Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos 14784-400, São Paulo, Brazil.
Life and Health Sciences Research Institute (ICVS), Medical School, University of Minho, 4710-057 Braga, Portugal.
Int J Mol Sci. 2023 Jul 25;24(15):11887. doi: 10.3390/ijms241511887.
Lung cancer has the highest mortality rate among all cancer types, resulting in over 1.8 million deaths annually. Immunotherapy utilizing immune checkpoint inhibitors (ICIs) has revolutionized the treatment of non-small cell lung cancer (NSCLC). ICIs, predominantly monoclonal antibodies, modulate co-stimulatory and co-inhibitory signals crucial for maintaining immune tolerance. Despite significant therapeutic advancements in NSCLC, patients still face challenges such as disease progression, recurrence, and high mortality rates. Therefore, there is a need for predictive biomarkers that can guide lung cancer treatment strategies. Currently, programmed death-ligand 1 (PD-L1) expression is the only established biomarker for predicting ICI response. However, its accuracy and robustness are not consistently reliable. This review provides an overview of potential biomarkers currently under development or in the validation stage that hold promise in improving the classification of responders and non-responders to ICI therapy in the near future.
肺癌是所有癌症类型中死亡率最高的一种,每年导致超过 180 万人死亡。利用免疫检查点抑制剂(ICIs)的免疫疗法已经彻底改变了非小细胞肺癌(NSCLC)的治疗方法。ICI 主要是单克隆抗体,调节对维持免疫耐受至关重要的共刺激和共抑制信号。尽管 NSCLC 的治疗取得了重大进展,但患者仍然面临疾病进展、复发和高死亡率等挑战。因此,需要有预测性生物标志物来指导肺癌的治疗策略。目前,程序性死亡配体 1(PD-L1)表达是唯一确定的预测 ICI 反应的生物标志物。然而,其准确性和稳健性并不总是可靠的。本综述提供了目前正在开发或验证阶段的潜在生物标志物的概述,这些标志物有望在未来改善对 ICI 治疗反应者和非反应者的分类。