前列腺癌
背景(考古学)
计算生物学
癌症
生物标志物发现
癌症生物标志物
生物信息学
医学
蛋白质组学
生物
基因
遗传学
古生物学
作者
Tânia Lima,Rita Ferreira,Marina Freitas,Rui Henrique,Rui Vitorino,Margarida Fardilha
标识
DOI:10.1021/acs.jproteome.1c00763
摘要
Prostate cancer (PCa) is the most prevalent noncutaneous cancer among men. The limited accuracy and/or invasive nature of the current diagnostic tools have driven the demand for new and noninvasive biomarkers. Urine as a noninvasive sample that contains prostatic secretions is a promising source of PCa markers. The automatic text-mining functionality of VOSviewer was used to retrieve and create co-occurrence networks of terms associated with PCa. These results were complemented with DisGENET data, a repository of PCa associations, and with a recent bioinformatic analysis integrating all differentially expressed proteins identified in tumor tissue and urine from PCa patients to address the limited term selection of VOSviewer. Afterward, the results were integrated with gene expression data from the Gene Expression Omnibus database to correlate gene and protein levels. This study suggests AXIN2, GSTM2, KLK3, LGALS3, MSMB, PRTFDC1, and SH3RF1 as important entities in PCa context. KLK, LGALS3, and MSMB proteins are common to a previous bioinformatic analysis, and a concordance was found between the levels of gene and protein expression. The applicability of the pipeline presented here was validated by showing altered urinary levels of galectin-3 protein in PCa patients compared to noncancer subjects.
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