Abstract

Intense androgen deprivation therapy (ADT) with androgen receptor pathway inhibitors (ARPIs) before radical prostatectomy (RP) produced favorable pathologic responses in approximately 20% of patients. The molecular reason for the low rate of response remains unclear. Lipid metabolism is known to influence androgen receptor signaling and ARPI efficacy. The aim of the study was to identify circulating lipid profiles associated with ADT/ARPI resistance in localized prostate cancer. Two independent experimental approaches were used. Experiment 1: Post hoc analysis of the association between plasma lipidomic profiles and ADT/ARPI response was performed on patients (n = 104) from two phase II trials of neoadjuvant ADT/ARPI. Response to ADT/ARPI was defined by pathologic response. Experiment 2: Patient-derived tumor explants from RP (n = 105) were cultured in enzalutamide for 48 hours. Explant response to enzalutamide was evaluated against pre-RP plasma lipidomic profiles (n = 105) and prostate tissue lipidomic profiles (n = 36). Response was defined by Ki67 (cell proliferation marker) fold difference between enzalutamide and vehicle-treated explants. In both experiments, associations between lipid profiles and ADT/ARPI response were analyzed by latent class analysis. Pretreatment plasma lipid profiles classified each experimental cohort into two groups with differences in ADT/ARPI response rates. The response rates of the groups were 9.6% versus 29% in experiment 1 (chi-squared test P = .012) and 49% versus 70% in experiment 2 (chi-squared test P = .037). In both experiments, the group with a higher incidence of ADT/ARPI resistance had higher plasma levels of sphingomyelin, glycosylceramides, free fatty acids, acylcarnitines, cholesterol esters, and alkyl/alkenyl-phosphatidylcholine and lower plasma levels of triacylglycerols, diacylglycerols, and phosphoethanolamine (t-test P < .05). Pretreatment circulating lipid profiles are associated with ADT/ARPI resistance in localized cancer in both human cohorts and explant models.

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