(PQ8) Predicting immune-related toxicity in the adjuvant melanoma setting with checkpoint inhibition

项目总结 免疫检查点抑制物(ICI)，例如抗CTLA-4(Ipilimumab)或抗PD-1(nivolumab，pembrolizumab)， 改变了晚期黑色素瘤的治疗格局，增强了抗肿瘤活性， 在部分患者中产生持久的临床益处。ICIS已被证明在佐剂中有效 用于治疗黑色素瘤和许多其他癌症(例如，膀胱癌、肺癌、肾癌)。然而， 免疫相关不良事件(IrAEs)是充分发挥ICI潜力的关键障碍： 接受ICI治疗的患者会出现严重的免疫毒性，涉及多个器官，导致 发病率高，需要系统治疗或停止治疗。在试点测试中，我们使用了 含有约20,000个全长人类蛋白的人类蛋白质组阵列用于分析67例患者血清中的抗体水平 接受抗CTLA-4或抗PD-1治疗的黑色素瘤患者。我们的结果确定了不同的治疗前血清 自身抗体(AutoAbbs)与严重的irAEs的发生有关。使用人性化的FcgR鼠标 模型中，我们生成了初步数据，表明治疗前患者血清免疫球蛋白可能会加剧 IrAEs的发展。最后，使用一种新的质谱学方法，我们证明了 ICI治疗的黑色素瘤患者的特定血清蛋白与治疗效果之间的关系。我们的中央 假设黑色素瘤患者的一部分具有基线自身免疫易感性，其特征是 预测和加重ICI发展的特异性自身抗体和血清蛋白谱系 毒性。我们的建议是对RFA-CA-17-017-PQ8的直接回应：“什么是预测性生物标志物 与检查点抑制相关的免疫相关不良事件的发生，以及它们是否 与疗效的标记物有关？“我们将利用大量来自CHECKMate-238的治疗前血清 在切除的III/IV期黑色素瘤中进行佐剂抗CTLA-4与抗PD-1的3期试验，以评估 自身抗体和血清蛋白与irAEs发展及无复发生存率的关系 (功效)。我们将使用我们的小鼠模型来测试预先存在的免疫系统之间的因果关系 ICI的反应和毒性，以选择最有可能作为irAEs生物标志物的AutoAbs。翻译型 我们工作的影响是，检测基线毒性相关的自体抗体可以识别黑色素瘤患者 可能因治疗、指导治疗选择和排序或毒性而发生严重的irAEs 管理层。我们在自体抗体和血清蛋白质组学方面的工作可能会定义新的靶点，这些靶点会影响 并为在不损害抗肿瘤免疫的情况下减轻毒性的新策略提供了洞察 回应。

PROJECT SUMMARY Immune checkpoint inhibitors (ICI), e.g., anti-CTLA-4 (ipilimumab) or anti-PD-1 (nivolumab, pembrolizumab), have transformed the therapeutic landscape for advanced melanoma, enhancing anti-tumor activity and producing durable clinical benefit in a subset of patients. ICIs have been shown to be effective in the adjuvant setting for melanoma, and for treatment of many other cancers (e.g., bladder, lung, renal cell). However, immune-related adverse events (irAEs) are a critical obstacle to realizing the full potential of ICI: a substantial proportion of ICI-treated patients develop severe immune toxicities involving multiple organs, causing significant morbidity and requiring systemic treatment or therapy discontinuation. In pilot testing, we used a human proteome array with ~20,000 full-length human proteins to analyze antibody levels in sera from 67 melanoma patients who received anti-CTLA-4 or anti-PD-1. Our results identified distinct pre-treatment serum autoantibodies (autoAbs) associated with development of severe irAEs. Using a humanized FcgR mouse model, we generated preliminary data to suggest that pre-treatment patient sera IgG may exacerbate development of irAEs. Finally, using a novel mass spectrometry approach we demonstrated an association between specific serum proteins from ICI-treated melanoma patients and treatment efficacy. Our central hypothesis is that a subset of melanoma patients has a baseline autoimmune susceptibility, characterized by a repertoire of specific preexisting autoAbs and serum proteins that predicts and exacerbates development of ICI toxicity. Our proposal is in direct response to RFA-CA-17-017 - PQ8: “What are the predictive biomarkers for the onset of immune-related adverse events associated with checkpoint inhibition, and are they related to markers for efficacy?” We will utilize a large cohort of pre-treatment sera from the CheckMate-238 phase 3 trial of adjuvant anti-CTLA-4 vs. anti-PD-1 in resected Stage III/IV melanoma to assess the relationship between autoAbs and serum proteins and development of irAEs and recurrence-free survival (efficacy). We will use our mouse model to test the cause-effect relationship between pre-existing immune responses and toxicities from ICI to select the autoAbs most likely to be biomarkers for irAEs. The translational impact of our work is that detection of baseline toxicity-associated autoAbs could identify melanoma patients likely to develop severe irAEs from treatment, guiding therapy selection and sequencing or toxicity management. Our work with autoAbs and serum proteomics may define new targets which impact the onset of irAEs and provide insight into new strategies to mitigate toxicity without compromising the anti-tumor immune response.