Literature DB >> 21999828

Targeted protein-omic methods are bridging the gap between proteomic and hypothesis-driven protein analysis approaches.

Ronald J Hause1, Hyung-Do Kim, Kin K Leung, Richard Baker Jones.   

Abstract

While proteomic methods have illuminated many areas of biological protein space, many fundamental questions remain with regard to systems-level relationships between mRNAs, proteins and cell behaviors. While mass spectrometric methods offer a panoramic picture of the relative expression and modification of large numbers of proteins, they are neither optimal for the analysis of predefined targets across large numbers of samples nor for assessing differences in proteins between individual cells or cell compartments. Conversely, traditional antibody-based methods are effective at sensitively analyzing small numbers of proteins across small numbers of conditions, and can be used to analyze relative differences in protein abundance and modification between cells and cell compartments. However, traditional antibody-based approaches are not optimal for analyzing large numbers of protein abundances and modifications across many samples. In this article, we will review recent advances in methodologies and philosophies behind several microarray-based, intermediate-level, 'protein-omic' methods, including a focus on reverse-phase lysate arrays and micro-western arrays, which have been helpful for bridging gaps between large- and small-scale protein analysis approaches and have provided insight into the roles that protein systems play in several biological processes.

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Year:  2011        PMID: 21999828      PMCID: PMC3269123          DOI: 10.1586/epr.11.49

Source DB:  PubMed          Journal:  Expert Rev Proteomics        ISSN: 1478-9450            Impact factor:   3.940


  78 in total

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Review 5.  ERBB receptors and cancer: the complexity of targeted inhibitors.

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Review 6.  Use of reverse phase protein microarrays and reference standard development for molecular network analysis of metastatic ovarian carcinoma.

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Journal:  Mol Cell Proteomics       Date:  2005-01-25       Impact factor: 5.911

Review 7.  Epidermal growth factor receptor: mechanisms of activation and signalling.

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Journal:  Mol Cell Proteomics       Date:  2002-05       Impact factor: 5.911

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  9 in total

Review 1.  The application of modular protein domains in proteomics.

Authors:  Joshua A Jadwin; Mari Ogiue-Ikeda; Kazuya Machida
Journal:  FEBS Lett       Date:  2012-04-21       Impact factor: 4.124

2.  The DIONESUS algorithm provides scalable and accurate reconstruction of dynamic phosphoproteomic networks to reveal new drug targets.

Authors:  Mark F Ciaccio; Vincent C Chen; Richard B Jones; Neda Bagheri
Journal:  Integr Biol (Camb)       Date:  2015-07       Impact factor: 2.192

Review 3.  Analytical challenges translating mass spectrometry-based phosphoproteomics from discovery to clinical applications.

Authors:  Anton B Iliuk; Justine V Arrington; Weiguo Andy Tao
Journal:  Electrophoresis       Date:  2014-07-10       Impact factor: 3.535

4.  Current dichotomy between traditional molecular biological and omic research in cancer biology and pharmacology.

Authors:  William C Reinhold
Journal:  World J Clin Oncol       Date:  2015-12-10

5.  Caffeic acid phenethyl ester suppresses the proliferation of human prostate cancer cells through inhibition of p70S6K and Akt signaling networks.

Authors:  Chih-Pin Chuu; Hui-Ping Lin; Mark F Ciaccio; John M Kokontis; Ronald J Hause; Richard A Hiipakka; Shutsung Liao; Richard Baker Jones
Journal:  Cancer Prev Res (Phila)       Date:  2012-05

6.  Cholestane-3β, 5α, 6β-triol suppresses proliferation, migration, and invasion of human prostate cancer cells.

Authors:  Ching-Yu Lin; Chieh Huo; Li-Kuo Kuo; Richard A Hiipakka; Richard Baker Jones; Hui-Ping Lin; Yuwen Hung; Liang-Cheng Su; Jen-Chih Tseng; Ying-Yu Kuo; Yu-Ling Wang; Yasuhisa Fukui; Yung-Hsi Kao; John M Kokontis; Chien-Chih Yeh; Linyi Chen; Shiaw-Der Yang; Hsiao-Hui Fu; Ya-Wen Chen; Kelvin K C Tsai; Jang-Yang Chang; Chih-Pin Chuu
Journal:  PLoS One       Date:  2013-06-13       Impact factor: 3.240

7.  Protein quantitative trait loci identify novel candidates modulating cellular response to chemotherapy.

Authors:  Amy L Stark; Ronald J Hause; Lidija K Gorsic; Nirav N Antao; Shan S Wong; Sophie H Chung; Daniel F Gill; Hae K Im; Jamie L Myers; Kevin P White; Richard Baker Jones; M Eileen Dolan
Journal:  PLoS Genet       Date:  2014-04-03       Impact factor: 5.917

8.  Arecoline induces TNF-alpha production and Zonula Occludens-1 redistribution in mouse Sertoli TM4 cells.

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9.  Identification and validation of genetic variants that influence transcription factor and cell signaling protein levels.

Authors:  Ronald J Hause; Amy L Stark; Nirav N Antao; Lidija K Gorsic; Sophie H Chung; Christopher D Brown; Shan S Wong; Daniel F Gill; Jamie L Myers; Lida Anita To; Kevin P White; M Eileen Dolan; Richard Baker Jones
Journal:  Am J Hum Genet       Date:  2014-07-31       Impact factor: 11.025

  9 in total

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