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非小细胞肺癌的一线免疫治疗:如何选择及何去何从。

First-line immunotherapy in non-small cell lung cancer: how to select and where to go.

机构信息

Department of Oncology, University of Turin, Turin, Italy.

Medical Oncology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.

出版信息

Expert Rev Respir Med. 2023 Dec;17(12):1191-1206. doi: 10.1080/17476348.2024.2302356. Epub 2024 Feb 9.

Abstract

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.

摘要

简介

免疫疗法(IO)在肺癌治疗中树立了新的里程碑。几项注册研究已经批准了免疫检查点抑制剂(ICI)在不同环境下的应用,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比例;因此,通过使用预测因素来选择他们已经成为制定以患者为中心的护理方案的关键问题。

涵盖领域

在我们的综述中,我们提出了一个详细而实用的关于 ICI 作为转移性 NSCLC 一线治疗的部分,包括适应症、组织学、临床和基于血液的生物标志物,以及它们的耐药机制和新的免疫治疗靶点。我们通过 PubMed 进行文献检索,输入符合免疫治疗关键特征的关键词。

专家意见

IO 代表了肺癌治疗的支柱。目前正在进行临床试验,测试新型免疫阻断剂,评估与标准 ICI 或携带免疫靶点的抗体药物偶联物(ADC)的联合治疗方法。完善患者选择是一个持续的挑战,也是一个越来越紧迫的需求,以便更好地预测那些将从中持续受益的应答者。

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