Prostate cancer (PCa) is one of the leading causes of death among men. Genes such as PCA3, PSA, and Fra-1 are suggested to serve as potential tools for the detection of PCa, as they are deregulated during this pathology. A similar event occurs with small non-coding RNAs, called miRNAs, specifically miR-195-5p, miR-133a-3p, and miR-148b-3p, which were analyzed in a Chinese population and suggested to be possible candidates for PCa diagnosis. We evaluated the expression levels of three miRNAs and three genes in tissue samples of PCa and benign prostate disease, such as benign prostatic hyperplasia, or prostatitis, in order to determine their potential as candidates for PCa detection. Our results showed a statistically significant overexpression of 279-fold increase in PSA levels and a 1,012-fold increase in PCA3 levels in PCa patients compared to benign prostate disease patients (p = 0.001 and p = 0.002, respectively). We observed a positive correlation between the expression of miR-148b-3p and the expression of PSA and PCA3 genes, two established biomarkers in PCa. The expression of miR-148b-3p was not related to clinical characteristics, such as age and weight, as observed for the other miRNAs analyzed, suggesting its potential as a biomarker for detection of this pathology.

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.

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