Enhancing anti-tumour efficacy with immunotherapy combinations.

Lancet (London, England) Pub Date : 2021-03-13 Epub Date: 2020-12-04 DOI:10.1016/S0140-6736(20)32598-8
Funda Meric-Bernstam, James Larkin, Josep Tabernero, Chiara Bonini
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引用次数: 144

Abstract

Several tumour types are responsive to immunotherapy, as shown by regulatory approvals for immune checkpoint inhibitors. However, many patients either do not respond or do not have durable clinical benefit. Thus, there is great interest in developing predictors of response to immunotherapy and rational combination therapies that can enhance efficacy by overcoming primary and acquired resistance. In this Review, we provide an assessment of immunotherapy response biomarkers that can identify patients who will benefit from monotherapy rather than from combinations. We review the rationale for combination therapy and different strategies, including combinations with chemotherapy, targeted therapy, radiation therapy, intratumoural therapies, other immunomodulators, and adaptive cell therapy, including chimeric antigen T-cell receptors and other novel T-cell receptor-based therapies. There are many combination partners in development; therefore, a programmatic approach is needed to develop a framework for biomarker-driven combination therapy selection.

联合免疫治疗增强抗肿瘤疗效。
免疫检查点抑制剂的监管批准表明,几种肿瘤类型对免疫治疗有反应。然而,许多患者要么没有反应,要么没有持久的临床获益。因此,人们对开发免疫治疗反应的预测因子和合理的联合疗法非常感兴趣,这些疗法可以通过克服原发性和获得性耐药来提高疗效。在这篇综述中,我们提供了一种免疫治疗反应生物标志物的评估,可以识别从单一治疗中获益的患者,而不是从联合治疗中获益的患者。我们回顾了联合治疗的基本原理和不同的策略,包括联合化疗、靶向治疗、放射治疗、肿瘤内治疗、其他免疫调节剂和适应性细胞治疗,包括嵌合抗原t细胞受体和其他新型t细胞受体为基础的治疗。在发展中有许多合作伙伴;因此,需要一种程序化的方法来开发一个生物标志物驱动的联合治疗选择框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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