Prostate cancer (PCa) is the most common cancer and the third most frequent cause of male cancer death in Germany. MicroRNAs (miRNA) appear to be involved in the development and progression of PCa. A diagnostic differentiation from benign prostate hyperplasia (BPH) is often only possible through transrectal punch biopsy. This procedure is described as painful and carries risks. It was investigated whether urinary miRNAs can be used as biomarkers to differentiate the prostate diseases above. Therefore urine samples from urological patients with BPH (25) or PCa (28) were analysed using Next-Generation Sequencing to detect the expression profile of total and exosomal miRNA/piRNA. 79 miRNAs and 5 piwi-interacting RNAs (piRNAs) were significantly differentially expressed (adjusted p-value < 0.05 and log2-Fc > 1 or < -1). Of these, 6 miRNAs and 2 piRNAs could be statistically validated (AUC on test cohort > = 0.7). In addition, machine-learning algorithms were used to identify a panel of 22 additional miRNAs, whose interaction makes it possible to differentiate the groups as well. There are promising individual candidates for potential use as biomarkers in prostate cancer. The innovative approach of applying machine learning methods to this kind of data could lead to further small RNAs coming into scientific focus, which have so far been neglected.
Introduction: Prostate cancer (PCa) is the second most frequently diagnosed cancer and the fifth most cancer-related cause of death worldwide. Various tools are used in the diagnosis of PCa, such as the Prostate-Specific Antigen (PSA) value or digital rectal examination. A final differentiation from benign prostate diseases such as benign prostatic hyperplasia (BPH) can often only be made by a transrectal prostate biopsy. This procedure carries post-procedural complications for the patients and may lead to hospitalization. Urinary exosomes contain unique components, such as microRNAs (miRNAs) with information about their original tissue. As miRNAs appear to play a role in the development of PCa, they might be useful to develop procedures that could potentially make transrectal biopsies avoidable in certain situations. Methods: The current study aimed to investigate whether miRNAs from urinary exosomes can be used to differentiate PCa from BPH. For this purpose, urine samples from 28 patients with PCa and 25 patients with BPH were collected and analysed using next-generation sequencing to obtain expression profiles. Results and conclusion: The two miRNAs hsa-miR-532-3p and hsa-miR-6749-5p showed a significant differential expression within the group of patients with PCa in a training subset of the data containing 32 patients. They were further validated on the independent test data subset containing 20 patients. Additionally, a machine learning algorithm was used to generate a miRNA pattern to distinguish the two disease entities. Both approaches seem to be suitable for the search of alternative diagnostic tools for the differentiation of benign and malignant prostate diseases.
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