Transcription factor network analysis based on single cell RNA-seq identifies that Trichostatin-a reverses docetaxel resistance in prostate Cancer

Background Overcoming drug resistance is critical for increasing the survival rate of prostate cancer (PCa). Docetaxel is the first cytotoxic chemotherapeutical approved for treatment of PCa. However, 99% of PCa patients will develop resistance to docetaxel within 3 years. Understanding how resistance arises is important to increasing PCa survival. Methods In this study, we modeled docetaxel resistance using two PCa cell lines: DU145 and PC3. Using the Passing Attributes between Networks for Data Assimilation (PANDA) method to model transcription factor (TF) activity networks in both sensitive and resistant variants of the two cell lines. We identified edges and nodes shared by both PCa cell lines that composed a shared TF network that modeled changes which occur during acquisition of docetaxel resistance in PCa. We subjected the shared TF network to connectivity map analysis (CMAP) to identify potential drugs that could disrupt the resistant networks. We validated the candidate drug in combination with docetaxel to treat docetaxel-resistant PCa in both in vitro and in vivo models. Results In the final shared TF network, 10 TF nodes were identified as the main nodes for the development of docetaxel resistance. CMAP analysis of the shared TF network identified trichostatin A (TSA) as a candidate adjuvant to reverse docetaxel resistance. In cell lines, the addition of TSA to docetaxel enhanced cytotoxicity of docetaxel resistant PCa cells with an associated reduction of the IC50 of docetaxel on the resistant cells. In the PCa mouse model, combination of TSA and docetaxel reduced tumor growth and final weight greater than either drug alone or vehicle. Conclusions We identified a shared TF activity network that drives docetaxel resistance in PCa. We also demonstrated a novel combination therapy to overcome this resistance. This study highlights the usage of novel application of single cell RNA-sequencing and subsequent network analyses that can reveal novel insights which have the potential to improve clinical outcomes.

Impact of STAT Proteins in Tumor Progress and Therapy Resistance in Advanced and Metastasized Prostate Cancer

Signal transducers and activators of transcription (STATs) are a family of transcription factors involved in several biological processes such as immune response, cell survival, and cell growth. However, they have also been implicated in the development and progression of several cancers, including prostate cancer (PCa). Although the members of the STAT protein family are structurally similar, they convey different functions in PCa. STAT1, STAT3, and STAT5 are associated with therapy resistance. STAT1 and STAT3 are involved in docetaxel resistance, while STAT3 and STAT5 are involved in antiandrogen resistance. Expression of STAT3 and STAT5 is increased in PCa metastases, and together with STAT6, they play a crucial role in PCa metastasis. Further, expression of STAT3, STAT5, and STAT6 was elevated in advanced and high-grade PCa. STAT2 and STAT4 are currently less researched in PCa. Since STATs are widely involved in PCa, they serve as potential therapeutic targets. Several inhibitors interfering with STATs signaling have been tested unsuccessfully in PCa clinical trials. This review focuses on the respective roles of the STAT family members in PCa, especially in metastatic disease and provides an overview of STAT-inhibitors evaluated in clinical trials.