Dynamic changes in proteome activity landscapes in treatment-resistant-prostate cancer

Abstract ID 126051 Poster Board 251 Integrative global proteomics and transcriptomics are emerging approaches to uncovering molecular mechanisms of drug action or resistance and designing more effective drugs and therapeutic strategies. Advanced prostate cancers continue to be the second leading cause of cancer-related deaths in men in the United States. While there have been advances in managing advanced diseases, patients unfortunately develop resistance to treatment and progress. Our understanding of the mechanisms of treatment resistance has primarily been based on genomic and transcriptomic studies with a limited focus on the proteomic landscape. This pilot study aimed to characterize changes in the proteome landscape in castrated-resistant prostate cancer (CRPC) models exposed to enzalutamide, an FDA-approved second-generation AR-targeted agent. Methods: We used a CRPC human cell line and CRPC patient-derived xenograft model treated with or without enzalutamide in vitro (cell line model) and in vivo (PDX model). At the end of treatment, cells and tissues were processed, followed by LC-MS/MS analysis to detect protein abundance. Integrative pathway analysis was performed using in-house pipelines. All terms and pathways have an FDR of Results: CRPC cell line and PDX models demonstrated poor response to enzalutamide. In comparing our cell line and PDX models, we observed a significant overlap in the differentially expressed proteins with exposure to treatment vs. their respective controls. Reactome and GO pathway analysis indicated a robust change in the proteome activity landscape in CRPC exposed to enzalutamide compared to control. Several pro-survival, metabolic, and chromatin remodeling pathways were enriched in cell lines and PDX models treated with enzalutamide. However, we observed changes in the Reactome that were unique in the PDX. Integrative studies highlight an overlap in the enrichment of pathways from gene expression data. Conclusion: Our pilot studies highlight unique changes in the proteomic landscape associated with treatment resistance that should be considered beyond transcriptomic changes in understanding molecular mechanisms of resistance.