Predicting response to immunotherapy in non-small cell lung cancer- from bench to bedside - Montoya, Chris; Spieler, Benjamin; Welford, Scott M.; Kwon, Deukwoo; Pra, Alan Dal; Lopes, Gilberto; Mihaylov, Ivaylo B. (Frontiers in Oncology, 2023)
For most patients with advanced non-small cell lung cancer, immunotherapy improves disease response compared with conventional chemotherapy. However, resistance to immunotherapy remains common. Models able to predict response to immunotherapy would be helpful in guiding selection for intensified or alternative regimens, further personalizing patient care. FDA-approved biomarkers of immunotherapy response require tissue sampling and advanced laboratory techniques. Previously, our group generated a murine lung cancer model predictive of immunotherapy response, incorporating only non-invasive baseline variables including radiomic features. In the current retrospective analysis, pretreatment radiomics features were used to develop models predictive of immunotherapy response both in mice and in actual patients, suggesting the translatability of the findings. This study supports the use of radiomics as a tool to augment baseline clinical data in guiding precision cancer therapy for patients with advanced non-small cell lung cancer.