Introduction
Considerable prevalence of genomic aberrations (19-23%) in key DNA repair genes was detected in tumors of localized and advanced prostate cancer (PC) patients. Furthermore, patients with metastatic castration resistant prostate cancer (mCRPC) who had defects in DNA repair genes also had a high response rate to the PARP inhibitor Olaparib. It was previously shown in several types of cancers that the DNA damage-repair machinery is interfered by microRNAs which target multiple components in this pathway. We therefore suggest that like genomic aberrations, these microRNAs may be indicative of response to DNA-repair directed therapies. In this work we examine the use of DNA repair related microRNAs as biomarkers for disease progression and prediction of response to DNA-repair directed therapies in prostate cancer patients.
Methods
Patients with locally advanced, metastatic castration sensitive and castration resistant prostate cancer (n=26) were recruited to the study. Plasma samples were subjected to exosome isolation and RNA extraction. MicroRNA expression levels were determined by qRT-PCR and normalized to RNU1-4.
Results
A panel of 11 microRNAs that target DNA-repair genes such as BRCA1, BRCA2, ATM and RAD51 was analyzed in plasma exosomes from PC patients. The results of 7 microRNAs (miR-503-5p, miR-222-3p, miR-18a-5p, miR-107, miR-106a-5p, miR-221-3p, miR-146a-5p) defined a “high expression” signature for 6/26 (23%) of the patients and a “low expression” signature for 9/26 (34.6%). The high expression signature was more common within the castration resistant (mCRPC) worse outcome subgroup (4/11, 36%) than in the castration sensitive subgroup (2/11, 18%).
Discussion and Conclusion
These preliminary results proved the recognition of differential expression signatures of DNA repair related microRNAs in the plasma of PC patients. The abundance of the “high expression” signature within the worse outcome mCRPC subgroup may be indicative for clinical implications. Examination of additional 40 patients is underway to improve correlation analyses with clinical parameters and to evaluate the potential of predicting response to DNA-repair directed therapies.