SBFI inhibitors reprogram transcriptomic landscape of prostate cancer leading to cell death [SBFI-103]
Prostate cancer (PCa) remains the second leading cause of cancer-related deaths in the United States. Fatty acid-binding protein 5 (FABP5), a member of a class of intracellular lipid transporters, promotes PCa progression via enhanced lipid metabolism and trafficking of lipid ligands. Previous work from our group has shown that the small molecule FABP5 inhibitors based on the truxillic-acid monoester (TAMEs) scaffold reduce PCa growth. In the current study, we demonstrate that the third-generation FABP5 inhibitor SBFI-1143 significantly inhibited the viability and proliferation of PCa cells by arresting cells at the G0/G1 and G2/M phases of the cell cycle and inducing apoptosis and cell death compared to 1st and 2nd generation inhibitors. Stinkingly, SBFI-1143 efficiently inhibited the growth of PCa spheroids compared to its predecessor, SBFI-103. RNA sequencing and Gene Set Enrichment Analysis (GSEA) demonstrated that SBFI-1143 more effectively suppressed the activity of pathways involved in cell cycle progression, cell cycle division, and chromosome organization, while upregulated genes associated with the endoplasmic reticulum (ER) stress, responses to the topologically incorrect folded proteins, and regulating apoptosis compared to the SBFI-103. We further show that SBFI-1143 inhibits oxidative phosphorylation, a process on which PCa depends during cancer initiation and progression. Notably, SBFI-1143 treatment downregulated genes attributed to the subpopulation of PCa cells characterized by the lineage plasticity-related signature leading to trans-differentiation, recurrence, and poor cancer prognosis. Our findings demonstrate that SBFI-1143 significantly modifies the transcriptomic landscape of PCa and may serve as a potentially effective therapeutic option for PCa. Overall design: To investigate the mechanism of action and efficacy of SBFI-103 in vitro, we treated the human prostate cancer cell line, PC-3, with vehicle control (DMSO) and 15uM of SBFI-103 for 24 hours. Total RNA was isolated and RNA-seq was conducted. We then performed differential gene expression analysis using RNA-seq data from three biological replicates of each treatment condition to characterize significant transcriptomic changes in response to treatments.