Expression Analysis of miRNAs and Their Potential Role as Biomarkers for Prostate Cancer Detection

Abstract

Prostate cancer (PCa) is the second most frequent cancer diagnosed in men worldwide. The detection methods for PCa are either unreliable, like prostate-specific antigen (PSA), or extremely invasive, such as in the case of biopsies. Therefore, there is an urgent necessity for reliable and less invasive detection procedures that can differentiate between patients with benign diseases and those with cancer. In this matter, microRNAs (miRNAs) are suggested as potential biomarkers for cancer. MiRNAs have been found to be dysregulated in several different cancers, and these genetic alterations may present specific signatures for a given malignancy. Here, we examined the expression of miR141-3p, miR145-5p, miR146a-5p, and miR148b-3p in human tissue samples of PCa (n = 41) and benign prostatic diseases (BPD) (n = 30) using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). We combined the expression results with patient clinicopathological characteristics in logistic regression models to create accurate PCa predictive models. A model including information of miR148b-3p and patient age showed relevant prediction results (area under the curve [AUC] = 0.818, precision = 0.763, specificity = 0.762, and accuracy = 0.762). A model including all four miRNAs and patient age presented outstanding prediction results (AUC = 0.918, precision = 0.861, specificity = 0.861, and accuracy = 0.857). Our results represent a potential novel procedure based on logistic regression models that utilize miRNA expressions and patient age to assist with PCa diagnosis.