非小细胞肺癌的一线免疫疗法:如何选择,何去何从?

Expert review of respiratory medicine Pub Date : 2023-12-01 Epub Date: 2024-02-09 DOI:10.1080/17476348.2024.2302356
Andrea Mogavero, Ornella Cantale, Veronica Mollica, Shobana Anpalakhan, Alfredo Addeo, Giannis Mountzios, Alex Friedlaender, Ravindran Kanesvaran, Silvia Novello, Giuseppe Luigi Banna
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引用次数: 0

摘要

简介:免疫疗法(IO)为肺癌治疗树立了新的里程碑:免疫疗法(IO)为肺癌治疗树立了新的里程碑。一些注册研究已经批准了免疫检查点抑制剂(ICIs)在不同情况下的应用,包括转移性非小细胞肺癌(NSCLC)。众所周知,应答者只是患者中的一部分,因此利用预测因素来选择应答者已成为以患者为中心的治疗中需要解决的关键问题:在我们的综述中,我们就 ICIs 作为转移性 NSCLC 一线治疗的适应症、组织学、临床和血液生物标志物,以及其耐药机制和新的免疫学可操作靶点等方面进行了详细而便捷的横向分析。我们在PubMed上输入符合免疫疗法关键特征的关键词进行了文献检索:免疫疗法是肺癌治疗的支柱。目前的试验正在测试新型免疫阻断剂,评估与标准 ICIs 或抗体药物结合物(ADC)的组合方法,这些药物都含有免疫靶点。完善患者的选择是一项持续的挑战,也是一项越来越迫切的需求,以便最好地预测将持续从中受益的应答者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
First-line immunotherapy in non-small cell lung cancer: how to select and where to go.

Introduction: Immunotherapy (IO) has established a new milestone in lung cancer treatment. Several registrational studies have approved immune checkpoint inhibitors (ICIs) in different settings, including the metastatic nonsmall cell lung cancer (NSCLC). As well known, responders are just a certain proportion of patients; therefore, their selection by using predictive factors has stood out as a crucial issue to address in tailoring a patient-centered care.

Areas covered: In our review we propose a detailed yet handy cross section on ICIs as first-line treatment in metastatic NSCLC, regarding indications, histological, clinical, and blood-based biomarkers, other than their mechanisms of resistance and new immunological actionable targets. We performed a literature search through PubMed entering keywords complying with crucial features of immunotherapy.

Expert opinion: IO represents the backbone of lung cancer treatment. Trials are currently testing novel immune blockade agents assessing combinatorial approaches with standard ICIs, or antibody drug conjugates (ADC), harboring immunological targets. Perfecting patients' selection is an ongoing challenge and a more and more urgent need in order to best predict responders who will consistently benefit from it.

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