Ferrari Victoria, Gal Jocelyn, Mograbi Baharia, Milano Gerard
Antoine Lacassagne Center, Department of Medical Oncology, University Côte d'Azur, 33 Avenue de Valombrose, 06189 Nice, France.
Antoine Lacassagne Center, Department of Epidemiology and Biostatistics, University Côte d'Azur, 33 Avenue de Valombrose, 06189 Nice, France.
Int J Mol Sci. 2025 Jun 24;26(13):6066. doi: 10.3390/ijms26136066.
Programmed Death-Ligand 1 (PD-L1) is a major target for immunotherapy using checkpoint inhibitors (CPIs), particularly in lung cancer treatment. Tumoral PD-L1 expression has been recognized as a natural predictor of CPI response. This predictive relationship is primarily due to its upregulation by interferon-gamma, which is released by immune cells (mainly T lymphocytes and natural killer cells) in proximity to tumor cells, driving an immune resistance mechanism. However, PD-L1 expression is modulated at multiple levels, including oncogenic signaling pathways, and transcriptional and post-transcriptional regulations, potentially leading to false positive predictions. Conversely, variable glycosylation of PD-L1 may compromise the accuracy of immunohistochemical measurements, resulting in false negative predictive data. In addition, PD-L1 expression demonstrates relative instability throughout treatment courses (e.g., chemotherapy and tyrosine kinase inhibitors), further limiting its clinical utility. In this review, we focused on the molecular mechanisms governing PD-L1 expression with a special emphasis on lung cancer. We also discussed biomarker strategies for optimizing patient selection for checkpoint inhibitor therapy where multimodal/multi-omics meta-biomarker approaches are emerging. Such comprehensive PD-L1-enriched biomarker strategies require evaluation through large-scale prospective studies, particularly in lung cancer, where numerous competing predictive candidates exist for CPI response.
程序性死亡配体1（PD-L1）是使用检查点抑制剂（CPI）进行免疫治疗的主要靶点，尤其是在肺癌治疗中。肿瘤PD-L1表达已被视为CPI反应的天然预测指标。这种预测关系主要归因于其被γ-干扰素上调，γ-干扰素由靠近肿瘤细胞的免疫细胞（主要是T淋巴细胞和自然杀伤细胞）释放，从而驱动免疫抵抗机制。然而，PD-L1表达在多个水平受到调控，包括致癌信号通路、转录和转录后调控，这可能导致假阳性预测。相反，PD-L1的可变糖基化可能会影响免疫组化测量的准确性，从而产生假阴性预测数据。此外，PD-L1表达在整个治疗过程（如化疗和酪氨酸激酶抑制剂治疗）中表现出相对不稳定性，进一步限制了其临床应用。在本综述中，我们重点关注了调控PD-L1表达的分子机制，尤其侧重于肺癌。我们还讨论了生物标志物策略，以优化检查点抑制剂治疗的患者选择，此时多模式/多组学元生物标志物方法正在兴起。这种全面的富含PD-L1的生物标志物策略需要通过大规模前瞻性研究进行评估，尤其是在肺癌中，因为对于CPI反应存在众多相互竞争的预测指标。
