Literature DB >> 18287776

Label-free LC-MS method for the identification of biomarkers.

Richard E Higgs1, Michael D Knierman, Valentina Gelfanova, Jon P Butler, John E Hale.   

Abstract

Pharmaceutical companies and regulatory agencies are pursuing biomarkers as a means to increase the productivity of drug development. Quantifying differential levels of proteins from complex biological samples like plasma or cerebrospinal fluid is one specific approach being used to identify markers of drug action, efficacy, toxicity, etc. Academic investigators are also interested in markers that are diagnostic or prognostic of disease states. We report a comprehensive, fully automated, and label-free approach to relative protein quantification including: sample preparation, proteolytic protein digestion, LCMS/MS data acquisition, de-noising, mass and charge state estimation, chromatographic alignment, and peptide quantification via integration of extracted ion chromatograms. Additionally, we describe methods for transformation and normalization of the quantitative peptide levels in multiplexed measurements to improve precision for statistical analysis. Lastly, we outline how the described methods can be used to design and power biomarker discovery studies.

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Year:  2008        PMID: 18287776     DOI: 10.1007/978-1-59745-117-8_12

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


  19 in total

1.  Halogenated peptides as internal standards (H-PINS): introduction of an MS-based internal standard set for liquid chromatography-mass spectrometry.

Authors:  Hamid Mirzaei; Mi-Youn Brusniak; Lukas N Mueller; Simon Letarte; Julian D Watts; Ruedi Aebersold
Journal:  Mol Cell Proteomics       Date:  2009-05-01       Impact factor: 5.911

Review 2.  Protein analysis by shotgun/bottom-up proteomics.

Authors:  Yaoyang Zhang; Bryan R Fonslow; Bing Shan; Moon-Chang Baek; John R Yates
Journal:  Chem Rev       Date:  2013-02-26       Impact factor: 60.622

3.  A rapid, reproducible, on-the-fly orthogonal array optimization method for targeted protein quantification by LC/MS and its application for accurate and sensitive quantification of carbonyl reductases in human liver.

Authors:  Jin Cao; Vanessa Gonzalez-Covarrubias; Vanessa M Covarrubias; Robert M Straubinger; Hao Wang; Xiaotao Duan; Haoying Yu; Jun Qu; Javier G Blanco
Journal:  Anal Chem       Date:  2010-04-01       Impact factor: 6.986

4.  An IonStar Experimental Strategy for MS1 Ion Current-Based Quantification Using Ultrahigh-Field Orbitrap: Reproducible, In-Depth, and Accurate Protein Measurement in Large Cohorts.

Authors:  Xiaomeng Shen; Shichen Shen; Jun Li; Qiang Hu; Lei Nie; Chengjian Tu; Xue Wang; Benjamin Orsburn; Jianmin Wang; Jun Qu
Journal:  J Proteome Res       Date:  2017-05-25       Impact factor: 4.466

5.  Effect of carbon nanoparticles on renal epithelial cell structure, barrier function, and protein expression.

Authors:  Bonnie L Blazer-Yost; Amiraj Banga; Adam Amos; Ellen Chernoff; Xianyin Lai; Cheng Li; Somenath Mitra; Frank A Witzmann
Journal:  Nanotoxicology       Date:  2010-11-10       Impact factor: 5.913

6.  A straightforward and highly efficient precipitation/on-pellet digestion procedure coupled with a long gradient nano-LC separation and Orbitrap mass spectrometry for label-free expression profiling of the swine heart mitochondrial proteome.

Authors:  Xiaotao Duan; Rebeccah Young; Robert M Straubinger; Brian Page; Jin Cao; Hao Wang; Haoying Yu; John M Canty; Jun Qu
Journal:  J Proteome Res       Date:  2009-06       Impact factor: 4.466

7.  Proteomic expression profiling of Haemophilus influenzae grown in pooled human sputum from adults with chronic obstructive pulmonary disease reveal antioxidant and stress responses.

Authors:  Jun Qu; Alan J Lesse; Aimee L Brauer; Jin Cao; Steven R Gill; Timothy F Murphy
Journal:  BMC Microbiol       Date:  2010-06-01       Impact factor: 3.605

8.  Bioinformatics Tools for Mass Spectrometry-Based High-Throughput Quantitative Proteomics Platforms.

Authors:  Alexey V Nefedov; Miroslaw J Gilski; Rovshan G Sadygov
Journal:  Curr Proteomics       Date:  2011-07       Impact factor: 0.837

9.  An ion-current-based, comprehensive and reproducible proteomic strategy for comparative characterization of the cellular responses to novel anti-cancer agents in a prostate cell model.

Authors:  Chengjian Tu; Jun Li; Yahao Bu; David Hangauer; Jun Qu
Journal:  J Proteomics       Date:  2012-09-07       Impact factor: 4.044

10.  Ion-current-based proteomic profiling of the retina in a rat model of Smith-Lemli-Opitz syndrome.

Authors:  Chengjian Tu; Jun Li; Xiaosheng Jiang; Lowell G Sheflin; Bruce A Pfeffer; Matthew Behringer; Steven J Fliesler; Jun Qu
Journal:  Mol Cell Proteomics       Date:  2013-08-26       Impact factor: 5.911

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