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Molecular characterization of clinical responses to PD‐1/PD‐L1 inhibitors in non‐small cell lung cancer: Predictive value of multidimensional immunomarker detection for the efficacy of PD‐1 inhibitors in Chinese patients

机译:非小细胞肺癌对PD-1 / PD-L1抑制剂临床反应的分子表征:多维免疫标志物检测对中国患者PD-1抑制剂疗效的预测价值

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摘要

According to multiple studies, the objective response rate of PD‐1/PD‐L1 inhibitors in the second‐line treatment of unscreened non‐small cell lung cancer (NSCLC) is only approximately 20%. Predictive biomarkers of treatment efficacies are still under investigation. In selected NSCLC patients with PD‐L1 expression ≥ 50%, the response rate of pembrolizumab in first‐line treatment can reach 44.8%. Moreover, patients with a higher tumor mutation burden (TMB) tend to achieve a better response with nivolumab. Besides PD‐L1 expression and TMB, taking all these indicators into consideration would hypothetically maximize the clinical response in a specific subgroup of patients. Our study aims to accumulate large and complete samples and clinical data to verify the biomarkers and their cutoff values related to the efficacy of PD‐1/PD‐L1 inhibitors in Chinese NSCLC patients, and to construct a comprehensive predictive model by combining multi‐omics data with contemporary machine learning techniques. NSCLC patients administered treatment of anti‐PD‐1/PD‐L1 antibodies or a combination with other drugs have been enrolled. The estimated enrollment is 250 participants. A sophisticated predictive model of immunotherapy response in the Chinese population has not yet been developed. It is clinically and practically imperative to comprehensively evaluate the possible indicators of Chinese NSCLC patients through multiple test platforms, such as next generation sequencing, PCR, or immunohistochemistry. This study is registered in the Chinese Clinical Trial Registry (ChiCTR1900021395).
机译:根据多项研究,PD-1 / PD-1L1抑制剂在未经筛选的非小细胞肺癌(NSCLC)的二线治疗中的客观缓解率仅为约20%。治疗效果的预测性生物标志物仍在研究中。在选定的PD-L1表达≥50%的NSCLC患者中,派姆单抗在一线治疗中的缓解率可达到44.8%。此外,具有更高肿瘤突变负担(TMB)的患者倾向于用尼古鲁单抗获得更好的反应。除了PD-L1表达和TMB,假设所有这些指标都可以在特定亚组患者中最大程度地提高临床反应。我们的研究旨在积累大量完整的样本和临床数据,以验证与中国NSCLC患者PD-1 / PD-1L1抑制剂疗效相关的生物标志物及其临界值,并通过结合多组学来构建全面的预测模型现代机器学习技术的数据。已纳入接受抗PD-1 / PD-L1抗体或与其他药物联合治疗的NSCLC患者。估计人数为250名参与者。尚未建立中国人群免疫疗法应答的复杂预测模型。通过下一代测序,PCR或免疫组化等多种测试平台全面评估中国非小细胞肺癌患者的可能指标在临床和实践上势在必行。该研究已在中国临床试验注册中心(ChiCTR1900021395)中注册。

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