NextGen IO · Exploiting the hypoxia response in T cells for Next-Generation Immuno-Oncology

NextGen_IO has a core focus on immuno-oncology, specifically on target discovery and drug development, to exploit several opportunities that the hypoxia pathway in T cells offers for the treatment of cancer. It is well recognised that the clinical response of immunotherapies depends on the ability of T-cells to mount an effective effector response, persist in treated patients and avoid exhaustion and toxicities. Several approaches to immunotherapy have shown promise in clinical trials, especially the use of immune checkpoint inhibitors and, more recently, autologous adoptive T-cell therapies. However, current state-of-the-art immunotherapies are only effective in a small fraction of patients, offering a medical need to be addressed in several cancer types. Importantly, the tumor microenvironment has specific features that impact the immune response, including decreased oxygenation, aberrant vascularization and altered nutrient availability; all these influence the success of immunotherapies. During the last 10 years, my research has been focused on elucidating the role of the oxygen sensing machinery in T cell function, and the link of hypoxia-driven metabolism and epigenetic modifications with T cell differentiation into effector and memory T cells within the context of cancer immunotherapy. The current proposal aims to exploit these previous findings with a multi-disciplinary strategy, to deliver several early-stage drug discovery outputs.The main objectives are: 1. Development of a novel small molecule inhibitor to modulate the hypoxic response in T cells. 2. Therapeutic target discovery in T cells, focused on hypoxia-driven epigenetic modifications. 3. Development of hypoxia-inducible molecular switches for adoptive T cell therapy.Successful completion of the project will allow me to further innovate and consolidate my position as a leader in this field, harness this pathway for therapeutic potential and explore potential combinatorial approaches.