Department of Pathology, Faculty of Medicine, Dalhousie University Halifax, Nova Scotia, Canada.
Department of Laboratory Medicine, Faculty of Applied Medical Sciences, Umm Al-Qura University Makkah, Makkah, Saudi Arabia.
PLoS One. 2021 May 6;16(5):e0251080. doi: 10.1371/journal.pone.0251080. eCollection 2021.
Most lung cancer patients are diagnosed at an advanced stage, limiting their treatment options with very low response rate. Lung cancer is the most common cause of cancer death worldwide. Therapies that target driver gene mutations (e.g. EGFR, ALK, ROS1) and checkpoint inhibitors such anti-PD-1 and PD-L1 immunotherapies are being used to treat lung cancer patients. Identification of correlations between driver mutations and PD-L1 expression will allow for the best management of patient treatment. 851 cases of non-small cell lung cancer cases were profiled for the presence of biomarkers EGFR, KRAS, BRAF, and PIK3CA mutations by SNaPshot/sizing genotyping. Immunohistochemistry was used to identify the protein expression of ALK and PD-L1. Total PD-L1 mRNA expression (from unsorted tumor samples) was quantified by RT-qPCR in a sub-group of the cohort to assess its correlation with PD-L1 protein level in tumor cells. Statistical analysis revealed correlations between the presence of the mutations, PD-L1 expression, and the pathological data. Specifically, increased PD-L1 expression was associated with wildtype EGFR and vascular invasion, and total PD-L1 mRNA levels correlated weakly with protein expression on tumor cells. These data provide insights into driver gene mutations and immune checkpoint status in relation to lung cancer subtypes and suggest that RT-qPCR is useful for assessing PD-L1 levels.
大多数肺癌患者在晚期被诊断出来,这限制了他们的治疗选择,反应率非常低。肺癌是全球最常见的癌症死因。针对驱动基因突变(如 EGFR、ALK、ROS1)和检查点抑制剂(如抗 PD-1 和 PD-L1 免疫疗法)的治疗方法正被用于治疗肺癌患者。确定驱动突变与 PD-L1 表达之间的相关性将有助于患者治疗的最佳管理。对 851 例非小细胞肺癌病例进行了 SNaPshot/基因分型,以检测生物标志物 EGFR、KRAS、BRAF 和 PIK3CA 突变的存在。免疫组织化学用于鉴定 ALK 和 PD-L1 的蛋白表达。在队列的亚组中通过 RT-qPCR 定量未分选肿瘤样本中的总 PD-L1 mRNA 表达,以评估其与肿瘤细胞中 PD-L1 蛋白水平的相关性。统计分析揭示了突变、PD-L1 表达和病理数据之间的相关性。具体而言,PD-L1 表达增加与野生型 EGFR 和血管浸润有关,而总 PD-L1 mRNA 水平与肿瘤细胞上的蛋白表达弱相关。这些数据提供了有关与肺癌亚型相关的驱动基因突变和免疫检查点状态的见解,并表明 RT-qPCR 可用于评估 PD-L1 水平。