Abstract B17: Data-driven discovery of targets for immune-metabolic antitumor drugs identifies Estrogen Related Receptor Alpha

Abstract Drugs that kill tumors through multiple mechanisms have the potential for broad clinical benefits. Here, we first developed an in silico multi-omics approach (BipotentR) to find cancer-cell-specific regulators that simultaneously modulate tumor immunity and another oncogenic pathway, and use it to identify 38 candidate immune-metabolic regulators. We show the tumor activity of these regulators stratify melanoma patients by their response to anti-PD1 using machine learning and deep neural approaches, which we benchmarked against current biomarkers. The topmost identified regulator, ESRRA (Estrogen Related Receptor Alpha), is activated in immunotherapy-resistant tumors of many types. Its inhibition killed tumors by suppressing energy metabolism and activating two immune mechanisms: (i) cytokine induction, causing proinflammatory macrophage polarization (ii) antigen-presentation stimulation, recruiting CD8+ T cells into tumors. We also demonstrate a wide utility of BipotentR by applying it to angiogenesis and growth-suppressor pathways. BipotentR, available at http://bipotentr.dfci.harvard.edu/, provides a resource for evaluating patient response and discovering drug targets that act simultaneously through multiple mechanisms. Citation Format: Avinash Sahu. Data-driven discovery of targets for immune-metabolic antitumor drugs identifies Estrogen Related Receptor Alpha [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy; 2022 Oct 21-24; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2022;10(12 Suppl):Abstract nr B17.