Literature DB >> 18615424

Quantitative proteomic analysis to discover potential diagnostic markers and therapeutic targets in human renal cell carcinoma.

Noboru Okamura1, Taro Masuda, Akinobu Gotoh, Toshiro Shirakawa, Shuji Terao, Naoki Kaneko, Kazuki Suganuma, Makoto Watanabe, Toshiya Matsubara, Ryota Seto, Jun Matsumoto, Megumi Kawakami, Motohiro Yamamori, Tsutomu Nakamura, Tatsurou Yagami, Toshiyuki Sakaeda, Masato Fujisawa, Osamu Nishimura, Katsuhiko Okumura.   

Abstract

Renal cell carcinoma (RCC) is relatively resistant to chemotherapy and radiotherapy. Recent advances in drug development are providing novel agents for the treatment of RCC, but the effects are still minimal. In addition, there is an urgent need to identify diagnostic markers for RCC. In this report, to discover potential diagnostic markers and therapeutic targets, we subjected RCC samples to a quantitative proteomic analysis utilizing 2-nitrobenzenesulfenyl (NBS) reagent. Proteins were extracted from RCC and adjacent normal tissue, obtained surgically from patients, and labeled with NBS reagent containing six (12)C or (13)C. This was followed by trypsin digestion and the enrichment of labeled peptides. Samples were then subjected to analysis by MALDI-TOF MS. NBS-labeled peptides with a 6 Da difference were identified by MS/MS. Thirty-four proteins were upregulated in more than 60% of the patients of which some were previously known, and some were novel. The identity of a few proteins was confirmed by Western blotting and quantitative real time RT-PCR. The results suggest that NBS-based quantitative proteomic analysis is useful for discovering diagnostic markers and therapeutic targets for RCC.

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Year:  2008        PMID: 18615424     DOI: 10.1002/pmic.200700619

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  15 in total

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3.  Linkage of microRNA and proteome-based profiling data sets: a perspective for the priorization of candidate biomarkers in renal cell carcinoma?

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4.  Identification and characterization of human leukocyte antigen class I ligands in renal cell carcinoma cells.

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Journal:  Proteomics       Date:  2011-05-18       Impact factor: 3.984

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8.  KEGG spider: interpretation of genomics data in the context of the global gene metabolic network.

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9.  Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling.

Authors:  A Atrih; M A V Mudaliar; P Zakikhani; D J Lamont; J T-J Huang; S E Bray; G Barton; S Fleming; G Nabi
Journal:  Br J Cancer       Date:  2014-02-18       Impact factor: 7.640

10.  Quantitative proteomics approach to screening of potential diagnostic and therapeutic targets for laryngeal carcinoma.

Authors:  Li Li; Zhenwei Zhang; Chengyu Wang; Lei Miao; Jianpeng Zhang; Jiasen Wang; Binghua Jiao; Shuwei Zhao
Journal:  PLoS One       Date:  2014-02-27       Impact factor: 3.240

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