CAR-T(CAR-T)细胞疗法在非肿瘤性疾病中的应用
Chimeric antigen receptor T (CAR-T) cell therapy in non-oncological diseases.
CAR-T(CAR-T)细胞在血液系统恶性肿瘤中的应用推动了这种免疫治疗形式的显著进展。
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Data-driven computational modeling of CAR-T cell function.
Data-driven computational modeling of CAR-T cell function.
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我们的工作表明,尽管治疗前 CAR-T 细胞功能参数因患者和产品而异,但这些参数并不能预测初始治疗应答。
我们采用常微分方程(ODE)药代动力学(PK)和药效学(PD)模型,描述关键CAR-T 细胞功能参数。依据本方法建立的模型参数具有产品特异性,来自临床试验NCT04186520中对每位患者CAR-T 产品开展的体外检测。
不同产品间体外细胞毒性动力学及随后估算的模型参数存在显著差异,但在所研究的患者总体中,这些差异无法预测治疗后早期(28天)或晚期(90天)应答。不过,模型估算中反映CAR-T 细胞对肿瘤细胞毒性反应增强的参数差异,与持久治疗应答(180天内未复发)相关。此外,在弥漫大B细胞淋巴瘤(DLBCL)患者队列中,我们发现估算CAR-T 细胞间协同性的模型参数也与持久治疗应答相关,并可能与CAR-T 产品中CD4:CD8比例差异有关。
总体而言,我们的研究显示,治疗前CAR-T 细胞功能参数因患者和产品而异,但不能预测初始治疗应答。在一系列不同的初始产品动力学参数下,均可能实现初始治疗应答。不过,我们观察到,初始产品可能存在与疾病复发相关的独特动力学特征。
We use an ordinary differential equation (ODE)-based pharmacokinetic (PK) and pharmacodynamic (PD) model to characterize key CAR-T cell functional parameters. Parameters for the model developed using our method are product-specific and derived from in vitro assays performed on individual patient CAR-T products from clinical trial NCT04186520.
Our results demonstrate that while considerable variability is present in in vitro cytotoxicity kinetics and subsequently estimated model parameters between each product, these differences do not predict early (28 days) or late responses (90 days) after treatment across the total cohort of patients investigated. However, we show that differences in an estimated model parameter for increased CAR-T cell responsiveness to tumor cytotoxicity are correlated with durable therapy responses (no relapse through 180 days). Additionally, in a cohort of diffuse large B-cell lymphoma (DLBCL) patients, we demonstrate that a model parameter estimating cooperativity between CAR-T cells is also correlated with durable therapy responses and that may be related to differences in CD4:CD8 ratios in the CAR-T cell product.
Overall, our work demonstrates that while pre-treatment CAR-T cell functional parameters vary on a patient and product basis, these parameters do not predict initial therapeutic responses. We find that initial therapeutic responses are possible across a range of initial product kinetic parameters. However, we observed that their potentially exist unique kinetic properties associated with the initial product that is predictive of disease relapse.
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