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


 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.