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Metastatic castration resistant prostate cancer (mCRPC) is the most advanced and lethal stage of prostate cancer. A subset of advanced CRPC patients eventually develop an aggressive variant of prostate cancer (AVPCa), a rapidly progressive disease state with lack of AR expression (AR-ve mCRPC) and limited or no therapeutic options. To address this outstanding issue, we have previously reported using a novel computational algorithm (‘secDrug') and in vitro chemosensitivity and phenotypic assays to identify TAK715-a p38MAPK inhibitor as a synergistic partner for Taxanes/TX in treating AVPCa. Notably, in CRPC, MAPK pathway is involved in sustaining AR-independent cell proliferation. In this study, we investigated the genes, networks and molecular pathways underlining TX+TAK715 drug synergy in AVPCa. Gene expression profiling (mRNA sequencing) followed by Ingenuity pathway analysis (IPA) revealed upregulation of mitochondrial dysfunction and oxidative phosphorylation (OXPHOS) as the top dysregulated pathways following single-agent and combination treatment, which were confirmed by immunoblotting. In vitro ROS generation assay and Mitochondrial membrane potential measurement following combination treatment confirmed elevated intra-cellular ROS level (≈7 folds; indicating oxidative stress) and membrane depolarization (indicating mitochondrial dysfunction), respectively, in mCRPC lines. Furthermore, our IPA causal network analysis predicted significant upregulation of microRNA-132 and downregulation of miR-21 in response to combination treatment. Using in silico analysis on multiple GEO PCa datasets, we found low expression level of miR-132 was associated with poor clinical prognosis, transition from androgen dependent (AD) to independent (AI) stage and metastasis. miRNA 21 was significantly up regulated in the GEO PCa datasets. miRNA 21 is an AR-regulated miRNA that plays key role in nullifying the effect of castration, drive progression to AI stage, TX resistance and cellular invasiveness through down-regulation of tumor suppressor PTEN. Finally, using single-cell transcriptomic analysis we showed that cell subpopulations expressing the PCa stemness marker CD44, or drug resistant markers (CXCL8, CDK1), or epithelial-to-mesenchymal transition markers (Vimentin, TGFB1) were also very high expressors of TAK715 target genes (CSNK1D, MAPK14, MAP4K4) indicating TAK715 is potentially effective against treatment-refractory and stem-cell like subclones.Together, we conclude that TAK715+Taxane combination may be useful in curbing oncogenic progressions in AVPCa through simultaneous inhibition of multiple oncogenic factors/pathways. Currently, we are performing functional analysis of microRNA signatures of drug synergy as well as in vivo validation of the drug combinations using mouse xenograft models. Citation Format: Sayak Chakravarti, Suman Mazumder, Farnaz Hemmati, Farshad Amiri, Taraswi Mitra Ghosh, Ujjal Kumar Mukherjee, Panagiotis Mistriotis, Timothy Moore, Robert Arnold, Clayton Yates, Amit Kumar Mitra. Deciphering the functional basis of synergy between taxanes and TAK715: A novel repurposed drug candidate in treatment-refractory aggressive prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1354.

Drug resistance is a major cause of concern in cancer chemotherapy that not only reduces efficacy but also causes toxicity through overdosing. For example, Ixazomib, an oral proteasome inhibitor, has proven to remarkably improve myeloma patient outcomes but is associated with dose limiting toxicities and drug resistance. Therefore, new combination treatment regimens are urgently needed for the treatment of cancers, including multiple myeloma, which can lower the required dose of standard-of-care drug without compromising on treatment efficacy. We will present an optimization-regularization based computational prediction method called secDrug that uses large-scale pharmacogenomics databases to identify novel secondary drug combinations to reverse drug resistance. In this study, we applied secDrug to Ixazomib-resistant cell lines (>100) in the Genomics of Drug Sensitivity in Cancer (GDSC) database and predicted that the following FDA-approved drug classes can be best combined with Ixazomib to overcome resistance in MM: nicotinamide phospho ribosyl transferase or Nampt inhibitor (FK866), HDAC inhibitors (Panobinostat, SAHA), neddylation inhibitor (MLN4924), Raf inhibitor (PLX-4720) and HSP90 inhibitor (17-AAG). Our results corroborate with earlier studies that have indicated these drugs could potentially be used in MM, alone or in combination. To validate our prediction results, we treated our panel of >50 human multiple myeloma cell lines (Ix-sensitive and Ix-resistant HMCLs) with the top predicted drug combination - FK866 + Ixazomib. The results, based on combination index theorem, show that this combination works highly synergistically where the IC50 of ixazomib in MM cells was significantly reduced in presence of FK866. Similar results were obtained for the other top predicted combination regimens. Our findings provide a strong case for using secDrug for predicting secondary drugs in cancers resistant to the standard-of-care therapy. Furthermore, this provides additional evidence in support of combining FK866 with ixazomib to enhance sensitivity or overcome resistance to ixazomib and thereby improve patient outcome. Our future aim is to investigate the mechanism behind the synergism between proteasome inhibitors and the top drugs identified by our algorithm as candidates for secondary combination therapies using next-gen transcriptomics and single-cell approaches. Citation Format: Harish Kumar, Ujjal Kumar Mukherjee, Sayak Chakravarti, Li Chen, Brian Van ness, Amit Kumar Mitra. A novel computational combination-therapy prediction algorithm (secDrug) identifies the Nampt inhibitor FK866 reverses PI-resistant multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-266.