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

项目2-摘要 辐射诱导的淋巴细胞减少症：理解、预测性建模和发展光子和 基于质子的缓解策略 在许多类型的癌症中，越来越多的证据表明，辐射诱导的淋巴细胞减少症(RIL)是 这很常见，但它往往被忽视，因为它是不可避免的副作用。严重的RIL已被证明与 因疾病而产生的不良后果。放射治疗在实体瘤治疗中的广泛应用 肿瘤需要发展RIL缓解策略。我们有令人信服的证据表明 质子疗法(PT)与光子(或X射线)疗法(XRT)的淋巴细胞节省效果的差异， 可能是由于它们的剂量分布模式不同所致。我们的工作有了进一步的进展 证明了患者特有的因素和剂量学因素都会导致严重的RIL和T细胞的风险 克隆性。我们的假设如下：(1)考虑单个患者的RIL预测模型 敏感性和剂量学因素将在临床上具有显著的预测能力；(2)将剂量减少到 处于危险中的循环免疫细胞和免疫结构不仅保留了数量，更重要的是， 淋巴细胞的质量，这对癌症免疫和疾病预后有直接的积极影响； 通过使用强度调制质子和光子RT(IMPT和IMRT)，采用个体化 根据模型得出的剂量学约束，我们将能够选择最佳的治疗方式 (质子或光子)，并制定针对患者的策略，以大幅减轻RIL及其后果。 为了检验这些假设，我们提出了三个具体目标。在目标1中，我们将利用我们的大型数据库 主要是食道癌、肝癌和脑癌患者，以提高我们对淋巴细胞耗竭作为一种 剂量学和特定于患者的基线临床因素的作用和开发模型以准确预测 个体化的严重RIL风险。在目标2中，我们将评估放射治疗方式的临床影响。 T细胞多样性、免疫谱系和功能免疫状态。我们将检验这一假设 RT后通过免疫表型、T细胞多样性和功能免疫检测淋巴细胞质量 是临床结果的主要驱动因素，而不仅仅是淋巴细胞的绝对计数。在目标3中，我们将评估 使用独立的回顾和前瞻性数据验证了我们模型的有效性。我们还将应用这些模型 为特定患者选择最佳治疗方式和技术，并定义个性化的 剂量学约束用于优化质子和光子辐射剂量分布模式，以最小化 RIL的严重程度和风险。在这个项目完成后，我们将更好地了解 基线临床特征和质子和光子剂量学因素影响RIL风险和严重程度，T细胞 多样性和功能免疫力。此外，我们还将开发先进的质子和光子剂量学。 降低RIL风险的策略。我们的研究有可能更好地为每个人选择最优的模式 患者，优化IMPT和IMRT治疗，以最大限度地缓解淋巴细胞减少症，以改善RT结果， 并在未来将RT与免疫治疗策略最佳地结合起来。

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.