RNA Biomarkers as a Response Measure for Survival in Patients with Metastatic Castration-Resistant Prostate Cancer

• Published in: Cancers Vol. 13; no. 24; p. 6279
• Main Authors: Boerrigter, Emmy, Benoist, Guillemette E, van Oort, Inge M, Verhaegh, Gerald W, de Haan, Anton F J, van Hooij, Onno, Groen, Levi, Smit, Frank, Oving, Irma M, de Mol, Pieter, Smilde, Tineke J, Somford, Diederik M, Hamberg, Paul, Dezentjé, Vincent O, Mehra, Niven, van Erp, Nielka P, Schalken, Jack A
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 14.12.2021; MDPI
• Subjects: abiraterone acetate; Acetic acid; Androgens; Antigens; Biomarkers; Cancer therapies; Castration; castration-resistant prostate cancer; Clinical medicine; Clinical trials; enzalutamide; Metastases; Metastasis; mRNA; Patients; Prediction models; Prostate cancer; RNA; Survival; RNA; biomarkers; survival; abiraterone acetate; castration-resistant prostate cancer; enzalutamide; liquid biopsy
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers13246279

Treatment evaluation in metastatic castration-resistant prostate cancer is challenging. There is an urgent need for biomarkers to discriminate short-term survivors from long-term survivors, shortly after treatment initiation. Thereto, the added value of early RNA biomarkers on predicting progression-free survival (PFS) and overall survival (OS) were explored. The RNA biomarkers: mRNA, miR-375, miR-3687, and were measured in 93 patients with mCRPC, before and 1 month after start of first-line abiraterone acetate or enzalutamide treatment, in two prospective clinical trials. The added value of the biomarkers to standard clinical parameters in predicting PFS and OS was tested by Harell's C-index. To test whether the biomarkers were independent markers of PFS and OS, multivariate Cox regression was used. The best prediction model for PFS and OS was formed by adding miR-375 and (at baseline and 1 month) to standard clinical parameters. Baseline miR-375 and detectable after 1 month of therapy were independently related to shorter PFS, which was not observed for OS. In conclusion, the addition of and miR-375 (at baseline and 1 month) to standard clinical parameters resulted in the best prediction model for survival assessment.