Literature DB >> 17140865

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

Seth A Hoffman1, Won-A Joo, Lynn A Echan, David W Speicher.   

Abstract

The plasma proteome has a wide dynamic range of protein concentrations and is dominated by a few highly abundant proteins. Discovery of novel cancer biomarkers using proteomics is particularly challenging because specific biomarkers are expected to be low abundance proteins with normal blood concentrations of low nanograms per milliliter or less. Conventional, one- and two-dimensional proteomic methods including 2D PAGE, 2D DIGE, LC-MS/MS, and LC/LC-MS/MS do not have the capacity to consistently detect many proteins in this range. In contrast, new higher dimensional (Hi-D) separation strategies, utilizing more than two dimensions of fractionation, can profile the low abundance proteome.

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Year:  2006        PMID: 17140865     DOI: 10.1016/j.jchromb.2006.10.069

Source DB:  PubMed          Journal:  J Chromatogr B Analyt Technol Biomed Life Sci        ISSN: 1570-0232            Impact factor:   3.205


  14 in total

1.  Comparative proteomics analysis of serum proteins in ulcerative colitis patients.

Authors:  Nan Li; Xueming Wang; Yuefan Zhang; Junshan Zhai; Tuo Zhang; Kaihua Wei
Journal:  Mol Biol Rep       Date:  2011-12-24       Impact factor: 2.316

2.  Rapid verification of candidate serological biomarkers using gel-based, label-free multiple reaction monitoring.

Authors:  Hsin-Yao Tang; Lynn A Beer; Kurt T Barnhart; David W Speicher
Journal:  J Proteome Res       Date:  2011-07-26       Impact factor: 4.466

3.  Search for breast cancer biomarkers in fractionated serum samples by protein profiling with SELDI-TOF MS.

Authors:  Annemieke W J Opstal-van Winden; Jos H Beijnen; Arnoud Loof; Waander L van Heerde; Roel Vermeulen; Petra H M Peeters; Carla H van Gils
Journal:  J Clin Lab Anal       Date:  2012-01       Impact factor: 2.352

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

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

5.  A gel-free approach in vascular smooth muscle cell proteome: perspectives for a better insight into activation.

Authors:  Silvia Rocchiccioli; Lorenzo Citti; Claudia Boccardi; Nadia Ucciferri; Lorena Tedeschi; Caterina Lande; Maria Giovanna Trivella; Antonella Cecchettini
Journal:  Proteome Sci       Date:  2010-03-24       Impact factor: 2.480

6.  In-Depth, Reproducible Analysis of Human Plasma Using IgY 14 and SuperMix Immunodepletion.

Authors:  Lynn A Beer; Bonnie Ky; Kurt T Barnhart; David W Speicher
Journal:  Methods Mol Biol       Date:  2017

7.  Efficient Quantitative Comparisons of Plasma Proteomes Using Label-Free Analysis with MaxQuant.

Authors:  Lynn A Beer; Pengyuan Liu; Bonnie Ky; Kurt T Barnhart; David W Speicher
Journal:  Methods Mol Biol       Date:  2017

8.  Identification of multiple novel protein biomarkers shed by human serous ovarian tumors into the blood of immunocompromised mice and verified in patient sera.

Authors:  Lynn A Beer; Huan Wang; Hsin-Yao Tang; Zhijun Cao; Tony Chang-Wong; Janos L Tanyi; Rugang Zhang; Qin Liu; David W Speicher
Journal:  PLoS One       Date:  2013-03-27       Impact factor: 3.240

9.  High abundance proteins depletion vs low abundance proteins enrichment: comparison of methods to reduce the plasma proteome complexity.

Authors:  Renato Millioni; Serena Tolin; Lucia Puricelli; Stefano Sbrignadello; Gian Paolo Fadini; Paolo Tessari; Giorgio Arrigoni
Journal:  PLoS One       Date:  2011-05-04       Impact factor: 3.240

10.  Postoperative serum proteomic profiles may predict recurrence-free survival in high-risk primary breast cancer.

Authors:  Marie-Christine W Gast; Marc Zapatka; Harm van Tinteren; Marijke Bontenbal; Paul N Span; Vivianne C G Tjan-Heijnen; Jaco C Knol; Connie R Jimenez; Jan H M Schellens; Jos H Beijnen
Journal:  J Cancer Res Clin Oncol       Date:  2011-09-13       Impact factor: 4.553

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