模拟CART-细胞-肿瘤细胞相互作用过程中信号特征的演变
Simulating the Evolution of Signaling Signatures during CART-Cell -- Tumor Cell Interactions
摘要：
免疫疗法已被证明在癌症治疗中具有显著的治疗功效。在过去的十年中，过继性细胞疗法，如嵌合抗原受体T细胞（CART细胞）疗法，获得了FDA对特定癌症的批准。此外，还有许多临床试验正在研究其他设计和目标。然而，尽管CART细胞疗法令人兴奋和有希望的潜力，但对治疗的反应率在研究、患者和癌症之间差异很大。仍然存在开发更准确地预测CART细胞功能和临床功效的计算框架的未满足的需求。在这里，我们提出了一个用逻辑规则模拟的粗粒度模型，该模型展示了CART细胞和肿瘤细胞之间相互作用后信号特征的演变，并允许在实验之前对CART细胞功能进行基于计算机模拟的预测。
英文摘要：
Immunotherapies have been proven to have significant therapeutic efficacy in the treatment of cancer. The last decade has seen adoptive cell therapies, such as chimeric antigen receptor T-cell (CART-cell) therapy, gain FDA approval against specific cancers. Additionally, there are numerous clinical trials ongoing investigating additional designs and targets. Nevertheless, despite the excitement and promising potential of CART-cell therapy, response rates to therapy vary greatly between studies, patients, and cancers. There remains an unmet need to develop computational frameworks that more accurately predict CART-cell function and clinical efficacy. Here we present a coarse-grained model simulated with logical rules that demonstrates the evolution of signaling signatures following the inter-action between CART-cells and tumor cells and allows for in silico based prediction of CART-cell functionality prior to experimentation.
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