PET-based radiomics visualizes tumor-infiltrating CD8 T cell exhaustion to optimize radiotherapy/immunotherapy combination in mouse models of lung cancer - Ying Zhang; Hui-Hui Hu; Shi-Hong Zhou; Wu-Yan Xia; Yan Zhang; Jian-Ping Zhang; Xiao-Long Fu; Wen Yu (BMC, 2023)
Abstract Background Cumulative preclinical and clinical evidences showed radiotherapy might augment systemic antitumoral responses to immunotherapy for metastatic non-small cell lung cancer, but the optimal timing of combination is still unclear. The overall infiltration and exhausted subpopulations of tumor-infiltrating CD8+ T cells might be a potential biomarker indicating the response to immune checkpoint inhibitors (ICI), the alteration of which is previously uncharacterized during peri-irradiation period, while dynamic monitoring is unavailable via repeated biopsies in clinical practice. Methods Basing on tumor-bearing mice model, we investigated the dynamics of overall infiltration and exhausted subpopulations of CD8+ T cells after ablative irradiation. With the understanding of distinct metabolic characteristics accompanied with T cell exhaustion, we developed a PET radiomics approach to identify and visualize T cell exhaustion status. Results CD8+ T cell infiltration increased from 3 to 14 days after ablative irradiation while terminally exhausted populations significantly predominated CD8+ T cells during late course of this infiltrating period, indicating that 3-7 days post-irradiation might be a potential appropriate window for delivering ICI treatment. A PET radiomics approach was established to differentiate T cell exhaustion status, which fitted well in both ICI and irradiation settings. We also visualized the underlying association of more heterogeneous texture on PET images with progressed T cell exhaustion. Conclusions We proposed a non-invasive imaging predictor which accurately assessed heterogeneous T cell exhaustion status relevant to ICI treatment and irradiation, and might serve as a promising solution to timely estimate immune-responsiveness of tumor microenvironment and the optimal timing of combined therapy.