Literature DB >> 20307887

Fast proteomic protocol for biomarker fingerprinting in cancerous cells.

Jenny M Armenta1, Milagros Perez, Xu Yang, Danielle Shapiro, Debby Reed, Leepika Tuli, Carla V Finkielstein, Iulia M Lazar.   

Abstract

The advance of novel technologies that will enable the detection of large sets of biomarker proteins, to greatly improve the sensitivity and specificity of an assay, represents a major objective in biomedical research. To demonstrate the power of mass spectrometry (MS) detection for large-scale biomarker screening in cancer research, a simple, one-step approach for fast biomarker fingerprinting in complex cellular extracts is described. MCF-7 breast cancer cells were used as a model system. Fast proteomic profiling of whole cellular extracts was achieved on a linear trap quadrupole (LTQ) mass spectrometer by one of the following techniques: (a) data-dependent liquid chromatography (LC)-MS/MS of un-labeled cell extracts, (b) data-dependent LC-MS/MS with pulsed Q dissociation (PQD) detection of iTRAQ labeled samples, and (c) multiple reaction monitoring (MRM)-MS of low abundant proteins that could not be detected with data-dependent MS/MS. The data-dependent LC-MS/MS analysis of MCF-7 cells enabled the identification of 796 proteins (p<0.001) and the simultaneous detection of 156 previously reported putative cancer biomarkers. PQD detection of iTRAQ labeled cells resulted in the detection of 389 proteins and 64 putative biomarkers. MRM-MS analysis enabled the successful monitoring of a panel of low-abundance proteins in one single experiment, highlighting the utility of this technique for targeted analysis in cancer investigations. These results demonstrate that MS-based technologies relying on a one-step separation protocol have the potential to revolutionize biomarker research and screening applications by enabling fast, sensitive and reliable detection of large panels of putative biomarkers. To further stimulate the exploration of proteins that have been previously reported in the literature to be differentially expressed in a variety of cancers, an extensive list of approximately 1100 candidate biomarkers has been compiled and included in the manuscript. Copyright 2010 Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 20307887      PMCID: PMC2856699          DOI: 10.1016/j.chroma.2010.02.065

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  53 in total

Review 1.  Proteomics for cancer biomarker discovery.

Authors:  Pothur R Srinivas; Mukesh Verma; Yinming Zhao; Sudhir Srivastava
Journal:  Clin Chem       Date:  2002-08       Impact factor: 8.327

2.  Cancer proteomics: in pursuit of "true" biomarker discovery.

Authors:  Zhen Zhang; Daniel W Chan
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2005-10       Impact factor: 4.254

3.  Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and cICAT with multidimensional liquid chromatography and tandem mass spectrometry.

Authors:  Leroi DeSouza; Georg Diehl; Mary Joe Rodrigues; Jingzhong Guo; Alexander D Romaschin; Terence J Colgan; K W Michael Siu
Journal:  J Proteome Res       Date:  2005 Mar-Apr       Impact factor: 4.466

4.  Multiple reaction monitoring to identify sites of protein phosphorylation with high sensitivity.

Authors:  Richard D Unwin; John R Griffiths; Michael K Leverentz; Agnes Grallert; Iain M Hagan; Anthony D Whetton
Journal:  Mol Cell Proteomics       Date:  2005-05-27       Impact factor: 5.911

Review 5.  A perspective on the use of iTRAQ reagent technology for protein complex and profiling studies.

Authors:  Lynn R Zieske
Journal:  J Exp Bot       Date:  2006-03-30       Impact factor: 6.992

Review 6.  Population proteomics: the concept, attributes, and potential for cancer biomarker research.

Authors:  Dobrin Nedelkov; Urban A Kiernan; Eric E Niederkofler; Kemmons A Tubbs; Randall W Nelson
Journal:  Mol Cell Proteomics       Date:  2006-05-30       Impact factor: 5.911

7.  The 4F2hc surface antigen is necessary for expression of system L-like neutral amino acid-transport activity in C6-BU-1 rat glioma cells: evidence from expression studies in Xenopus laevis oocytes.

Authors:  S Bröer; A Bröer; B Hamprecht
Journal:  Biochem J       Date:  1995-12-15       Impact factor: 3.857

8.  Evaluation of data-dependent versus targeted shotgun proteomic approaches for monitoring transcription factor expression in breast cancer.

Authors:  Charanjit Sandhu; Johannes A Hewel; Gwenael Badis; Shaheynoor Talukder; Jian Liu; Timothy R Hughes; Andrew Emili
Journal:  J Proteome Res       Date:  2008-02-27       Impact factor: 4.466

9.  A list of candidate cancer biomarkers for targeted proteomics.

Authors:  Malu Polanski; N Leigh Anderson
Journal:  Biomark Insights       Date:  2007-02-07

10.  Identification of the functional role of peroxiredoxin 6 in the progression of breast cancer.

Authors:  Xin-Zhong Chang; Da-Qiang Li; Yi-Feng Hou; Jiong Wu; Jin-Song Lu; Gen-Hong Di; Wei Jin; Zhou-Luo Ou; Zhen-Zhou Shen; Zhi-Ming Shao
Journal:  Breast Cancer Res       Date:  2007       Impact factor: 6.466

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  4 in total

1.  Quantification of beta-catenin signaling components in colon cancer cell lines, tissue sections, and microdissected tumor cells using reaction monitoring mass spectrometry.

Authors:  Yi Chen; Mike Gruidl; Elizabeth Remily-Wood; Richard Z Liu; Steven Eschrich; Mark Lloyd; Aejaz Nasir; Marilyn M Bui; Emina Huang; David Shibata; Timothy Yeatman; John M Koomen
Journal:  J Proteome Res       Date:  2010-08-06       Impact factor: 4.466

2.  Fast Enzymatic Processing of Proteins for MS Detection with a Flow-through Microreactor.

Authors:  Iulia M Lazar; Jingren Deng; Nicole Smith
Journal:  J Vis Exp       Date:  2016-04-06       Impact factor: 1.355

3.  Microfluidic LC device with orthogonal sample extraction for on-chip MALDI-MS detection.

Authors:  Iulia M Lazar; Jarod L Kabulski
Journal:  Lab Chip       Date:  2013-06-07       Impact factor: 6.799

4.  Cell Cycle Model System for Advancing Cancer Biomarker Research.

Authors:  Iulia M Lazar; Ina Hoeschele; Juliana de Morais; Milagros J Tenga
Journal:  Sci Rep       Date:  2017-12-21       Impact factor: 4.379

  4 in total

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