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首页> 外文期刊>BMC Cancer >Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy
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Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy

机译：NSCLC患者的基因组学既可以肯定PD-L1的表达，又可以预测其对抗PD-1免疫疗法的临床反应

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Programmed Death Ligand 1 (PD-L1) is a co-stimulatory and immune checkpoint protein. PD-L1 expression in non-small cell lung cancers (NSCLC) is a hallmark of adaptive resistance and its expression is often used to predict the outcome of Programmed Death 1 (PD-1) and PD-L1 immunotherapy treatments. However, clinical benefits do not occur in all patients and new approaches are needed to assist in selecting patients for PD-1 or PD-L1 immunotherapies. Here, we hypothesized that patient tumor cell genomics influenced cell signaling and expression of PD-L1, chemokines, and immunosuppressive molecules and these profiles could be used to predict patient clinical responses. We used a recent dataset from NSCLC patients treated with pembrolizumab. Deleterious gene mutational profiles in patient exomes were identified and annotated into a cancer network to create NSCLC patient-specific predictive computational simulation models. Validation checks were performed on the cancer network, simulation model predictions, and PD-1 match rates between patient-specific predicted and clinical responses. Expression profiles of these 24 chemokines and immunosuppressive molecules were used to identify patients who would or would not respond to PD-1 immunotherapy. PD-L1 expression alone was not sufficient to predict which patients would or would not respond to PD-1 immunotherapy. Adding chemokine and immunosuppressive molecule expression profiles allowed patient models to achieve a greater than 85.0% predictive correlation among predicted and reported patient clinical responses. Our results suggested that chemokine and immunosuppressive molecule expression profiles can be used to accurately predict clinical responses thus differentiating among patients who would and would not benefit from PD-1 or PD-L1 immunotherapies.
机译：程序性死亡配体1（PD-L1）是一种共刺激和免疫检查点蛋白。 PD-L1在非小细胞肺癌（NSCLC）中的表达是适应性耐药的标志，其表达通常用于预测程序性死亡1（PD-1）和PD-L1免疫治疗的结果。但是，并非所有患者都会有临床益处，因此需要新的方法来协助选择PD-1或PD-L1免疫疗法的患者。在这里，我们假设患者肿瘤细胞基因组学会影响细胞信号传导和PD-L1，趋化因子和免疫抑制分子的表达，并且这些谱可用于预测患者的临床反应。我们使用了来自接受pembrolizumab治疗的NSCLC患者的最新数据集。识别患者外显子组中有害的基因突变谱，并将其注释到癌症网络中，以创建NSCLC患者特定的预测性计算模拟模型。对癌症网络，模拟模型预测以及患者特定预测和临床反应之间的PD-1匹配率进行了验证检查。这24种趋化因子和免疫抑制分子的表达谱用于鉴定对PD-1免疫治疗有反应或无反应的患者。单独的PD-L1表达不足以预测哪些患者会对PD-1免疫疗法产生反应或不会产生反应。添加趋化因子和免疫抑制分子表达谱可使患者模型在预测和报告的患者临床反应之间实现大于85.0％的预测相关性。我们的研究结果表明，趋化因子和免疫抑制分子的表达谱可用于准确预测临床反应，从而区分哪些患者会受益于PD-1或PD-L1免疫疗法。

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