Abstract A35: Drug repurposing for castration resistant prostate cancer based on disease-disease relationships
Authors: Majumder Joydeb , Lantz Travis , Fine Jonathan , Chopra Gaurav 
Published: May 2017

Prostate cancer (PCa) ranks second in terms of cancer-related deaths among men in the United States. The primary cause is the emergence of castration resistant prostate cancer (CRPC) and subsequent metastasis and chemoresistance. There is no known cure for CRPC with a median survival rate of about 18 months. CRPC tumors are either intrinsically resistant or rapidly develop resistance to chemotherapy. Traditional approaches to drug discovery are highly specific to single targets (molecules and indications) and are time-consuming trial-and-error approaches, which are often ineffective and unsafe for humans. This approach has resulted in a dearth of novel drugs (currently less than thirty are approved each year) and the time and costs to develop and bring one to market are prohibitive ($2.6 billion in 2013). A solution is to repurpose existing drugs with known safety profiles that interact with therapeutic targets and can be rapidly deployed for use in mono and multi-drug therapies. However, there is a problem in consistently identifying high-confidence drugs for CRPC. Many computational tools have been developed for analyses of high-throughput genomics data, and these methods have led to improved understanding of cancer biology. However, despite the generation of enormous amounts of data, improved treatments and diagnostics take a long time, and a substantial amount of research is needed to translate a genomic discovery to the bedside. We have developed an integrated drug discovery/repurposing platform that analyzes compound-protein structural interaction signatures across multiple proteomes to determine drug behavior, in contrast to traditional single (or few) target approaches. The platform implements a modeling pipeline that generates an interaction between ‘all’ (currently 3,733) human approved drugs and ‘all’ (currently 48,278) proteins using our interactome docking with dynamics program to compute ~ 1 billion proteome-compound interactions. We have prospectively validated our predictions with in vitro and in vivo preclinical studies for more than 10 different diseases including immunological, metabolic, infectious and genetic indications. Recently, we applied our integrated drug discovery pipeline and found strong relationship between CRPC with breast cancer, hypertension and inflammation to repurpose human approved drugs for CRPC. We have newly identified an FDA approved drug with IC50 less than 10nM activity on LnCaP and C4-2 cell proliferation. The repurposed lead is tissue specific and its toxicity is very less compared to other chemotherapeutic agents used for cancer. Using our computational design approach of taking into account target and anti-target binding profile we are modifying and synthesizing new analogues of this potent anti-cancer human approved drug for immunomodulation without effecting anti-cancer potency. We conclude that compared to traditional single target drug discovery that is slow and error prone, interactome based drug discovery that takes into account cancer as a heterogeneous combination of other diseases will help bring anticancer drugs faster to the clinic.

Citation Format: Joydeb Majumder, Travis Lantz, Jonathan Fine, Gaurav Chopra. Drug repurposing for castration resistant prostate cancer based on disease-disease relationships. [abstract]. In: Proceedings of the AACR Special Conference on Translational Control of Cancer: A New Frontier in Cancer Biology and Therapy; 2016 Oct 27-30; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2017;77(6 Suppl):Abstract nr A35.