摘要
目的:基于加权基因共表达网络筛选PD-L1阴性非小细胞肺癌(non-small cell lung cancer, NSCLC)患者的潜在免疫治疗靶点并筛选相应小分子药物提高免疫应答效率。方法:分别从TGCA数据库筛选出1 037例NSCLC数据和108例正常数据,以及GEO数据库中的60例NSCLC数据和9例正常数据。在数据标准化后,将PD-L1表达水平后五分位的患者定义为PD-L1阴性患者,两个数据集中的差异基因作为加权基因共表达网络分析的输入。同时,构建风险比例回归模型预测高风险基因对于预后的影响。最后在DrugBank数据库中筛选以风险基因为靶点的小分子药物并进行模拟对接。结果:风险比例回归模型通过六个风险基因(CXCL12、GBP1、TGM2、HMOX1、GBP3、C1QB)的表达将数据分为高风险组和低风险组,两组间患者的生存时间、生存状态、免疫细胞比例、基质细胞比例和基因表达均存在极大的差异(P<0.05),模型在测试集和验证集中的AUC分别达到了0.860和0.752。此外,高表达GBP1和TGM2患者预后更差,因此被确定为最终的生物标志物。以GBP1和TGM2为靶点,药物数据库共筛选到4个靶向基因的小分子药物,并达到有效结合。结论:GBP1和TGM2可能是NSCLC免疫治疗的潜在标志物,且与小分子药物的联药治疗有可能提高免疫应答效率。
Objective:To screen potential immunotherapy targets for PD-L1 negative non-small cell lung cancer(NSCLC)patients based on weighted gene co-expression network analysis and identify corresponding small molecule drugs to enhance immunotherapeutic response.Methods:A total of 1037 NSCLC samples and 108 normal samples were retrieved from the TCGA database,along with 60 NSCLC samples and 9 normal samples from the GEO database.After data normalization,patients with PD-L1 expression levels in the lowest quintile were defined as PD-L1 negative patients,and the differentially expressed genes between the two datasets were used as input for weighted gene co-expression network analysis.Concurrently,a Cox proportional hazards regression model was constructed to evaluate the prognostic impact of high-risk genes.Finally,small molecule drugs targeting the identified risk genes were screened from the DrugBank database and subjected to molecular docking simulations.Results:The COX proportional hazards regression model stratified patients into high-risk and low-risk groups based on the expression levels of six risk genes(CXCL12,GBP1,TGM2,HMOX1,GBP3,C1QB).Significant differences were observed between the two groups in terms of patient survival time,survival status,immune cell proportion,stromal cell proportion,and gene expression(P<0.05).The model achieved AUCs of 0.860 and 0.752 in the test and validation sets,respectively.Furthermore,GBP1 and TGM2 were associated with poorer prognosis in the high-risk group,and were thus identified as the final biomarkers.Four small molecule drugs targeting GBP1 and TGM2 were screened from the drug database and exhibited effective binding.Conclusion:GBP1 and TGM2 may serve as potential biomarkers for immunotherapy in NSCLC,and combination therapy with small molecule drugs targeting these genes could enhance immunotherapeutic response.
作者
柯益忠
石磊
KE Yizhong;SHI Lei(The Cancer Hospital of the University of Chinese Academy of Sciences(Zhejiang Cancer Hospital),Institute of Basic Medicine and Cancer(IBMC),Chinese Academy of Sciences,Zhejiang Hangzhou 310022,China.)
出处
《现代肿瘤医学》
CAS
2024年第15期2776-2782,共7页
Journal of Modern Oncology
