RNF43 p.G659fs 通过 PI3K/AKT/mTOR 信号通路和 HLA-E 上调导致 MSI-high 结直肠癌中 NK 细胞功能障碍
RNF43 p.G659fs leads to natural killer cell dysfunction in MSI-high colorectal cancer through PI3K/AKT/mTOR signaling and HLA-E up-regulation.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:PD-L1 Expression in NSCLC: Clouds in a Bright Sky.
PD-L1 Expression in NSCLC: Clouds in a Bright Sky.
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程序性死亡配体1(PD-L1)是使用检查点抑制剂(CPIs)进行免疫治疗的主要靶点,尤其在肺癌治疗中。肿瘤PD-L1表达已被认为是CPI应答的天然预测因子。这种预测关系主要归因于其被干扰素-γ上调,干扰素-γ由邻近肿瘤细胞的免疫细胞(主要是T淋巴细胞和NK 细胞)释放,驱动免疫抵抗机制。
然而,PD-L1表达在多个层面受到调控,包括致癌信号通路以及转录和转录后调控,可能导致假阳性预测。相反,PD-L1的可变糖基化可能损害免疫组化测量的准确性,导致假阴性预测数据。
此外,PD-L1表达在整个治疗过程中(如化疗和酪氨酸激酶抑制剂)表现出相对不稳定性,进一步限制了其临床实用性。在本综述中,我们聚焦于调控PD-L1表达的分子机制,特别强调肺癌。
我们还讨论了用于优化检查点抑制剂治疗患者选择的生物标志物策略,其中多模式/多组学元生物标志物方法正在兴起。这种综合性的富含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,因为存在众多竞争性的CPI应答预测候选标志物。
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.
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