Department of Biomedical Engineering, University of Houston, Houston, TX 77004
J Immunol. 2021 Apr 1;206(7):1561-1568. doi: 10.4049/jimmunol.2001249. Epub 2021 Mar 10.
Chimeric Ag receptor (CAR) T cell therapy has shown astonishing potency in treating a variety of hematological malignancies in recent years. Along with this lifesaving potential comes the life-threatening toxicities of cytokine release syndrome (CRS) and neurotoxicity. This work seeks to consolidate biomarker candidates with the potential to predict the severity of CRS and neurotoxicity in patients receiving CD19-targeted CAR T cell therapy. In this systematic review, 33 clinical trials were evaluated for biomarkers that can predict the severity of posttreatment CRS and neurotoxicity. CRS and neurotoxicity occurred in 73.4 and 37% of the reviewed patients, respectively. Identified biomarker candidates included tumor burden, platelet count, C-reactive protein, ferritin, IFN-γ, IL-2, IL-6, IL-8, IL-10, IL-15, and TGF-β. Combinatorial algorithms based on cytokine levels and clinical parameters show excellent promise in predicting CAR-T-cell-therapy-associated toxicities, with improved accuracy over the component biomarkers.
嵌合抗原受体 (CAR) T 细胞疗法近年来在治疗多种血液系统恶性肿瘤方面显示出了惊人的疗效。在带来这种救命潜力的同时,也带来了细胞因子释放综合征 (CRS) 和神经毒性的致命毒性。这项工作旨在整合具有预测接受 CD19 靶向 CAR T 细胞治疗的患者 CRS 和神经毒性严重程度潜力的生物标志物候选物。在这项系统评价中,评估了 33 项临床试验中可预测治疗后 CRS 和神经毒性严重程度的生物标志物。在接受评估的患者中,分别有 73.4%和 37%发生了 CRS 和神经毒性。确定的生物标志物候选物包括肿瘤负担、血小板计数、C 反应蛋白、铁蛋白、IFN-γ、IL-2、IL-6、IL-8、IL-10、IL-15 和 TGF-β。基于细胞因子水平和临床参数的组合算法在预测 CAR-T 细胞治疗相关毒性方面显示出了巨大的潜力,其准确性优于单个生物标志物。