Mitigating High Grade Radiation-Induced Lymphopenia through Pretreatment Autologous Lymphocyte Infusion

通过预处理自体淋巴细胞输注减轻高级别辐射引起的淋巴细胞减少症

• 批准号: 10017926
• 负责人: Gheath Al-Atrash
• 金额: $ 17.62万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-13 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10017926
• 关键词: Applications Grants; Bayesian Prediction; Blood Component Removal; CD8B1 gene; Cancer Control; Characteristics; Clinical; Clinical Research; Collaborations; Combination immunotherapy; Complication; Data; Databases; Diagnosis; Disease; Distant; Effectiveness; Enrollment; Feasibility Studies; Future; Grant; Immunologic Surveillance; Immunotherapy; Incidence; Inferior; Infusion procedures; Link; Low Dose Radiation; Lymphocyte; Lymphocyte Count; Lymphopenia; Machine Learning; Malignant Neoplasms; Malignant neoplasm of esophagus; Methods; Modeling; Nomograms; Normal tissue morphology; Outcome; Patient-Focused Outcomes; Patients; Phase I Clinical Trials; Phase I/II Clinical Trial; Pilot Projects; Play; Probability; Prognosis; Proliferating; Radiation; Radiation Dose Unit; Radiation therapy; Recording of previous events; Recurrence; Risk; Risk Factors; Role; Safety; Solid Neoplasm; Statistical Models; Stem cell transplant; Time; Toxic effect; Training; Translating; Treatment outcome; Tumor Antigens; Tumor Escape; Tumor-Infiltrating Lymphocytes; Validation; Work; autologous lymphocytes; base; cancer radiation therapy; cancer therapy; chemoradiation; clinical translation; clinical trial enrollment; cohort; computerized tools; disorder control; esophageal cancer patient; fundamental research; high risk; high risk population; improved; innovation; personalized approach; pre-clinical; predictive modeling; prognostic value; radiation effect; response; risk stratification; safety and feasibility; safety study; side effect; tool; tumor

PROJECT SUMMARY Radiation induced lymphopenia (RIL) is a common radiation-related toxicity that has been recognized for over a century but often ignored as clinically inconsequential. However, accumulating evidence has demonstrated strong association of high grade RIL (seen in 30-50% of patients) with poor prognosis. The pervasive role of radiotherapy in the curative management of solid tumors supports the need to develop mitigating strategies, particularly for patients with a high risk of developing grade 4 (G4) RIL. We have compelling evidence from both clinical and preclinical work that severe RIL impacts cancer control and therapy effectiveness, and methods to reduce RIL may improve treatment outcomes. To further develop these approaches for clinical translation, we have proposed 2 specific aims. In aim 1, we will build on our initial prediction model for G4 RIL and leverage our large database of esophageal cancer patients who have completed chemoradiation (CRT) to develop a better predictive model for G4 RIL so that we can rapidly and efficiently identify the highest risk patients for mitigating strategies. In aim 2, we will determine the feasibility and safety of raising the baseline lymphocyte levels by autologous lymphocyte infusion (ALI) prior to initiating CRT. Fundamentally, this research will allow us to develop the necessary computational tool capable of properly identifying patients at risk for developing severe RIL, and complete a small feasibility and safety study of using ALI as a way to raise the baseline pre-treatment lymphocyte levels so that the probability of developing G4 RIL could be possibly curtailed. By targeting the at-risk patients to receive RIL mitigating strategies, we will hopefully be able to improve the cancer outcomes of standard cancer therapies, and build on current innovative strategies of immunotherapy and radiation combinations.

项目摘要 放射性淋巴细胞减少症（RIL）是一种常见的辐射相关毒性， 一个世纪，但经常被忽视的临床无关紧要。然而，越来越多的证据表明， 高级别RIL（见于30-50%的患者）与不良预后密切相关。在全球范围内 在实体瘤的治疗管理中的放射疗法支持了开发缓解策略的需要， 特别是对于具有发展4级（G4）RIL的高风险的患者。我们有确凿的证据 临床和临床前研究表明，严重的RIL会影响癌症控制和治疗效果， 减少RIL的方法可以改善治疗结果。为了进一步开发这些临床方法 翻译，我们提出了两个具体目标。在目标1中，我们将建立G4 RIL的初始预测模型 并利用我们已完成放化疗（CRT）的食管癌患者的大型数据库， 为G4 RIL开发更好的预测模型，以便我们能够快速有效地识别最高风险 患者的缓解策略。在目标2中，我们将确定提高基线的可行性和安全性 在开始CRT之前通过自体淋巴细胞输注（ALI）检测淋巴细胞水平。从根本上说，这 研究将使我们能够开发必要的计算工具，能够正确识别患者， 发展严重RIL的风险，并完成一项小型的可行性和安全性研究，使用ALI作为提高 基线治疗前淋巴细胞水平，因此发生G4 RIL的概率可能是 缩减了通过针对高危患者接受RIL缓解策略，我们希望能够 改善标准癌症治疗的癌症结果，并建立在目前的创新战略， 免疫疗法和放射组合。