Project 3

项目3

• 批准号: 10434089
• 负责人: MICHELLE KROGSGAARD
• 金额: $ 28.32万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-19 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10434089
• 关键词: Adjuvant; Adjuvant Study; American; Antibodies; Autoantibodies; Autoimmune; Autoimmune Diseases; B-Lymphocytes; Biological Assay; Biological Markers; Bladder; Cancer Patient; Clinical; Clinical Laboratory Improvement Amendments; Clinical Trials; Colitis; Data; Dermatologic; Development; Diarrhea; Endocrine; Exposure to; Goals; Hepatic; Human; Immune; Immune checkpoint inhibitor; Immunoglobulin G; Immunologic Adjuvants; Immunologic Markers; Immunosuppression; Inflammatory Bowel Diseases; Kidney; Laboratories; Length; Lung; Malignant Neoplasms; Morbidity - disease rate; Nivolumab; Oncologist; Organ; Pathogenicity; Pathologist; Patients; Phase; Phase II Clinical Trials; Placebo Control; Placebos; Preclinical Testing; Predisposition; Prevention; Prevention strategy; Proteins; Proteome; Proteomics; Publishing; Randomized; Recurrence; Regimen; Renal Cell Carcinoma; Resected; Role; Selection for Treatments; Serum; T-Lymphocyte; TNF gene; Testing; Therapeutic; Thyroiditis; Toxic effect; Ulcerative Colitis; Validation; Work; anti-CTLA4; anti-PD-1; base; biomarker signature; biomarker-driven; cancer type; checkpoint inhibition; cohort; college; experience; experimental study; gastrointestinal; high risk; humanized mouse; immune-related adverse events; infliximab; interest; ipilimumab; melanoma; mouse model; pembrolizumab; phase 2 study; phase II trial; predicting response; predictive test; predictive tools; prevent; prophylactic; response; tool; treatment optimization; treatment strategy; tumor

PROJECT 3 SUMMARY Immune checkpoint inhibitors have transformed melanoma treatment, producing durable responses, prolonged survival, and clinical benefit in a significant proportion of patients. Moreover, they delay recurrence and extend survival in the adjuvant melanoma setting, and have also shown efficacy in a range of different cancer types. However, immune checkpoint inhibition (ICI) therapy can also be accompanied by immune-related adverse events (irAEs) that impact multiple organs, cause significant morbidity, and require immunosuppression or discontinuation of ICI treatment. There is an urgent need to identify patients who will develop severe irAEs from ICI. This would enable us to optimize treatment selection and sequencing, justify preventive strategies to mitigate toxicity, and better manage toxicities. While there is intense interest in identifying markers to predict response to ICI, no pre-treatment biomarker tool can predict irAEs associated with ICI for any cancer type. The goal of our project is to develop a predictive tool that enables clinicians to minimize exposure of patients to severe toxicity, while maximizing clinical benefit from ICI. We hypothesize that a subset of melanoma patients has a baseline, sub-clinical autoimmune susceptibility, characterized by specific pre-existing autoantibodies (autoAbs) that can predict and exacerbate the development of toxicity from ICI therapy. We have identified autoAb signatures in baseline (pre-treatment) sera that predict severe immune toxicity in melanoma patients treated with ICI (AUC >0.95). Using a humanized mouse model, we found that autoAbs from baseline sera of melanoma patients can exacerbate irAEs from ICI. In this project, we propose to refine and validate baseline autoAb biomarker signatures of ICI toxicity using sera (n=600) from two large adjuvant ICI clinical trials for resected stage-III/IV melanoma (Aim 1). To understand the relevance of specific autoAbs to common irAEs (e.g., colitis) and to investigate an autoimmune predisposition in some patients, we will compare irAE-associated autoAbs with those from inflammatory bowel disease patients and from normal donors. We will use our humanized FcR mouse model to determine the cause-effect relationship between autoAbs and irAEs, with a focus on colitis, and for preclinical testing of prophylactic anti-TNF- as a strategy to mitigate gastrointestinal (GI) toxicity from ICI (Aim 2). These findings will inform a biomarker-driven phase-II trial of prophylactic anti-TNF- (infliximab) in patients receiving ICI therapy who are at high risk for developing severe diarrhea and colitis (Aim 3). Our work will inform personalized melanoma treatment strategies by validating a robust pre-treatment biomarker to enable clinicians to optimize ICI regimens and minimize patient exposure to severe irAEs. We will both identify an autoimmune susceptibility to irAE development and establish whether prophylactic TNF- blockade mitigates development of GI toxicity from ICI in patients identified as being at high risk of these irAEs.

项目3摘要 免疫检查点抑制剂已转化了黑色素瘤治疗，产生持久反应，延长 在很大一部分患者中的生存和临床益处。此外，它们延迟复发并扩展 在可调节的黑色素瘤环境中的生存，还显示了各种不同癌症类型的效率。 但是，免疫抑制（ICI）疗法也可以伴有与免疫相关的敌人 影响多个器官，引起明显发病率的事件（伊拉斯），需要免疫抑制或 中断ICI治疗。迫切需要确定将从 ICI。这将使我们能够优化治疗选择和测序，证明预防性策略是合理的 毒性，更好地管理毒性。虽然有浓厚的兴趣识别标记以预测对 ICI，没有预处理生物标志物工具可以预测与任何癌症类型相关的ICI相关的IRAE。我们的目标 项目是开发一种预测工具，使临床医生能够最大程度地减少患者暴露于严重 毒性，同时最大化ICI的临床益处。 我们假设一部分黑色素瘤患者具有基线，亚临床自身免疫性 易感性，其特征是可以预测和 加剧ICI疗法的毒性发展。我们已经确定了基线中的自动签名 （预处理）血清预测用ICI治疗的黑色素瘤患者严重免疫毒性（AUC> 0.95）。 使用人源化的小鼠模型，我们发现来自黑色素瘤患者基线血清的自动AB可以 ICI加剧了伊拉斯。在这个项目中，我们建议完善和验证基线自动AutoAB生物标志物 使用Sera（n = 600）的ICI毒性的特征来自两个大型调整ICI临床试验，用于切除的III/IV期 黑色素瘤（AIM 1）。了解特定自动动体与普通伊拉斯（例如结肠炎）的相关性和 调查某些患者的自身免疫性倾向，我们将比较与IRAE相关的自动AB 来自炎症性肠病患者和正常供体。我们将使用人源化的FCR鼠标 确定自动摄影和伊拉斯之间的原因效应关系的模型，重点是结肠炎以及用于 预防性抗TNF-的临床前测试是减轻ICI胃肠道（GI）毒性的策略（AIM 2）。这些发现将为预防性抗TNF-（英夫利昔单抗）的生物标志物驱动的II期试验提供信息。 接受患有严重腹泻和结肠炎的高风险的ICI疗法（AIM 3）。 我们的工作将通过验证强大的预处理生物标志物来为个性化的黑色素瘤治疗策略提供信息 使临床医生能够优化ICI方案并最大程度地减少患者暴露于严重的伊拉斯。我们俩都会识别 对IRAE开发和建立的自身免疫性敏感性是否可以减轻预防性TNF- ICI的GI毒性在被确定为这些伊拉斯高风险的患者中。