Abstract
Abstract Advances in cancer research have led to the rapid development of novel therapies designed to target specific molecular pathways altered in tumors. However, reliable high-throughput approaches for matching novel drugs to specific tumor types are needed. The potential of systematically identifying and repurposing currently existing targeted therapies designed for a specific cancer to treat other malignancies could hasten the availability of therapeutic options for patients. To address this problem, we have developed an integrative computational therapy-predicting algorithm. This algorithm incorporates data from The Cancer Genome Atlas (TCGA) as well as molecular and survival correlations to identify early-stage antitumor drugs that can be repurposed for other malignancies by targeting novel molecular pathways. To biologically validate our bioinformatics tool, we chose ovarian cancer as a model, which is currently the most lethal gynecologic malignancy afflicting women in the U.S. Our analysis predicted that bromodomain inhibitors, which inhibit bromodomain-containing proteins such as BRD4 and have proved effective in various types of leukemias, would provide a survival benefit for ovarian cancer patients. Furthermore, our analysis revealed that BRD4 inhibition could target the Notch3 pathway, which is known to play an important role in ovarian cancer pathogenesis and is associated with worse patient survival and chemoresistance. We hypothesize that inhibition of BRD4 is an effective therapeutic target in ovarian cancer by downregulating the Notch3 pathway. Inhibition of BRD4 by either using the small-molecule CPI203 or siRNA transfection resulted in a decrease in both Notch3 transcription and protein levels in a panel of Notch3 overexpressing ovarian cancer cell lines. Given that BRD4 regulates gene transcription, we performed chromatin immunoprecipitation (ChIP) and observed that BRD4 was present in the Notch3 gene promoter, but not in the promoter of other Notch genes, such as NOTCH2. To determine the therapeutic efficacy of BRD4 inhibition, we conducted in vitro and in vivo experiments using both CPI203 and siRNA approaches. BRD4 inhibition decreased cell viability, as demonstrated by both 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and 2-D colony formation assays in ovarian cancer cell lines. The biologic mechanism of this is mainly by inhibiting cell proliferation, as determined by EdU incorporation assays. Utilizing the OVCAR5 orthotopic tumor model, we determined that treatment with CPI203 significantly decreased tumor weight in mice (p = 0.0468). Additionally, sustained downregulation of BRD4 in OVCAR 5 tumors using a shRNA doxycycline inducible system significantly increases survival by 57% (p = 0.0008). Our current findings suggest that by inhibiting BRD4 in ovarian cancer, we can directly target Notch3 simultaneously and provide both a positive therapeutic and survival effect in ovarian cancer. Completion of this work will provide biologic validation of our Therapy Forecasting Tool by delineating a systematic and accurate approach in identifying and repurposing currently existing targeted therapies. This allows for the expansion of our approach for other tumor types by targeting novel downstream signaling pathways with the ultimate goal of improving patient survival. Citation Format: Alejandro Villar-Prados, Sherry Y. Wu, Jason Roszik, Margaret I. Engelhardt, Anil K. Sood. Systematic approach for identifying and validating novel therapies and targets for ovarian cancer. [abstract]. In: Proceedings of the AACR Conference: Addressing Critical Questions in Ovarian Cancer Research and Treatment; Oct 1-4, 2017; Pittsburgh, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(15_Suppl):Abstract nr B60.
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