Predict radiation-induced shifts in patient-specific tumor immune ecosystem composition to harness immunological consequences of radiotherapy

预测辐射引起的患者特异性肿瘤免疫生态系统组成的变化，以利用放射治疗的免疫学后果

• 批准号: 10589786
• 负责人: Heiko Enderling
• 金额: $ 10.61万
• 依托单位: H. LEE MOFFITT CANCER CTR & RES INST
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10589786
• 关键词: Address; Adoptive Transfer; Biological; Biological Markers; Biopsy Specimen; CD8-Positive T-Lymphocytes; Calibration; Cancer Patient; Cell Survival; Cells; Clinical; Clinical Data; Clinical Trials; Clinical assessments; Complex; Data; Decision Making; Dose; Dose Fractionation; Ecosystem; Environment; Environmental Risk Factor; Evolution; Experimental Models; Fractionated radiotherapy; Fractionation; Funding; Goals; Growth; HPV oropharyngeal cancer; Heat shock proteins; High Prevalence; Human Papillomavirus; Immune; Immune response; Immune system; Immunity; Immunologic Adjuvants; Immunologic Markers; Immunologic Stimulation; Immunologics; Immunosuppression; Immunotherapy; In complete remission; Incidence; Individual; Link; Literature; Malignant Neoplasms; Modeling; Molecular; Molecular Profiling; Normal tissue morphology; Oncology; Outcome; Patient Simulation; Patients; Pattern; Prediction of Response to Therapy; Property; Protocols documentation; Radiation; Radiation Dose Unit; Radiation Oncology; Radiation Tolerance; Radiation therapy; Retrospective cohort; Sample Size; Sampling; Schedule; T-Lymphocyte; Testing; Therapeutic Agents; Tissue Sample; Training; Treatment Efficacy; Treatment-related toxicity; Tumor Antigens; Tumor Debulking; Tumor Immunity; Tumor-Infiltrating Lymphocytes; anti-tumor immune response; cancer cell; cancer survival; cancer therapy; cancer type; clinical practice; cohort; cytotoxic; dynamic system; experimental study; first-in-human; immune activation; immune cell infiltrate; immune clearance; immunoregulation; improved; improved outcome; in silico; in vivo; indexing; individual patient; innovation; interest; malignant oropharynx neoplasm; mathematical model; mouse model; outcome prediction; personalized medicine; predictive modeling; programs; prospective; radiation effect; response; spatiotemporal; standard of care; success; synergism; therapy outcome; treatment response; tumor; tumor growth; virus related cancer

SUMMARY Tumor-associated antigens, stress proteins, and danger-associated molecular patterns are endogenous immune adjuvants that can both initiate and continually stimulate an immune response against a tumor. In retaliation, tumors can hijack intrinsic immune regulatory programs, thereby facilitating continued growth despite an activated antitumor immune response. Clinically apparent tumors have co-evolved with the patient’s immune system and form a complex Tumor-Immune EcoSystem (TIES). The success of radiotherapy (RT) may be the result of radiation shifting the relative proportions of tumor and immune cells such that surviving cancer cells are subject to elimination by the immune system. However, current RT fractionation has not specifically focused on enhancing immune responses, nor has immune cell infiltration into the tumor as biomarker been considered to predict treatment response. We hypothesize that patients with a TIES such that radiation debulks the tumor and induces a robust immune response may be cured. A TIES with weak antitumor-immunity or strong immune suppression may not be sufficiently perturbed by current RT dose fractionation to fully harness radiation-immune synergy and provide tumor control. The goal of the project is to combine experimental studies and clinical data to calibrate and rigorously validate the in silico framework that simulates the influence of different TIES compositions on the response to different radiation doses and dose fractionations. We will focus on oropharyngeal cancer, one of the few cancer types increasing in incidence. In vivo tumors with and without tumor specific T cells provide radiation dose and fractionation-dependent changes in immune infiltration to derive in silico model parameters. For clinical analysis we will use a retrospective cohort of 51 oropharyngeal cancer (OPC) tissue samples as training cohort. We will prospectively collect radiosensitivity and immune infiltration data from 105 OPC patients that undergo radiation therapy with different total doses, dependent on their intrinsic radiosensitivity index (RSI). These data serve as a test cohort to validate model outcome predictions against clinical assessment of complete response at 3 months. Our overall aims are to determine radiation dose and fractionation that optimize radiation-induced immunity, and to identify how to use RT to shift a patient-specific TIES toward immune-modulated tumor elimination. These aims will motivate profound changes to how we conceive of and clinically prescribe RT. Radiation could be understood as immunotherapy. For patients with unfavorable TIES, RT fractionation protocols should focus on the radical perturbation of the TIES toward immune-modulated tumor control. For favorable TIES, dose could be de-escalated with focus on immune activation. Integrating our interdisciplinary expertise allows us to predict RT response and guide decision-making for individual patients, which holds the promise of leading to better outcomes. Successful project completion motivates an in silico model framework-aided clinical trial.

概括 肿瘤相关抗原，应激蛋白和与危险相关的分子模式是内源性的 可以启动并连续刺激针对肿瘤的免疫反应的免疫调节器。 报复，肿瘤可以劫持内在的免疫调节计划，从而支持持续增长 尽管激活了抗毒物免疫反应。临床上明显的肿瘤已与患者共同发展 免疫系统并形成复杂的肿瘤免疫生态系统（TIE）。放射疗法的成功（RT） 可能是辐射转移肿瘤和免疫细胞相对比例的结果 癌细胞会被免疫系统消除。但是，当前的RT分馏尚未 特别专注于增强免疫反应，免疫细胞渗入肿瘤中也没有 认为生物标志物可以预测治疗反应。我们假设有联系的患者 可以治愈辐射质量，并诱导鲁棒的免疫增强响应。纽带 抗肿瘤免疫或强烈的免疫抑制可能不会受到电流RT剂量的影响 分馏以完全利用辐射 - 免疫协同作用并提供肿瘤控制。该项目的目的是 结合实验研究和临床数据，以校准和严格验证在计算机框架中 模拟不同关系组成对不同辐射剂量和剂量的反应的影响 分馏。我们将重点关注口咽癌，这是发病率增加的少数癌症类型之一。在 带有和没有肿瘤特异性T细胞的体内肿瘤可提供辐射剂量和分级依赖性变化 在免疫浸润中以衍生为硅模型参数。对于临床分析，我们将使用回顾性 51个口咽癌（OPC）组织样品作为训练队列。我们可能会收集 来自105名OPC患者的放射性浸润数据和免疫浸润数据，这些患者接受放射治疗 不同的总剂量，取决于其内在的放射敏性指数（RSI）。这些数据用作测试队列 验证模型预测，以针对3个月的完全反应的临床评估。我们的 总体目的是确定辐射剂量和分馏，以优化辐射诱导的免疫力，以及对 确定如何使用RT将患者特异性的纽带转移到消除免疫调节的肿瘤上。这些 目标将激励人们对我们如何想象和临床处方的RT进行深刻的改变。辐射可能是 理解为免疫疗法。对于有不利领带的患者，RT分级方案应集中在 与免疫调节肿瘤控制的纽带的根本扰动。对于有利的关系，剂量可以 专注于免疫激活而被降低。整合我们的跨学科专业知识使我们能够预测 RT的反应和指导个别患者的决策，这有望导致更好 结果。成功的项目完成激发了一项在Silico模型框架辅助临床试验中。