Diagnostic and prognostic significance of extracellular vesicles in prostate cancer drug resistance: A systematic review of the literature

Abstract

Background: The clinical behavior of prostate cancer is highly heterogeneous, with most patients diagnosed with localized disease that successfully responds to surgery or radiotherapy. However, a fraction of men relapse after initial treatment because they develop drug resistance. The failure of anticancer drugs leaves resistant cancer cells to survive and proliferate, negatively affecting patient survival. Thus, drug resistance remains a significant obstacle to the effective treatment of prostate cancer patients. In this scenario, the involvement of extracellular vesicles (EVs) in intrinsic and acquired resistance have been reported in several tumors, and accumulating data suggests that their differential content can be used as diagnostic or prognostic factors. Thus, we propose a systematic study of literature to provide a snapshot of the current scenario regarding EVs as diagnostic and prognostic biomarkers resource in resistant prostate cancer.

Methods: We performed the current systematic review according to PRISMA guidelines and comprehensively explored PubMed, EMBASE and Google Scholar databases to achieve the article search.

Results: Thirty-three studies were included and investigated. Among all systematically reviewed EV biomarkers, we found mainly molecules with prognostic significance (61%), molecules with diagnostic relevance (18%), and molecules that serve both purposes (21%). Moreover, among all analyzed molecules isolated from EVs, proteins, mRNAs, and miRNAs emerged to be the most investigated and proposed as potential tools to diagnose or predict resistance/sensitivity to advanced PCa treatments.

Discussion: Our analysis provides a snapshot of the current scenario regarding EVs as potential clinical biomarkers in resistant PCa. Nevertheless, despite many efforts, the use of EV biomarkers in PCa is currently at an early stage: none of the selected EV biomarkers goes beyond preclinical studies, and their translatability is yet far from clinical settings.