Seminal plasma (SP) contains a unique concentration of miRNA, mostly contained in small extracellular vesicles (sEVs) such as exosomes, some of which could be clinically useful for diagnosis and/or prognosis of urogenital diseases such as prostate cancer (PCa). We optimized several exosome-EV isolation technologies for their use in semen, evaluating EV purifying effectiveness and impact on the downstream analysis of miRNAs against results from the standard ultracentrifugation (UC) method to implement the use of SP sEV_miRNAs as noninvasive biomarkers for PCa. Our results evidenced that commercial kits designed to isolate exosomes/EVs from blood or urine are mostly applicable to SP, but showed quantitative and qualitative variability between them. ExoGAG 3500× g and the miRCURY Cell/Urine/CSF 1500× g methods resulted as equivalent alternative procedures to UC for isolating exosomes/sEVs from semen for nanoparticle characteristics and quality of RNA contained in vesicles. Additionally, the expression profile of the altered semen sEV-miRNAs in PCa varies depending on the EV isolation method applied. This is possibly due to different extraction techniques yielding different proportions of sEV subtypes. This is evidence that the exosome-EV isolation method has a significant impact on the analysis of the miRNAs contained within, with important consequences for their use as clinical biomarkers. Therefore, miRNA analysis results for EVs cannot be directly extrapolated between different EV isolation methods until clear markers for delineation between microvesicles and exosomes are established. However, EV extraction methodology affects combined models (semen exosome miRNA signatures plus blood Prostate specific antigen (PSA) concentration for PCa diagnosis) less; specifically our previously described (miR-142-3p + miR-142-5p + miR-223-3p + PSA) model functions as molecular marker from EVs from any of the three isolation methods, potentially improving the efficiency of PSA PCa diagnosis.

The purpose of this study is to describe Health-Related Quality of Life (HRQoL) of localized prostate cancer patients in an Active Surveillance (AS) program, and to compare them with those undergoing radical prostatectomy (RP), external-beam radiotherapy (XRT) and brachytherapy (BT). Multi-institutional pooled cross-sectional analysis on patients in an AS protocol: < 75 years old; pathologically confirmed LPC (maximum of three positive cylinders); Gleason score < 3 + 4; clinical stage T1a-T2b; and PSA < 15 ng/ml. Exclusion criteria for this study were: less than 6 months in AS, termination of AS protocol, or incomplete data. Patients in AS were matched with those treated with RP, XRT or BT from the ‘Spanish Multicentric Study of Clinically Localized Prostate Cancer’ cohort according to risk group, time from treatment selection to HRQoL survey, and age. Prostate-specific (EPIC) and generic (SF-36) HRQoL instruments were completed. Analysis was stratified by HRQoL survey moment (>or < 2.5 years from treatment selection), and age (>or < 70 years old). Median of time from treatment selection to HRQoL survey in the total 396 patients (99 per treatment group) was 2.4 years (range 0.5–8.3). Patients in AS presented higher (better) urinary incontinence scores than RP ones in both stratus of time from treatment selection to HRQoL survey (92.6 vs 67.0 and 81.4 vs 64.4, p < 0.01). Patients in AS for < 2.5 years presented greater sexual scores than any active treatment (p < 0.01), but only statistically higher than RP for those in AS for longer than 2.5 years. The magnitude of the differences between AS and RP groups in both EPIC domains ranged from moderate (0.7 SD) to large (1.0 SD). Regardless of treatment applied, patients presented similar and slightly increased SF-36 scores than US general population reference norms. Nonetheless, patients in AS for < 2.5 years reported worse outcomes than other treatment groups on physical health domains, especially in bodily pain (0.5–0.6 SD), and vitality (0.6–0.8 SD). Considering patients’ well-being, AS can be a good therapeutic option due to the low impact caused on urinary continence and sexual function. However, longitudinal studies are required to take into account HRQoL evolution over time.

Besides serum levels of PSA, there is a lack of prostate cancer specific biomarkers. It is need to develop new biological markers associated with the tumor behavior which would be valuable to better individualize treatment. The aim of this study was to elucidate the relationship between single nucleotide polymorphisms (SNPs) in genes involved in DNA repair and prostate cancer progression. A total of 494 prostate cancer patients from a Spanish multicenter study were genotyped for 10 SNPs in XRCC1, ERCC2, ERCC1, LIG4, ATM and TP53 genes. The SNP genotyping was made in a Biotrove OpenArray® NT Cycler. Clinical tumor stage, diagnostic PSA serum levels, and Gleason score at diagnosis were obtained for all participants. Genotypic and allelic frequencies were determined using the web-based environment SNPator. SNPs rs11615 (ERCC1) and rs17503908 (ATM) appeared as risk factors for prostate cancer aggressiveness. Patients wild homozygous for these SNPs (AA and TT, respectively) were at higher risk for developing cT2b – cT4 (OR = 2.21 (confidence interval (CI) 95% 1.47 – 3.31), p < 0.001) and Gleason scores ≥ 7 (OR = 2.22 (CI 95% 1.38 – 3.57), p < 0.001), respectively. Moreover, those patients wild homozygous for both SNPs had the greatest risk of presenting D’Amico high-risk tumors (OR = 2.57 (CI 95% 1.28 – 5.16)). Genetic variants at DNA repair genes are associated with prostate cancer progression, and would be taken into account when assessing the malignancy of prostate cancer.

