The IL-18-IFNγ axis predicts response to immunotherapy

摘要 CAR T细胞彻底改变了儿童白血病的治疗方法。然而，约50%的有反应的患者 最终复发，在约50%-70%的患者中，这种疗法会导致毁灭性的副作用(即神经毒性 (NTX)和细胞因子释放综合征(CRS))，可能导致长期的神经损伤和死亡。 尽管有迫切的需求，但没有临床生物标记物来预测生存或毒性。SCRI已经取得了实质性的进展 投资于CAR T疗法，是儿科CAR T细胞临床试验的世界领先者。这项拟议的项目 将通过帮助预测和减轻破坏性的、危及生命的副作用来加强这一计划 通过这种革命性的疗法，可能有助于预测无应答病例。来自我们飞行员的数据 使用SCRI CAR-T试验患者样本的实验表明，前单核细胞激活 患者单核细胞组分的状态和细胞因子谱可以预测两种血液中的CAR T毒性 和实体肿瘤，特别是我们看到了IL-18-干扰素𝛾𝛾轴的趋势。我们计划对这一令人鼓舞的试点项目采取行动 本提案中的数据以开发一系列有效的单核细胞生物标记物(细胞因子、流动和转录) 和机器学习算法，可以在患者进行试验之前使用，以节省时间和 为治疗失败的患者提供资源，并允许医疗团队做好更多准备，以缓解 对那些更容易患上这种病的人有毒性。该建议进一步扩展到开发人性化的老鼠 可以采用健康供体和儿科患者免疫系统恢复自然变异性的模型 人类免疫力调查IL-18-干扰素𝛾𝛾轴在驱动这两种治疗毒性方面的因果关系。该项目 将现有但未使用的SCRI CAR患者样本/数据大库与单核细胞组学分析相结合，以 开发治疗毒性的预测生物标记物(AIM 1)。我们打算进一步扩大这项工作的影响 为了机械地理解为什么某些患者的细胞通过使用新奇的 人源化小鼠模型(AIM2)。这是建立在开发治疗或战略，以提高安全性和 CAR-T治疗的疗效。重要的是，我们的临床T车专家团队(丽贝卡·加德纳博士、纳文博士 机器学习(Bobbie-Jo Webb-Robertson博士)、人性化小鼠(James Keck博士)和髓系小鼠 肿瘤生物学(希瑟·古斯塔夫森博士)为最佳成功提供了这笔赠款。

ABSTRACT CAR T-cells have revolutionized the treatment of pediatric leukemia. However, ~50% of responsive patients eventually relapse and in ~50-70% of patients, this therapy induces devastating side effects (i.e. neurotoxicity (NTX) and cytokine release syndrome (CRS)), potentially leading to long term neurological damage and death. There are no clinical biomarkers to predict survival or toxicity despite a crucial need. SCRI has made a substantial investment in CAR T therapy and is a world leader in pediatric CAR T cell clinical trials. This proposed project will build upon this program by helping to predict and mitigate the devastating, life-threatening side effects caused by this revolutionary therapy and may aide in the prediction of non-response cases. Data from our pilot experiments utilizing samples from patients on CAR-T trials at SCRI suggests that pre-monocyte activation status and cytokine profiles from the monocyte fraction of a patient can predict CAR T toxicity across both blood and solid tumors, in particular we see trends in the IL-18- IFN𝛾𝛾 axis. We plan to act on this encouraging pilot data in this proposal to develop a series of validated monocytic biomarkers (cytokine, flow and transcriptional) and machine learning algorithms which can be utilized prior to patients going on trial in order to save time and resources for patients who are set to fail treatment and allow medical teams to be more prepared to mitigate toxicity in those who are more prone to it. The proposal further expands to the development a humanized mouse model that can adopt the healthy donor and pediatric patient immune systems recapturing natural variability in human immunity to investigate causality of the IL-18- IFN𝛾𝛾 axis in driving both therapeutic toxicity. The project combines existing but unused large bank of SCRI CAR T patient samples/data with monocytic omics profiling to develop predictive biomarkers for therapeutic toxicity (AIM 1). We aim to further extend the impact of this work to mechanistically understand why certain patients’ cells are working against them through the use of novel humanized mouse models (AIM2). This is built upon to develop therapeutics or strategies to improve safety and efficacy of CAR-T treatments. Importantly, our team of experts in clinical CAR T (Dr. Rebecca Gardner, Dr. Navin Pinto), machine learning (Dr. Bobbie-Jo Webb-Robertson), humanized mice (Dr. James Keck), and myeloid tumor biology (Dr. Heather Gustafson) pose this grant for optimal success.