Literature DB >> 20839112

Urinary proteome profiling using 2D-DIGE and LC-MS/MS.

Mark E Weeks1.   

Abstract

Proteomic methodologies have been at the forefront of cancer research for several years. The use of proteomic strategies to study all expressed genes aims to discover biomarkers indicative of the physiological state of cancer cells at specific time points, enabling early diagnosis, following cancer development/progression, screening and monitoring the efficacy of new therapeutic agents. Onco-proteomics has the potential to impact on oncology practice by delivering individualised highly selective clinical care. 2D-DIGE (2D difference in gel electrophoresis) enables simultaneous examination and comparison of multiple samples using cyanine dyes to label amino acid residues that are then separated based on charge and mass. These advantages combined with universal availability have until recently made 2D-DIGE a first method of choice in cancer proteome analysis of diverse specimens, including tissues, cell lines, blood and other body fluids.

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Year:  2010        PMID: 20839112     DOI: 10.1007/978-1-60761-780-8_18

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


  3 in total

1.  Identification of novel serological tumor markers for human prostate cancer using integrative transcriptome and proteome analysis.

Authors:  Zhao-dong Han; Yan-qiong Zhang; Hui-chan He; Qi-shan Dai; Guo-qiang Qin; Jia-hong Chen; Chao Cai; Xin Fu; Xue-cheng Bi; Jian-guo Zhu; Dong-jiang Liao; Xin-peng Lu; Zi-yao Mo; Yun-ping Zhu; Wei-de Zhong
Journal:  Med Oncol       Date:  2012-01-04       Impact factor: 3.064

2.  Potential urine proteomics biomarkers for primary nephrotic syndrome.

Authors:  Young Wook Choi; Yang Gyun Kim; Min-Young Song; Ju-Young Moon; Kyung-Hwan Jeong; Tae-Won Lee; Chun-Gyoo Ihm; Kang-Sik Park; Sang-Ho Lee
Journal:  Clin Proteomics       Date:  2017-05-16       Impact factor: 3.988

3.  An integrative proteomics and interaction network-based classifier for prostate cancer diagnosis.

Authors:  Fu-neng Jiang; Hui-chan He; Yan-qiong Zhang; Deng-Liang Yang; Jie-Hong Huang; Yun-xin Zhu; Ru-jun Mo; Guo Chen; Sheng-bang Yang; Yan-ru Chen; Wei-de Zhong; Wen-Liang Zhou
Journal:  PLoS One       Date:  2013-05-30       Impact factor: 3.240

  3 in total

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