基于eQTL定位筛选乳腺癌免疫相关标志物:孟德尔随机化与转录组学研究  

Identification of immune-related markers of breast cancer based on eQTLlocalization: a Mendelian randomization and transcriptomics study

作　　者：何亚玲 张鑫 吴泽远 张平茜 叶亚林 潘云 李艳 HE Yaling;ZHANG Xin;WU Zeyuan;ZHANG Pingxi;YE Yalin;PAN Yun;LI Yan(School of Basic Medical Sciences,Dali University,Dali 671000,Yunnan,China;Department of Pathology,the First Affiliated Hospital of Dali University,Dali 671000,Yunnan,China)

机构地区：[1]大理大学基础医学院,云南大理671000 [2]大理大学第一附属医院病理科,云南大理671000

出　　处：《右江医学》2025年第2期102-114,共13页Chinese Youjiang Medical Journal

基　　金：国家自然科学基金(82160044)。

摘　　要：目的 通过表达数量性状位点(eQTL)定位筛选乳腺癌免疫相关分子标志物,旨在为乳腺癌的诊断和治疗寻找潜在靶标。方法 对来自GEO数据库的3个乳腺癌数据集进行系统分析,利用eQTL分析确定工具变量(IVs),利用公开的乳腺癌全基因组关联(GWAS)数据进行孟德尔随机化(MR)分析,得到与MR相关的基因并通过OR值确定基因的风险程度,与GEO数据集中识别的差异表达基因(DEGs)取交集得到疾病的关键基因。然后对关键基因进行GO、KEGG、GSEA富集分析和免疫细胞浸润及基因免疫相关性分析,进一步分析关键基因在乳腺癌中的作用。最后使用独立的GEO数据集和TCGA数据进行验证。结果 通过差异分析得到307个上调基因,440个下调基因。利用MR分析和DEGs交叉共得到9个疾病的关键基因(PARP1、MUC1、LILRB2、TNNT1、CTNNAL1、DNASE1L3、HOXA9、PIK3R1、SLPI),这些基因参与了乳腺癌发生发展过程中的B细胞受体、细胞凋亡等信号通路。根据CIBERSORT分析得出,乳腺癌中CD4^(+) T细胞浸润显著下降,M0巨噬细胞浸润显著上升,且关键基因与na6ve B以及记忆B细胞之间存在负调控关系,与M0巨噬细胞及调节T细胞等存在正调控关系,表明关键基因与乳腺癌细胞免疫的关系密切。结论 筛选出来的关键基因尤其是DNASE1L3与乳腺癌的免疫进程密切关联,未来可能会成为乳腺癌免疫治疗的理想靶标。Objective To screen breast cancer immune-related molecular markers through expression quantitative trait loci(eQTL)localization,so as to provide potential targets for the diagnosis and treatment of breast cancer.Methods Systematic analysis was conducted on three breast cancer datasets from GEO database.eQTL analysis was utilized to identify instrumental variables(IVs).Subsequently,Mendelian randomization(MR)analysis was performed using publicly available genome-wide association study(GWAS)data of breast cancer.Genes associated with MR were obtained,and their risk levels were determined through odds ratios(OR).The intersection of these genes with differentially expressed genes(DEGs)identified from the GEO datasets was then taken to obtain key genes for the disease.And then,gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analyses,gene set enrichment analysis(GSEA),and immune cell infiltration and gene-immune correlation analyses were conducted on key genes to further elucidate their roles in breast cancer.Finally,independent GEO datasets and the cancer genome atlas(TCGA)data were used for validation.Results A total of 307 upregulated genes and 440 downregulated genes were identified through differential expression analysis.A total of 9 disease-critical genes were identified through MR analysis and the intersection of DEGs:PARP1,MUC1,LILRB2,TNNT1,CTNNAL1,DNASE1L3,HOXA9,PIK3R1,and SLPI.These genes were involved in signaling pathways such as B-cell receptor signaling and apoptosis,which play important roles in the development and progression of breast cancer.According to CIBERSORT analysis,there was a significant decrease in CD4^(+)T cell infiltration and a significant increase in M0 macrophage infiltration in breast cancer.Moreover,the key genes exhibited negative regulatory relationship with na ve B cells and memory B cells,and positive regulatory relationship with M0 macrophages and regulatory T cells,which indicated that key genes were closely related to breast cancer cell immunity.Con

关 键 词：表达数量性状位点定位 乳腺癌 孟德尔随机化 肿瘤免疫 生物标志物 

分 类 号：R734.2[医药卫生—肿瘤]