Journal:  Mol Cell Biochem       Date:  2010-06-05       Impact factor: 3.396

8.  Amyloid β-induced FOXRED2 mediates neuronal cell death via inhibition of proteasome activity.

Authors:  SangMi Shim; WonJae Lee; HaeWon Chung; Yong-Keun Jung
Journal:  Cell Mol Life Sci       Date:  2010-10-23       Impact factor: 9.261

9.  Mass spectrometry in cancer biomarker research: a case for immunodepletion of abundant blood-derived proteins from clinical tissue specimens.

Authors:  Darue A Prieto; Donald J Johann; Bih-Rong Wei; Xiaoying Ye; King C Chan; Dwight V Nissley; R Mark Simpson; Deborah E Citrin; Crystal L Mackall; W Marston Linehan; Josip Blonder
Journal:  Biomark Med       Date:  2014       Impact factor: 2.851

Review 10.  Unleashing the power of proteomics to develop blood-based cancer markers.

Authors:  Ayumu Taguchi; Samir M Hanash
Journal:  Clin Chem       Date:  2012-10-24       Impact factor: 8.327

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