Presence of cells in the polyaneuploid cancer cell (PACC) state predicts risk of recurrence in prostate cancer

Abstract

AbstractBackgroundThe non-proliferating polyaneuploid cancer cell (PACC) state is associated with therapeutic resistance in cancer. A subset of cancer cells enters the PACC state by polyploidization and acts as cancer stem cells by undergoing depolyploidization and repopulating the tumor cell population after the therapeutic stress is relieved. Our aim was to systematically assess the presence and importance of this entity in men who underwent radical prostatectomy with curative intent to treat their presumed localized PCa.Materials and MethodsMen with NCCN intermediate- or high-risk PCa who underwent radical prostatectomy l from 2007-2015 and who did not receive neoadjuvant treatment were included. From the cohort of 2159 patients, the analysis focused on a subcohort of 209 patients was selected, and 38 cases. Prostate tissue microarrays (TMAs) were prepared from formalin-fixed paraffin-embedded blocks of the radical prostatectomy specimens. A total of 2807 tissue samples of matched normal/benign and cancer were arrayed in 9 TMA blocks. The presence of PACCs and the number of PACCs on each core were noted.ResultsThe total number of PACCs and the total number of cores with PACCs were significantly correlated with increasing Gleason score (p=0.0004) and increasing CAPRA-S (p=0.004), but no other variables. In univariate proportional hazards models of metastasis-free survival, year of surgery, Gleason score (9-10 vs. 7-8), pathology stage, CAPRA-S, total PACCs, and cores positive for PACCs were all statistically significant. The multivariable models with PACCs that gave the best fit included CAPRA-S. Adding either total PACCs or cores positive for PACCs to CAPRA-S both significantly improved model fit compared to CAPRA-S alone.ConclusionOur findings show that the number of PACCs and the number of cores positive for PACCs are statistically significant prognostic factors for metastasis-free survival, after adjusting for CAPRA-S, in a case-cohort of intermediate- or high-risk men who underwent radical prostatectomy. In addition, despite the small number of men with complete data to evaluate time to mCRPC, the total number of PACCs was a statistically significant predictor of mCRPC in univariate analysis, and suggested a prognostic effect even after adjusting for CAPRA-S.