Project 2: Radiation-Induced Lymphopenia: Understanding, Predictive Modeling and Developing Photon and Proton-Based Mitigation Strategies.

Project 2 - Summary Radiation-Induced Lymphopenia: Understanding, Predictive Modeling and Developing Photon and Proton-Based Mitigation Strategies There is accumulating evidence across many types of cancers that radiation-induced lymphopenia (RIL) is common, but it is often ignored as an unavoidable side effect. Severe RIL has been shown to correlate with poor disease-specific outcomes. Extensive use of radiotherapy (RT) in the curative management of solid tumors necessitates the development of RIL-mitigation strategies. We have compelling evidence of significant differences in the lymphocyte-sparing effects of proton therapy (PT) vs. photon (or x-ray) therapy (XRT), presumably attributable to the differences in their dose distribution patterns. Our work has further demonstrated that both patient-specific and dosimetric factors contribute to the risk of severe RIL and T-cell clonality. Our hypotheses are as follows: (1) RIL predictive models that account for individual patient susceptibilities and dosimetric factors will have clinically significant predictive power; (2) reducing dose to circulating immune cells and immune structures at risk preserves not only the quantity but, more importantly, the quality of lymphocytes, which has a direct positive impact on cancer immunity and disease outcomes; (3) through the utilization of intensity-modulated proton and photon RT (IMPT and IMRT), employing individualized dosimetric constraints derived from the models, we will be able to select the optimum treatment modality (protons or photons) and develop patient-specific strategies to substantially mitigate RIL and its consequences. To test these hypotheses, we propose three specific aims. In Aim 1, we will utilize our large databases of mainly esophagus, liver and brain cancer patients to improve our understanding of lymphocyte depletion as a function of dosimetric and patient-specific baseline clinical factors and develop models to accurately predict individualized severe RIL risk. In Aim 2, we will evaluate the clinical impact of the radiation treatment modality on T-cell diversity, immune repertoire, and functional immune status. We will test the hypothesis that the quality of lymphocytes as measured by immune phenotyping, T-cell diversity, and functional immunity after RT is a major driver of clinical outcomes rather than just the absolute lymphocyte count. In Aim 3, we will assess the validity of our models using independent retrospective and prospective data. We will also apply the models to select the optimum treatment modality and technique for a given patient and define the personalized dosimetric constraints to be used to optimize proton and photon radiation dose distribution patterns to minimize RIL severity and risk. Upon the completion of this project, we will have a better understanding of how the baseline clinical characteristics and proton and photon dosimetric factors impact RIL risk and severity, T-cell diversity, and functional immunity. Moreover, we will have developed advanced proton and photon dosimetric strategies to reduce RIL risk. Our research has the potential to better select the optimum modality for each patient, to optimize IMPT and IMRT treatments to maximally mitigate lymphopenia to improve RT outcomes, and to optimally integrate RT with immunotherapy strategies in the future.