[18F]-AraG -PET imaging to evaluate immunological response to checkpoint inhibitor therapy (CKI) in patients with advanced solid tumors

[18F]-AraG -PET 成像评估晚期实体瘤患者对检查点抑制剂治疗 (CKI) 的免疫反应

• 批准号: 9913280
• 负责人: Shivaani Kummar
• 金额: $ 42.34万
• 依托单位: STANFORD UNIVERSITY
• 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 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9913280
• 关键词: Advanced Malignant Neoplasm; Adverse event; Aftercare; Antibodies; Area; Biological Markers; Biopsy; Blood; CD4 Positive T Lymphocytes; CD8B1 gene; Cell physiology; Cells; Clinical; Clinical Trials; Colitis; Complex; Confidence Intervals; Data; Data Reporting; Development; Diarrhea; Disease; Dose; Drug Design; Early treatment; Exposure to; Gastrointestinal tract structure; Head and Neck Cancer; Human; Image; Immune; Immune checkpoint inhibitor; Immune response; Immune system; Immunooncology; Immunotherapy; In complete remission; Inflammatory Arthritis; Institution; Label; Laboratories; Lesion; Logistic Regressions; Lung; Malignant Neoplasms; Measures; Metastatic Neoplasm to the Lung; Modeling; Multiplexed Ion Beam Imaging; Non-Small-Cell Lung Carcinoma; Normal tissue morphology; Patient Selection; Patient-Focused Outcomes; Patients; Pharmaceutical Preparations; Positron-Emission Tomography; Pre-Clinical Model; Prognostic Marker; Pulmonary Inflammation; ROC Curve; Sample Size; Sampling; Scanning; Side; Signal Transduction; Site; Solid Neoplasm; Spearman Rank Correlation Coefficient; Stable Disease; T-Cell Activation; T-Lymphocyte; Therapeutic; Time; Tissues; Toxic effect; Tumor-Derived; Tumor-infiltrating immune cells; Work; X-Ray Computed Tomography; analog; base; cancer therapy; cell mediated immune response; checkpoint therapy; experience; imaging biomarker; imaging probe; immune-related adverse events; melanoma; mouse model; non-invasive imaging; novel; partial response; patient safety; patient subsets; personalized management; pre-clinical; predictive marker; programmed cell death ligand 1; programmed cell death protein 1; recruit; response; response biomarker; safety outcomes; side effect; study population; time of flight mass spectrometry; treatment response; tumor; tumor heterogeneity; uptake

Contact PD/PI: Kummar, Shivaani PROJECT SUMMARY/ABSTRACT Immunotherapy, specifically checkpoint inhibitor (CKI) therapy, has resulted in dramatic and sustained tumor responses in patients with a variety of advanced cancers, such as melanoma, non-small cell lung cancer, head and neck cancer and others. However, only a subset of patients with advanced solid tumors derive clinical benefit, and of those a substantial portion progress over time. The ability to better select patients likely to respond to CKI therapy would optimize delivery; and reduce the number of patients exposed to agents not likely to work on their disease. There are multiple ongoing efforts focusing on blood or tissue based biomarkers; and number of immune cells, especially T cells, in the tumor lesions has correlated with tumor response to CKI treatment. However, it remains difficult and risky to biopsy solid tumor lesions repeatedly in a given patient. Since imaging can be safely performed at multiple time points, and multiple disease sites can be assessed simultaneously, it presents an attractive strategy for patient selection. [18F]F-AraG, a 18F-labeled analog of arabinofuranosylguanine (AraG), has been shown to be selectively taken up by T cells in laboratory models and in initial human studies. We hypothesize that [18F]F-AraG signal will increase in patients who develop T-cell immune responses in tumor following CKI therapy, and this will correlate with subsequent clinical benefit. In aim 1, we will correlate changes in [18F]F-AraG signal to number of T cells in tumor biopsies obtained pre and post-treatment with CKI. In our second aim, we will correlate the change in [18F]F-AraG signal following treatment to observed clinical benefit, defined as either tumor stabilization or shrinkage. In the third aim, correlate change in [18F]-AraG signal in lung and GI tract with the subsequent occurrence of higher grade immune related adverse events. Data generated from the proposed study will inform development of a novel imaging biomarker of response to immunotherapies, optimizing patient selection and outcome. In addition, our ability to predict which patients will go on to develop more severe toxicities will inform institution of therapies earlier to mitigate these side effects, as well as personalize management of adverse events.

联系PD/PI：Kummar，Shivaani 项目总结/摘要 免疫疗法，特别是检查点抑制剂（CKI）疗法，已经导致了显着的， 在患有多种晚期癌症，如黑素瘤， 非小细胞肺癌、头颈癌等。然而，只有一部分患者 晚期实体瘤患者获得临床益处，其中相当大一部分进展超过 时间更好地选择可能对CKI治疗有反应的患者的能力将优化交付; 并减少暴露于不太可能对他们的疾病起作用的药剂的患者数量。那里 是多个正在进行的努力，重点是基于血液或组织的生物标志物;和免疫 细胞，尤其是T细胞，与肿瘤对CKI治疗的反应相关。 然而，在给定患者中重复活检实体瘤病变仍然是困难和危险的。 由于成像可以在多个时间点安全地进行，并且多个疾病部位可以被检查。 同时评估，它提出了一个有吸引力的战略，病人的选择。[18F]F-AraG，a 18F标记的阿拉伯呋喃糖基鸟嘌呤（AraG）类似物已被证明可选择性地摄取 在实验室模型和最初的人体研究中，我们假设[18F]F-AraG 在CKI后肿瘤中产生T细胞免疫应答的患者中，信号将增加 治疗，这将与随后的临床获益相关。在目标1中，我们将 在[18F]F-AraG信号传导中，在用 CKI。在我们的第二个目标中，我们将使治疗后[18 F]F-AraG信号的变化与以下因素相关： 观察到的临床获益，定义为肿瘤稳定或缩小。第三个目标， 将肺和胃肠道中[18F]-AraG信号的变化与随后发生的较高的 免疫相关不良事件分级。拟议研究产生的数据将告知 开发一种新的免疫治疗反应的成像生物标志物，优化患者 选择和结果。此外，我们预测哪些患者将继续发展的能力 严重的毒性将更早地通知治疗机构以减轻这些副作用，以及 不良事件的个性化管理。