c8ab92624dba4f4826e1ad92ca3ce313 309010.pdf 731f290a6522bbbef87a3f2fbd09295d70c4f553 309010.pdf bdc123f95d962da4546d0223078170ffe2fac443386665964e081c8ba007a059 309010.pdf Title: Semen sEV tRF-Based Models Increase Non-Invasive Prediction Accuracy of Clinically Significant Prostate Cancer among Patients with Moderately Altered PSA Levels Subject: 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. Keywords: prostate cancer; tsRNAs; 5'tRFs; PSA; biomarkers; non-invasive diagnosis/prognosis; semen extracellular vesicles Author: Adriana Ferre-Giraldo, Manel Castells, José Francisco Sánchez-Herrero, Olga López-Rodrigo, Maurizio de Rocco-Ponce, Lluís Bassas, Francesc Vigués, Lauro Sumoy and Sara Larriba Creator: LaTeX with hyperref Producer: pdfTeX-1.40.25 CreationDate: Fri Sep 20 14:19:52 2024 CEST ModDate: Fri Sep 20 14:28:00 2024 CEST Custom Metadata: no Metadata Stream: no Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 24 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 5128484 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- JYPLJJ+VnURWPalladioL-Bold Type 1 Custom yes yes yes 10 0 NWFDSW+URWPalladioL-Bold Type 1 Custom yes yes yes 16 0 LIIVQX+URWPalladioL-Roma Type 1 Custom yes yes yes 22 0 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RepresentationInformation: 309010.pdf ReportingModule: PDF-hul, Rel. 1.12.4 (2023-03-16) LastModified: 2025-03-18 13:58:51 CET Size: 5128484 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 651 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: section.1 Item: Title: Results Destination: section.2 Children: Item: Title: Selection of Candidate tRFs Differentially Expressed in PCa Tissue to Study in Semen sEVs Destination: subsection.2.1 Item: Title: Clinical Assessment of the Individuals Included in the Study Destination: subsection.2.2 Item: Title: PCa-Associated tRFs Show Altered Levels in Semen sEVs from Men with Prostate Carcinogenesis Destination: subsection.2.3 Item: Title: 5'tRF Levels in Semen sEVs Are Associated with PCa Clinical Risk/Severity Destination: subsection.2.4 Item: Title: Prediction of the 5'tRF Target Genes Destination: subsection.2.5 Item: Title: Discussion Destination: section.3 Item: Title: Materials and Methods Destination: section.4 Children: Item: Title: Subjects of Study Destination: subsection.4.1 Item: Title: Cell Culture and Reagents Destination: subsection.4.2 Item: Title: Semen Samples and sEV Isolation Destination: subsection.4.3 Item: Title: Small RNA-Containing Total RNA Isolation Destination: subsection.4.4 Item: Title: tRF Quantification by miRPrimer2 RT-qPCR Strategy Destination: subsection.4.5 Item: Title: Determining In Silico Target Genes of tsRNAs Destination: subsection.4.6 Item: Title: Statistical Analysis Destination: subsection.4.7 Item: Title: Data Visualization Destination: subsection.4.8 Item: Title: References Destination: appendix.A. Info: Title: Semen sEV tRF-Based Models Increase Non-Invasive Prediction Accuracy of Clinically Significant Prostate Cancer among Patients with Moderately Altered PSA Levels Author: Adriana Ferre-Giraldo, Manel Castells, José Francisco Sánchez-Herrero, Olga López-Rodrigo, Maurizio de Rocco-Ponce, Lluís Bassas, Francesc Vigués, Lauro Sumoy and Sara Larriba Subject: 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. 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