Ni Siqi, Liang Qi, Jiang Xingyu, Ge Yinping, Jiang Yali, Liu Lingxiang
Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
The Friendship Hospital of Ili Kazakh Autonomous Prefecture Ili & Jiangsu Joint Institute of Health, Yining 835000, Xinjiang Uygur Autonomous Regio, China.
Heliyon. 2024 Apr 17;10(8):e29840. doi: 10.1016/j.heliyon.2024.e29840. eCollection 2024 Apr 30.
The introduction of immune checkpoint inhibitors (ICIs) has revolutionized the treatment of lung cancer. Given the limited clinical benefits of immunotherapy in patients with non-small cell lung cancer (NSCLC), various predictors have been shown to significantly influence prognosis. However, no single predictor is adequate to forecast patients' survival benefit. Therefore, it's imperative to develop a prognostic model that integrates multiple predictors. This model would be instrumental in identifying patients who might benefit from ICIs. Retrospective analysis and small case series have demonstrated the potential role of these models in prognostic prediction, though further prospective investigation is required to evaluate more rigorously their application in these contexts. This article presents and summarizes the latest research advancements on immunotherapy prognostic models for NSCLC from multiple omics perspectives and discuss emerging strategies being developed to enhance the domain.
免疫检查点抑制剂(ICI)的引入彻底改变了肺癌的治疗方式。鉴于免疫疗法对非小细胞肺癌(NSCLC)患者的临床益处有限,各种预测指标已被证明会显著影响预后。然而,没有单一的预测指标足以预测患者的生存获益。因此,开发一个整合多个预测指标的预后模型势在必行。该模型将有助于识别可能从ICI中获益的患者。回顾性分析和小病例系列研究已经证明了这些模型在预后预测中的潜在作用,不过还需要进一步的前瞻性研究来更严格地评估它们在这些情况下的应用。本文从多个组学角度介绍并总结了NSCLC免疫疗法预后模型的最新研究进展,并讨论了为加强该领域而正在开发的新兴策略。