Literature DB >> 21553213

14-3-3 protein beta/alpha as a urinary biomarker for renal cell carcinoma: proteomic analysis of cyst fluid.

Satoru Minamida1, Masatsugu Iwamura, Yoshio Kodera, Yusuke Kawashima, Kenichi Tabata, Kazumasa Matsumoto, Tetsuo Fujita, Takefumi Satoh, Tadakazu Maeda, Shiro Baba.   

Abstract

Although various samples, including tissue, cells, serum, and urine, from patients with renal cell carcinoma (RCC) have been analyzed, biomarkers with diagnostic value have yet to be identified. We used a proteomics approach to analyze cyst fluid in cases of cyst-associated RCC to identify accessible and abundant proteins that are overexpressed and/or secreted by RCC cells. Proteins in the cyst fluid were separated by reverse-phase high-performance liquid chromatography and agarose two-dimensional gel electrophoresis and were identified by tandem mass spectrometry. We conducted a National Center for Biotechnology Information search and a MEDLINE search to predict the function of these identified proteins and to select a tumor-marker candidate protein. Our search resulted in the identification and selection of the differentially regulated protein known as 14-3-3 protein beta/alpha, which was overexpressed in cyst fluid from cyst-associated RCC but has not been previously associated with RCC. We then measured its incidence through Western blotting of various normal and RCC samples (serum, urine, tissue, and cyst fluid). The expression levels of 14-3-3 protein beta/alpha were higher in urine samples from patients with RCC than in samples from healthy volunteers. Receiver operating characteristic (ROC) curve analyses were performed to assess this potential biomarker; these data (area under the ROC curve value was 0.8813) indicate a high degree of accuracy for this screening method. 14-3-3 Protein beta/alpha may be a diagnostically useful biomarker for early diagnosis of RCC.

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Year:  2011        PMID: 21553213     DOI: 10.1007/s00216-011-5057-5

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  12 in total

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Authors:  Hiromi I Wettersten; Robert H Weiss
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Review 3.  Molecular diagnostic trends in urological cancer: biomarkers for non-invasive diagnosis.

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5.  Identification of 14-3-3β gene as a novel miR-152 target using a proteome-based approach.

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9.  Proteomics-Based Identification of Differentially Abundant Proteins from Human Keratinocytes Exposed to Arsenic Trioxide.

Authors:  Udensi K Udensi; Alan J Tackett; Stephanie Byrum; Nathan L Avaritt; Deepanwita Sengupta; Linley W Moreland; Paul B Tchounwou; Raphael D Isokpehi
Journal:  J Proteomics Bioinform       Date:  2014-07

10.  Urinary signatures of Renal Cell Carcinoma investigated by peptidomic approaches.

Authors:  Clizia Chinello; Marta Cazzaniga; Gabriele De Sio; Andrew James Smith; Erica Gianazza; Angelica Grasso; Francesco Rocco; Stefano Signorini; Marco Grasso; Silvano Bosari; Italo Zoppis; Mohammed Dakna; Yuri E M van der Burgt; Giancarlo Mauri; Fulvio Magni
Journal:  PLoS One       Date:  2014-09-09       Impact factor: 3.240

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