Abstract 3736: Application of patient tumors-derived tumor ecosystem platform for the development of novel HDAC inhibitor in solid cancers
Authors: Mallikarjun Sundaram, Baraneedharan Ulaganathan, Muthu Dhandapani, Allen Thayakumar, Pragnashree Mukhopadhyay, Saravanan Thiyagarajan, Biswanath Majumder, Prasad Shivarudriah, H Jagadheshan, Ganesh Sambasivam, Steve Birnbuam, Padhma Radhakrishnan, Pradip K. Majumder
Journal: Cancer Research (2014)

Abstract Histone deacetylases (HDAC) are deregulated in many human cancers and a few HDAC inhibitors (HDACi) have been shown to be effective in patients with rare leukemia. However, clinical responses are not very promising for many HDACi in solid cancers. There is an urgent need to develop best in class HDACi with higher therapeutic index in solid cancers. At present less than 10% of anti-cancer drugs entering phase 1 clinical trials are successful in getting market approval. There are many factors for this poor clinical success for oncology therapeutics, and one of them is the lack of robust preclinical model driving clinical development. Cancer is a very heterogeneous disease and many of the present preclinical models do not represent this heterogeneity. As a result, while a candidate drug may appear good in present preclinical models, they often fail to make the cut in clinical development. To circumvent this critical problem, we have developed a robust TE (Tumor Ecosystem) platform technology using patient tumors, autologous ligands, and immune compartments from the same patients.Our TE platform preserves patient tumor heterogeneity along with other functional and genomic markers and immunogenic cytokines. Efficacy of drugs exposed to the patient's tumor tissue in our TE platform is assessed by as many as 17 orthogonal assays within a week. The results from these assays are converted into a single predictive score called the “M-Score,” and it has been clinically validated using FDA approved drugs in &amp;gt; 1,800 patients across multiple solid and hematological cancers. Our data shows that TE platform predicts treatment outcome of FDA approved drugs in clinical setting with very high sensitivity and specificity. We have the opportunity to use this platform technology to identify cancer indications and appropriate combinations for MIT-1102, a novel HDACi that exhibited potent histone deacetylase inhibitory activity. Our data further indicates that the anti-tumor efficacy of MIT-1102 is superior to Vorinostat and comparable with Pracinostat (SB-939) while being more tolerable than Pracinostat. Results indicated the superiority of MIT-1102 when combined with SOCs in a subset of patients with gastric and pancreatic cancers. We are also using different omics to identify markers associated with response in those tumor types. MIT-1102 has the potential to be more effective in a defined patient population than other molecules in this class. In summary, we have identified a novel, potent HDACi with drug-like properties, and identified the correct cancer indications and most effective combinations using TE platform Technology. Citation Format: Mallikarjun Sundaram, Baraneedharan Ulaganathan, Muthu Dhandapani, Allen Thayakumar, Pragnashree Mukhopadhyay, Saravanan Thiyagarajan, Biswanath Majumder, Prasad Shivarudriah, H Jagadheshan, Ganesh Sambasivam, Steve Birnbuam, Padhma Radhakrishnan, Pradip K. Majumder. Application of patient tumors-derived tumor ecosystem platform for the development of novel HDAC inhibitor in solid cancers. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3736. doi:10.1158/1538-7445.AM2014-3736