Literature DB >> 21468938

Plasma biomarker discovery using 3D protein profiling coupled with label-free quantitation.

Lynn A Beer1, Hsin-Yao Tang, Kurt T Barnhart, David W Speicher.   

Abstract

In-depth quantitative profiling of human plasma samples for biomarker discovery remains quite challenging. One promising alternative to chemical derivatization with stable isotope labels for quantitative comparisons is direct, label-free, quantitative comparison of raw LC-MS data. But, in order to achieve high-sensitivity detection of low-abundance proteins, plasma proteins must be extensively pre-fractionated, and results from LC-MS runs of all fractions must be integrated efficiently in order to avoid misidentification of variations in fractionation from sample to sample as "apparent" biomarkers. This protocol describes a powerful 3D protein profiling method for comprehensive analysis of human serum or plasma proteomes, which combines abundant protein depletion and high-sensitivity GeLC-MS/MS with label-free quantitation of candidate biomarkers.

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Year:  2011        PMID: 21468938      PMCID: PMC3157887          DOI: 10.1007/978-1-61779-068-3_1

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  25 in total

1.  Characterization of the low molecular weight human serum proteome.

Authors:  Radhakrishna S Tirumalai; King C Chan; DaRue A Prieto; Haleem J Issaq; Thomas P Conrads; Timothy D Veenstra
Journal:  Mol Cell Proteomics       Date:  2003-08-13       Impact factor: 5.911

2.  Profiling core proteomes of human cell lines by one-dimensional PAGE and liquid chromatography-tandem mass spectrometry.

Authors:  Markus Schirle; Marie-Anne Heurtier; Bernhard Kuster
Journal:  Mol Cell Proteomics       Date:  2003-10-06       Impact factor: 5.911

Review 3.  The ABC's (and XYZ's) of peptide sequencing.

Authors:  Hanno Steen; Matthias Mann
Journal:  Nat Rev Mol Cell Biol       Date:  2004-09       Impact factor: 94.444

4.  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.

Authors:  Gilbert S Omenn; 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
Journal:  Proteomics       Date:  2005-08       Impact factor: 3.984

Review 5.  Higher dimensional (Hi-D) separation strategies dramatically improve the potential for cancer biomarker detection in serum and plasma.

Authors:  Seth A Hoffman; Won-A Joo; Lynn A Echan; David W Speicher
Journal:  J Chromatogr B Analyt Technol Biomed Life Sci       Date:  2006-11-30       Impact factor: 3.205

Review 6.  Comparative LC-MS: a landscape of peaks and valleys.

Authors:  Antoine H P America; Jan H G Cordewener
Journal:  Proteomics       Date:  2008-02       Impact factor: 3.984

7.  Evaluation of three principally different intact protein prefractionation methods for plasma biomarker discovery.

Authors:  Maria Pernemalm; Lukas M Orre; Johan Lengqvist; Pernilla Wikström; Rolf Lewensohn; Janne Lehtiö
Journal:  J Proteome Res       Date:  2008-06-13       Impact factor: 4.466

Review 8.  Mining the plasma proteome for cancer biomarkers.

Authors:  Samir M Hanash; Sharon J Pitteri; Vitor M Faca
Journal:  Nature       Date:  2008-04-03       Impact factor: 49.962

9.  Challenges in deriving high-confidence protein identifications from data gathered by a HUPO plasma proteome collaborative study.

Authors:  David J States; Gilbert S Omenn; Thomas W Blackwell; Damian Fermin; Jimmy Eng; David W Speicher; Samir M Hanash
Journal:  Nat Biotechnol       Date:  2006-03       Impact factor: 54.908

10.  Statistical implications of pooling RNA samples for microarray experiments.

Authors:  Xuejun Peng; Constance L Wood; Eric M Blalock; Kuey Chu Chen; Philip W Landfield; Arnold J Stromberg
Journal:  BMC Bioinformatics       Date:  2003-06-24       Impact factor: 3.169

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  7 in total

1.  Systematic comparison of fractionation methods for in-depth analysis of plasma proteomes.

Authors:  Zhijun Cao; Hsin-Yao Tang; Huan Wang; Qin Liu; David W Speicher
Journal:  J Proteome Res       Date:  2012-05-18       Impact factor: 4.466

2.  Proteome Analysis Using Gel-LC-MS/MS.

Authors:  Aaron R Goldman; Lynn A Beer; Hsin-Yao Tang; Peter Hembach; Delaine Zayas-Bazan; David W Speicher
Journal:  Curr Protoc Protein Sci       Date:  2019-06-10

3.  A xenograft mouse model coupled with in-depth plasma proteome analysis facilitates identification of novel serum biomarkers for human ovarian cancer.

Authors:  Hsin-Yao Tang; Lynn A Beer; Tony Chang-Wong; Rachel Hammond; Phyllis Gimotty; George Coukos; David W Speicher
Journal:  J Proteome Res       Date:  2011-11-18       Impact factor: 4.466

4.  In-depth analysis of a plasma or serum proteome using a 4D protein profiling method.

Authors:  Hsin-Yao Tang; Lynn A Beer; David W Speicher
Journal:  Methods Mol Biol       Date:  2011

5.  Enhanced identification of zero-length chemical cross-links using label-free quantitation and high-resolution fragment ion spectra.

Authors:  Sira Sriswasdi; Sandra L Harper; Hsin-Yao Tang; David W Speicher
Journal:  J Proteome Res       Date:  2014-01-07       Impact factor: 4.466

6.  Protein isoform-specific validation defines multiple chloride intracellular channel and tropomyosin isoforms as serological biomarkers of ovarian cancer.

Authors:  Hsin-Yao Tang; Lynn A Beer; Janos L Tanyi; Rugang Zhang; Qin Liu; David W Speicher
Journal:  J Proteomics       Date:  2013-06-21       Impact factor: 4.044

7.  Shotgun proteomics identifies serum fibronectin as a candidate diagnostic biomarker for inclusion in future multiplex tests for ectopic pregnancy.

Authors:  Jeremy K Brown; Katarina B Lauer; Emily L Ironmonger; Neil F Inglis; Tom H Bourne; Hilary O D Critchley; Andrew W Horne
Journal:  PLoS One       Date:  2013-06-24       Impact factor: 3.240

  7 in total

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