Literature DB >> 16674112

Enhanced analysis of metastatic prostate cancer using stable isotopes and high mass accuracy instrumentation.

Patrick A Everley1, Corey E Bakalarski, Joshua E Elias, Carol G Waghorne, Sean A Beausoleil, Scott A Gerber, Brendan K Faherty, Bruce R Zetter, Steven P Gygi.   

Abstract

The primary goal of proteomics is to gain a better understanding of biological function at the protein expression level. As the field matures, numerous technologies are being developed to aid in the identification, quantification and characterization of protein expression and post-translational modifications on a near-global scale. Stable isotope labeling by amino acids in cell culture is one such technique that has shown broad biological applications. While we have recently shown the application of this technology to a model of metastatic prostate cancer, we now report a substantial improvement in quantitative analysis using a linear ion-trap Fourier transform ion cyclotron resonance mass spectrometer (LTQ FT) and novel quantification software. This resulted in the quantification of nearly 1400 proteins, a greater than 3-fold increase in comparison to our earlier study. This dramatic increase in proteome coverage can be attributed to (1) use of a double-labeling strategy, (2) greater sensitivity, speed and mass accuracy provided by the LTQ FT mass spectrometer, and (3) more robust quantification software. Finally, by using a concatenated target/decoy protein database for our peptide searches, we now report these data in the context of an estimated false-positive rate of one percent.

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Year:  2006        PMID: 16674112     DOI: 10.1021/pr0504891

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  25 in total

1.  Quantitative proteomics analysis reveals molecular networks regulated by epidermal growth factor receptor level in head and neck cancer.

Authors:  Wei Yang; Quan Cai; Vivian W Y Lui; Patrick A Everley; Jayoung Kim; Neil Bhola; Kelly M Quesnelle; Bruce R Zetter; Hanno Steen; Michael R Freeman; Jennifer R Grandis
Journal:  J Proteome Res       Date:  2010-06-04       Impact factor: 4.466

2.  Comparative assessment of site assignments in CID and electron transfer dissociation spectra of phosphopeptides discloses limited relocation of phosphate groups.

Authors:  Nikolai Mischerikow; A F Maarten Altelaar; J Daniel Navarro; Shabaz Mohammed; Albert J R Heck
Journal:  Mol Cell Proteomics       Date:  2010-03-16       Impact factor: 5.911

3.  15N metabolic labeling of mammalian tissue with slow protein turnover.

Authors:  Daniel B McClatchy; Meng-Qiu Dong; Christine C Wu; John D Venable; John R Yates
Journal:  J Proteome Res       Date:  2007-03-22       Impact factor: 4.466

4.  Quantification of the synaptosomal proteome of the rat cerebellum during post-natal development.

Authors:  Daniel B McClatchy; Lujian Liao; Sung Kyu Park; John D Venable; John R Yates
Journal:  Genome Res       Date:  2007-08-03       Impact factor: 9.043

Review 5.  Accurate mass measurements in proteomics.

Authors:  Tao Liu; Mikhail E Belov; Navdeep Jaitly; Wei-Jun Qian; Richard D Smith
Journal:  Chem Rev       Date:  2007-07-25       Impact factor: 60.622

6.  Target-Decoy-Based False Discovery Rate Estimation for Large-Scale Metabolite Identification.

Authors:  Xusheng Wang; Drew R Jones; Timothy I Shaw; Ji-Hoon Cho; Yuanyuan Wang; Haiyan Tan; Boer Xie; Suiping Zhou; Yuxin Li; Junmin Peng
Journal:  J Proteome Res       Date:  2018-05-29       Impact factor: 4.466

7.  MassMatrix: a database search program for rapid characterization of proteins and peptides from tandem mass spectrometry data.

Authors:  Hua Xu; Michael A Freitas
Journal:  Proteomics       Date:  2009-03       Impact factor: 3.984

8.  Combined Antibody/Lectin Enrichment Identifies Extensive Changes in the O-GlcNAc Sub-proteome upon Oxidative Stress.

Authors:  Albert Lee; Devin Miller; Roger Henry; Venkata D P Paruchuri; Robert N O'Meally; Tatiana Boronina; Robert N Cole; Natasha E Zachara
Journal:  J Proteome Res       Date:  2016-10-14       Impact factor: 4.466

9.  Transcriptional interference among the murine beta-like globin genes.

Authors:  Xiao Hu; Susan Eszterhas; Nicolas Pallazzi; Eric E Bouhassira; Jennifer Fields; Osamu Tanabe; Scott A Gerber; Michael Bulger; James Douglas Engel; Mark Groudine; Steven Fiering
Journal:  Blood       Date:  2006-10-31       Impact factor: 22.113

10.  The impact of microRNAs on protein output.

Authors:  Daehyun Baek; Judit Villén; Chanseok Shin; Fernando D Camargo; Steven P Gygi; David P Bartel
Journal:  Nature       Date:  2008-07-30       Impact factor: 49.962

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