alexa Proteomic detection of cancer in asbestosis patients using SELDI-TOF discovered serum protein biomarkers.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Data Mining in Genomics & Proteomics

Author(s): Tooker BC, Newman LS, Bowler RP, Karjalainen A, Oksa P,

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Abstract OBJECTIVES: To identify biomarkers for cancer in asbestosis patients. METHODS: SELDI-TOF and CART were used to identify serum biomarker profiles in 35 asbestosis patients who subsequently developed cancer and 35 did not develop cancer. RESULTS: Three polypeptide peaks (5707.01, 6598.10, and 20,780.70 Da) could predict the development of cancer with 87\% sensitivity and 70\% specificity. The first two peaks were identified as KIF18A and KIF5A, respectively, and are part of the Kinesin Superfamily of proteins. CONCLUSIONS: We identified two Kinesin proteins that can be potentially used as blood biomarkers to identify asbestosis patients at risk of developing lung cancer. This article was published in Biomarkers and referenced in Journal of Data Mining in Genomics & Proteomics

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