Transcription Factor Network Reveals New Treatments for Prostate Cancer Docetaxel Drug Resistance

Overcoming drug resistance is critical increasing the survival rate for prostate cancer (PCa). In this study, we modeled­ docetaxel resistance using two PCa cell lines, DU145 and PC3. We conducted both single cell and bulk RNA sequencing. We constructed a transcription factor (TF) network for the docetaxel sensitive and resistant variants for all cell lines and sequencing methods resulting in 8 networks. We identified shared edges and nodes that represent a shared TF network for PCa that modeled the changes after acquiring drug resistance. Using this shared TF network, we identified drivers of the resistant phenotype. Interestingly, the network constructed from the bulk sequencing dataset revealed different TF drivers of resistance compared with the network constructed from the single cells. We validated the results constructed from the single cells to demonstrate the validity of the single cell sequenced TF network. We targeted GABPA (only identified in the single cell constructed network) and successfully re-sensitized both cell lines to docetaxel treatment. Additionally, we conducted connectivity map analysis to identify potential drugs that disrupt the resistant networks. We identified trichostatin A as a potential combination treatment using the single cell sequenced network. Combination treatment of trichostatin A and docetaxel, both in vitro and in vivo PCa models decreased tumor growth. These results suggest by analyzing a population of resistant cells, identification of drivers and novel treatments is possible. RNA sequencing of DU145 and PC3 sensitive and docetaxel resistant cell lines