Abstract
PurposeTo develop a microRNA (miRNA)-based predictive model for prostate cancer patients of 1) time to biochemical recurrence after radical prostatectomy and 2) biochemical recurrence after salvage radiation therapy following documented biochemical disease progression post-radical prostatectomy.MethodsForty three patients who had undergone salvage radiation therapy following biochemical failure after radical prostatectomy with greater than 4 years of follow-up data were identified. Formalin-fixed, paraffin-embedded tissue blocks were collected for all patients and total RNA was isolated from 1mm cores enriched for tumor (>70%). Eight hundred miRNAs were analyzed simultaneously using the nCounter human miRNA v2 assay (NanoString Technologies; Seattle, WA). Univariate and multivariate Cox proportion hazards regression models as well as receiver operating characteristics were used to identify statistically significant miRNAs that were predictive of biochemical recurrence.ResultsEighty eight miRNAs were identified to be significantly (p<0.05) associated with biochemical failure post-prostatectomy by multivariate analysis and clustered into two groups that correlated with early (≤ 36 months) versus late recurrence (>36 months). Nine miRNAs were identified to be significantly (p<0.05) associated by multivariate analysis with biochemical failure after salvage radiation therapy. A new predictive model for biochemical recurrence after salvage radiation therapy was developed; this model consisted of miR-4516 and miR-601 together with, Gleason score, and lymph node status. The area under the ROC curve (AUC) was improved to 0.83 compared to that of 0.66 for Gleason score and lymph node status alone.ConclusionmiRNA signatures can distinguish patients who fail soon after radical prostatectomy versus late failures, giving insight into which patients may need adjuvant therapy. Notably, two novel miRNAs (miR-4516 and miR-601) were identified that significantly improve prediction of biochemical failure post-salvage radiation therapy compared to clinico-histopathological factors, supporting the use of miRNAs within clinically used predictive models. Both findings warrant further validation studies.
Highlights
Prostate cancer (PCa) is one of the most common cancers worldwide and the most common cancer in men; treatment strategies remain highly controversial
A new predictive model for biochemical recurrence after salvage radiation therapy was developed; this model consisted of miR-4516 and miR-601 together with, Gleason score, and lymph node status
Two novel miRNAs were identified that significantly improve prediction of biochemical failure post-salvage radiation therapy compared to clinico-histopathological factors, supporting the use of miRNAs within clinically used predictive models
Summary
Prostate cancer (PCa) is one of the most common cancers worldwide and the most common cancer in men; treatment strategies remain highly controversial. Radical prostatectomy (RP) remains one of the more widely-used treatment options for men with early-stage PCa. Long-term data indicate that 30–40% of these patients experience biochemical failure after RP requiring salvage radiation therapy (RT); other studies have shown significantly different incidences due to different clinical prognostic characteristics of tumors [1,2,3]. The key clinical questions that are the focus of the current study are the identification of: 1) microRNAs (miRNAs) that predict biochemical recurrence after RP; 2) miRNAs that predict for biochemical recurrence after salvage radiation following failure after RP; and 3) miRNAs that can improve prediction of biochemical recurrence in combination with currently used clinicohistopathological factors, such as prostate-specific antigen (PSA), pathologic tumor (pT) and lymph node (pN) classification, resection status, and Gleason score. The goal of this study was to develop a miRNA signature that can add information to the existing clinical models and thereby help guide treatment decisions
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
