Khorasani Maryam, Shahbazi Shirin, Hosseinkhan Nazanin, Mahdian Reza
Molecular Medicine Department, Pasteur Institute of Iran, Tehran, Iran.
Department of Medical Genetics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
Int J Mol Cell Med. 2019 Spring;8(2):103-114. doi: 10.22088/IJMCM.BUMS.8.2.103. Epub 2019 Oct 29.
Early diagnosis of prostate cancer (PCa) as the second most common cancer in men is not associated with precise and specific results. Thus, alternate methods with high specificity and sensitivity are needed for accurate and timely detection of PCa. MicroRNAs regulate the molecular pathways involved in cancer by targeting multiple genes. The aberrant expression of the microRNAs has been reported in different cancer types including PCa. In this bioinformatics study, we studied differential expression profiles of microRNAs and their target genes in four PCa gene expression omnibus (GEO) databases. PCa diagnostic biomarker candidates were investigated using bioinformatics tools for analysis of gene expression data, microRNA target prediction, pathway and GO annotation, as well as ROC curves. The results of this study revealed significant changes in the expression of 14 microRNAs and 40 relevant target genes, which ultimately composed four combination panels (miR- 375+96+663/ miR- 133b+143- 3p + 205/ + + / + +) as candidate biomarkers capable to distinguish between PCa tumor samples and normal prostate tissue samples. These biomarkers may be suggested for a more accurate early diagnosis of PCa patients along with current diagnostic tests.
前列腺癌（PCa）是男性中第二常见的癌症，其早期诊断并未带来精确且特异的结果。因此，需要具有高特异性和敏感性的替代方法来准确、及时地检测前列腺癌。微小RNA通过靶向多个基因来调控参与癌症的分子途径。在包括前列腺癌在内的不同癌症类型中，均已报道了微小RNA的异常表达。在这项生物信息学研究中，我们在四个前列腺癌基因表达综合数据库（GEO）中研究了微小RNA及其靶基因的差异表达谱。使用生物信息学工具对前列腺癌诊断生物标志物候选物进行了研究，以分析基因表达数据、预测微小RNA靶标、进行通路和基因本体注释以及绘制ROC曲线。本研究结果揭示了14种微小RNA和40个相关靶基因表达的显著变化，最终组成了四个组合面板（miR-375+96+663/miR-133b+143-3p+205/++/+ ++）作为能够区分前列腺癌肿瘤样本和正常前列腺组织样本的候选生物标志物。除了当前的诊断测试外，这些生物标志物可能有助于更准确地早期诊断前列腺癌患者。