PSA screening has led to an over-diagnosis of prostate cancer (PCa) and unnecessary biopsies of benign conditions due to its low cancer specificity. Consequently, more accurate, preferentially non-invasive, tests are needed. We aim to evaluate the potential of semen sEV (small extracellular vesicles) tsRNAs (tRNA-derived small RNAs) as PCa indicators. Initially, following a literature review in the OncotRF database and high-throughput small RNA-sequencing studies in PCa tissue together with the sncRNA profile in semen sEVs, we selected four candidate 5′tRF tsRNAs for validation as PCa biomarkers. RT-qPCR analysis in semen sEVs from men with moderately elevated serum PSA levels successfully shows that the differential expression of the four tRFs between PCa and healthy control groups can be detected in a non-invasive manner. The combined model incorporating PSA and specific tRFs (5′-tRNA-Glu-TTC-9-1_L30 and 5′-tRNA-Val-CAC-3-1_L30) achieved high predictive accuracy in identifying samples with a Gleason score ≥ 7 and staging disease beyond IIA, supporting that the 5′tRF fingerprint in semen sEV can improve the PSA predictive value to discriminate between malignant and indolent prostate conditions. The in silico study allowed us to map target genes for the four 5′tRFs possibly involved in PCa. Our findings highlight the synergistic use of multiple biomarkers as an efficient approach to improve PCa screening and prognosis.

Purpose: To assess the validity, reliability, and responsiveness of the Spanish version of the Expanded Prostate cancer Index Composite (EPIC) with 26 items. Methods: Multicentric longitudinal study of patients diagnosed with localized or locally advanced prostate cancer (any T, any N, M0) treated with active surveillance, surgery, external radiotherapy, or brachytherapy. The EPIC-50 was administered initially to the cohort (n = 324 patients), until it was replaced in November 2019 by the EPIC-26 (n = 543), in both groups before treatment and 12 months after. We assessed confirmatory factor analysis (CFA), reliability with Cronbach’s alpha coefficient, criterion validity with the intraclass correlation coefficient (ICC), and responsiveness by testing a priori hypotheses on deterioration effect size (ES). Results: The CFA confirmed the five-domain structure of the EPIC-26 proposed by the original instrument (comparative fit index = 0.95). The agreement between EPIC-50 (gold standard) and EPIC-26 domains was excellent (ICC > 0.90). Cronbach’s alpha was > 0.7 in almost all domains, and the floor effect was near zero, although ceiling effect was higher than 50% in urinary incontinence and bowel domains. Hypothesized changes between before and 12 months after treatment were confirmed: ES > 0.8 in both urinary incontinence and sexual domains among patients who underwent surgery; and ES ranging 0.44–0.48 for bowel and sexual domains in patients treated with external radiotherapy. Conclusion: The Spanish version of the EPIC-26 has demonstrated adequate metric properties, similar to those of the original version, with acceptable goodness-of-fit indices, good criterion validity, reliability, and responsiveness to detect changes after radical prostatectomy or external radiotherapy.

The need for prostate cancer (PCa)-specific biomarkers that enable more accurate detection of the disease and better prediction of tumor aggressiveness remains ongoing due to the low cancer specificity of PSA screening. Several potential mRNA markers for diagnosing PCa, in tissue and urine, have been reported in the literature. In this study, we aim to explore the potential of selected prostate-specific molecules and transcripts contained in small extracellular vesicles (sEVs) in semen to predict PCa risk reclassification for patients with moderately elevated PSA levels—a clinical scenario where identifying truly non-invasive biomarkers is especially critical. RT-qPCR analysis in semen sEVs successfully showed differential expression of KLK3 and PCA3 genes between PCa and healthy controls, whereas CREB3L4, CCNQ and DUSP23 levels were related to the severity or degree of PCa affectation. Our findings also present strong evidence that classifiers based on combined long transcript levels in semen sEVs serve as effective biomarkers. They can be used alone or in combination with blood PSA and/or semen citric acid levels to improve the diagnosis of PCa and assess its severity and disease progression with high accuracy. This strategy would allow a more comprehensive assessment, increase prognostic accuracy, and facilitate accurate clinical decision-making in the management of PCa.