基于多平台数据识别胰腺导管腺癌预后相关肿瘤微环境基因

Identification of pancreatic duct adenocarcinoma prognostic-related tumor microenvironment genes using multi-platforin data

目的 探索与胰腺导管腺癌(PDAC)相关的肿瘤微环境基因表达模块,识别影响患者预后的生物学标志物和潜在的免疫治疗靶点。方法 筛选收集来自肿瘤基因组图谱(TCGA)数据库的1个包含142例PDAC患者数据集和基因表达综合(GEO)数据库的2个包含168例PDAC患者微阵列数据集(GSE2150、GSE62452)的基因表达谱数据,运用xCell网络工具对PDAC基因表达数据进行细胞类型富集分析。根据细胞富集评分中位数将TCGA的142例患者分为高分、低分2组,通过单因素生存分析确定有预后价值的细胞类型并使用GEO的数据集验证。再根据细胞类型进行基因差异表达分析及单因素生存分析确定与预后相关的差异表达基因(DEGs),并对DEGs进行功能富集分析及蛋白质-蛋白质相互作用(PPI)网络分析。同时使用GEO数据集对TCGA数据集的预后相关DEGs进行验证。最后在TISIDB数据库检索TCGA与GEO数据库的共同DEGs,并分析其与免疫系统的相关性。结果 细胞类型富集评分显示,Th1细胞和角质形成细胞在TCGA和GEO数据集中具有相同的预后价值,其高分组患者的总生存率显著低于低分组,差异均有统计学意义(P值均<0.05)。鉴定出216个预后相关DEGs,对其功能富集结果显示21个生物学过程条目中有9个与免疫过程密切相关,5条京都基因与基因组百科全书(KEGG)通路中有4条与免疫过程密切相关。通过PPI网络分析,CCR7、CD27、CD5、CXCL13、ZAP70、MS4A1和CCL19被鉴定为可能与PDAC密切相关的中枢基因。通过对GEO数据集的验证,共有15个DEGs在GEO和TCGA数据集中具有相似的预后价值。检索TISIDB数据库上述15个基因结果显示,GIMAP7与PDAC的免疫过程密切相关。结论 鉴定了216个与PDAC预后相关的肿瘤微环境基因及其7个中枢基因,并提供了CCR7、CCL19、CD27、CXCL13和GIMAP7 5个新的PDAC免疫治疗潜在靶点。

Objective To explore the tumor microenvironment(TME)module associated with pancreatic ductal adenocarcinoma(PDAC)and identify prognostic biomarkers and potential immunotherapeutic targets.Methods The genetic expression profile data were collected and selected from a dataset of 142 PDAC patients in The Cancer Genome Altas(TCGA)database and 2 niicroarray datasets(GSE2150,GSE62452)of 168 PDAC patients in Gene Expression Omnibus(GEO)database,and the cell type enrichment analysis of PDAC gene expression data was analyzed by xCell network tool.According to the median cell enrichment score,142 patients from TCGA were divided into high score group and low score group,and the cell types with prognostic value were determined by univariate survival analysis and validated by GEO datasets.According to the cell type,the differential expression gene analysis and univariate survival analysis were performed to determine the prognosis related differential expression genes(DEGs),and the prognostic DEGs were analyzed by function enrichment analysis and protein-protein interaction(PPI)network analysis.At the same time,GEO dataset was used to verify the prognosis related DEGs of TCGA datasets.Finally,TISIDB database was searched for the common DEGs of TCGA and GEO database,and its correlation with immune system was analyzed.Results Cell type enrichment analysis showed that Thl cell and keratinocyte had the same prognostic value in both TCGA and GEO dataset;the overall survival rate of patients with high score was lower than that of those with low score,and the differences were statistically significant(all P values<0.05).216 prognosis related DEGs were identified,and the results of functional enrichment showed that 9 of the 21 biological process items were closely related to the immune process,and 4 of the 5 KEGG(Kyoto Encyclopedia Of Genes and Genomes)pathways were closely related to the immune process.Through PPI network analysis,CCR7,CD27,CD5,CXCL13,ZAP70,MS4A1 and CCL19 were proved to be possibly closely associated with central genes.Through the validation of GEO datasets,there were 15 DEGs with similar prognostic value in GEO and TCGA datasets,which was searched in TISIDB dataset,and the result showed that GIMAP7 was closely related with the immune process of PDAC.Conclusions A group of 216 TME genes and 7 central genes related to the prognosis of PDAC were identified,and 5 potential targets for immunotherapy of PDAC were provided,including CCR7,CCL19,CD27,CXCL13 and GIMAP7.