非小细胞肺癌中与免疫治疗应答相关的差异表达基因和KRAS突变分析-现代医学

非小细胞肺癌中与免疫治疗应答相关的差异表达基因和KRAS突变分析

单位：1. 新疆医科大学附属肿瘤医院肺内科二病区, 新疆乌鲁木齐 830054;
2. 新疆维吾尔自治区人民医院乳腺甲状腺外科, 新疆乌鲁木齐 830001

分类号：R734.2

出版年·卷·期（页码）：2025·53·第七期（1069-1079）

摘要：

目的：探讨非小细胞肺癌(NSCLC)中与抗PD-1/PD-L1治疗应答相关的分子机制以及KRAS突变对免疫治疗的敏感性。方法：分析GSE75037、GSE81089和TCGA数据集中NSCLC和对照之间的差异表达基因(DEGs)，通过加权基因共表达网络分析(WGCNA)构建基因共表达网络。在GSE126044数据集中鉴定抗PD-1/PD-L1治疗的患者中应答和无应答之间的DEGs，并采用Cox回归模型评估基因对患者总生存期(OS)的影响。通过RT-qPCR和Western blot检测预后相关基因的表达。此外，收集56例接受抗PD-1/PD-L1免疫治疗的NSCLC患者，分析最佳疗效为部分缓解(PR)、疾病稳定(SD)和疾病进展(PD)患者之间的临床信息。在TCGA数据集中分析KRAS突变情况及其对免疫治疗的敏感性。结果：在GSE75037、GSE81089和TCGA数据集中鉴定了1 298个共同DEGs。在GSE126044数据集中鉴定了2 111个与抗PD-1/PD-L1治疗应答相关的DEGs，并通过WGCNA识别了10个基因模块，其中棕色模块与有效组呈正相关。Cox回归分析显示，SPP1、PTPRH、SLC35F2、GPR37和PLA2G4F在GSE81089和TCGA数据集中均显示与预后的关联有统计学意义(均P<0.05)。RT-qPCR和Western blot检测与免疫治疗无应答组比较，SPP1、PTPRH、SLC35F2和GPR37在应答组中低表达，PLA2G4F则高表达。此外，KRAS在PR、SD和PD组中差异有统计学意义(χ²=6.47, P<0.05)。TCGA中KRAS的突变率为15.15%，并在免疫治疗应答组中的突变率高于无效组，对免疫治疗应答具有积极作用。结论：本研究鉴定的关键基因和在NSCLC患者抗PD-1/L1治疗应答中发挥重要作用，而KRAS突变在预测治疗效果中可能发挥关键作用。这些结果为NSCLC患者的个性化治疗策略提供了新的线索。

Objective: To investigate the molecular mechanisms associated with the response to anti-PD-1/PD-L1 therapy in non-small cell lung cancer(NSCLC), and the sensitivity of KRAS mutations to immunotherapy.Methods:Differentially expressed genes(DEGs) between NSCLC and controls in the GSE75037, GSE81089, and TCGA datasets were analyzed, and gene co-expression networks was constructed using weighted gene co-expression network analysis(WGCNA). DEGs between responders and non-responders to anti-PD-1/PD-L1 therapy were identified in the GSE126044 dataset, and a Cox regression model was used to evaluate the effect of genes on overall survival(OS) of patients. The expression of prognostic-related genes was detected by RT-qPCR and Western blot. In addition, clinical data were collected from 56 NSCLC patients who received anti-PD-1/PD-L1 immunotherapy, and clinical information was analyzed among patients with partial response(PR), stable disease(SD), and progressive disease(PD). KRAS mutation status and its sensitivity to immunotherapy were analyzed in the TCGA dataset. Results: A total of 1 298 common DEGs were identified in the GSE75037, GSE81089, and TCGA datasets. In the GSE126044 dataset, 2 111 DEGs associated with response to anti-PD-1/PD-L1 therapy were identified, and 10 gene modules were identified through WGCNA, among which the brown module was significantly positively correlated with the responder group. Cox regression analysis showed that SPP1, PTPRH, SLC35F2, GPR37, and PLA2G4F were significantly associated with prognosis in both the GSE81089 and TCGA datasets(all P<0.05). Compared with the non-responder group, RT-qPCR and Western blot analysis showed that SPP1, PTPRH, SLC35F2, and GPR37 were expressed at lower levels in the responder group, while PLA2G4F was expressed at a higher level. In addition, KRAS mutation differed significantly among the PR, SD, and PD groups(χ²=6.47, P<0.05). In the TCGA dataset, the KRAS mutation rate was 15.15%, and the mutation rate was higher in the responder group than in the non-responder group, suggesting a positive role in response to immunotherapy. Conclusion: The key genes identified in this study play important roles in the response to anti-PD-1/PD-L1 therapy in NSCLC patients. KRAS mutation may serve as a critical predictor of therapeutic efficacy. These findings provide new insights into personalized treatment strategies for NSCLC patients.

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