Novel Radiogenomic Biomarkers to Predict Response to Immunotherapy in a Non-Small Cell Lung Cancer.
In 2023, the United States recorded 238,340 lung cancer diagnoses, with non-small cell lung cancer (NSCLC) representing 85% of cases. Immunotherapies (IO) show promise for advanced-stage NSCLC. Despite positive responses in high PD-L1 expression NSCLC patients, the overall therapeutic efficacy is around 20%, with 80% developing immunotherapy resistance. Additionally, IO therapy is frequently associated with off-target autoimmune toxicities. Therefore, there is an unmet need to identify biomarkers facilitating prediction of IO response and toxicity. In this study, we will investigate following aims: 1) To optimize and validate a cutting-edge radiomics toolkit designed to predict clinical benefit and identify early response in NSCLC patients undergoing IO based on CT scan imaging, 2) To define radiomic signature predicting subgroup of NSCLC patients with potential high risk of immune-related toxicity. 3) To elucidate biological basis of radiomic response signatures with response-associated genomics, innate and adaptive cytokine kinetics and pathology. The final developed model will be accessible for clinical implication.