目的 通过公共数据库筛选急性肺损伤（ALI）及急性呼吸窘迫综合征（ARDS）相关分子标志物,并探索其临床意义。方法 利用基因表达综合数据库（GEO）中有关ALI/ARDS基因表达芯片研究的两个数据集GSE76293和GSE10474,通过STRING网站和Cytoscape软件对差异基因进行蛋白互作网络分析并筛选ALI/ARDS相关关键基因。采用A549细胞构建ALI模型,并通过转录组测序验证关键基因在细胞中的表达差异情况。结果 2个GEO数据集中共筛选出共同上调基因27个,共同下调基因26个。主要参与抗原加工和外源抗原递呈、免疫受体活性调节、内质网膜构成等生物学功能,且与抗原加工、细胞分化等信号通路有关。蛋白互作网络分析共筛选出10个ALI/ARDS相关关键基因,分别为CD4、HLA-DQB1、CD74、HLA-DRA、FCGR2B、TOR1A、RELA、NME8、RNF19B、RHOB。细胞转录组测序结果显示,关键基因的上调或下调特征及表达差异情况与GEO数据集分析结果一致。结论 CD4等关键基因可能参与ALI/ARDS发生、发展的生物学过程,是ALI/ARDS临床诊断及预后预测的潜在个体化分子标志物。

Objective To identify molecular biomarkers associated with acute lung injury（ALI）/ acute respiratory distress syndrome（ARDS）and to explore their clinical significance with public databases. Methods Two datasets GSE76293 and GSE10474 in Gene Expression Omnibus（GEO）database for ALI/ARDS gene expression chip study were used to screen genes with significant differences in both datasets．The protein-protein interaction（PPI）analysis of co-expression genes was performed based on the STRING website and Cytoscape software,and then key genes related to ALI/ARDS were identified with cytoHubba method．The ALI model was constructed using A549 cells cultured in vitro,and the expression differences of key genes in the cells were verified by RNA sequencing. Results A total of 27 up-regulated genes and 26 down-regulated genes were screened in both the two GEO datasets with Venn Diagramm．These co-expression genes were mainly involved in biological functions such as antigen processing and presentation of exogenous peptide antigen,immune receptor activity,integral component of lumenal side of endoplasmic reticulum membrane and were related to signal pathways such as antigen processing and cell differentiation．A total of 10 key genes（CD4,HLA-DQB1,CD74,HLA-DRA,FCGR2B,TOR1A,RELA,NME8,RNF19B,RHOB）related to ALI/ARDS were identified． The results of cell RNA sequencing showed that the up-regulated or down-regulated characteristics and expression differences of key genes were consistent with the results of GEO datasets. Conclusions Several key genes identified in this study may be involved in the biological process of ALI/ARDS development,and may be potential individualized molecular markers for clinical diagnosis and prognosis prediction of ALI/ARDS．

目的 使用TCGA数据库,探索DNA甲基化位点对肺腺癌的预后影响。方法 使用TCGA数据库,获取肺腺癌病人癌和癌旁组织甲基化表达数据、基因表达数据及临床数据;将人群分为探索组和验证组,使用LASSO在探索人群中筛选对肺腺癌预后有影响的甲基化位点;受试者工作特征曲线用于评估甲基化位点预测效果,并进一步在验证人群中验证。结果 在TCGA数据库中筛选出158个癌和癌旁组织差异表达且与所在基因mRNA表达显著相关的甲基化位点,经LASSO回归分析,cg19378330与肺腺癌预后相关。甲基化位点水平高于中位数的患者,归入高风险组,甲基化位点水平低于中位数的为低风险组。结果发现与低风险组相比,高风险组的死亡风险比低风险组增加了38%(OR=1.38,95% CI=1.16～2.69)。在探索阶段人群中其曲线下面积为0.80(95% CI=0.73～0.88),灵敏度为86.2%。验证人群中也表现出类似结果。结论 甲基化位点cg19378330与肺腺癌具有较显著的关联性,且可以对肺腺癌的风险进行有效的预测。

Objective Using the TCGA database to explore the prognostic effects of DNA methylation sites on lung adenocarcinoma. Methods TCGA database was used to collecting DNA methylation data, gene expression data and clinical data of lung adenocarcinoma patients. The population were divided into the exploratory group and the validation group. The LASSO regression analysis was used to screen the methylation sites associated with the prognosis of lung adenocarcinoma in the exploratory group. Receiver operating characteristic curve was used to evaluate the prediction effect of the model, and further verified in the validation population. Results A total of 158 methylation sites with differential expression and significant correlation with the mRNA expression of the corresponding gene were screened from the TCGA database. With LASSO regression analysis, the DNA methylation sites associated with prognosis of lung adenocarcinoma were cg19378330. Those patients with levels above the median methylation site were assigned to the high-risk group, while those with levels below the median methylation site were assigned to the low-risk group. Patients' death risk in the high-risk group were 38% higher than those in the low-risk group (OR=1.38, 95%CI=1.16-2.69). The area under the curve was 0.80 (95%CI=0.73-0.88) and the sensitivity was 86.2% in the exploratory stage population.Similar results were seen in the validation population. Conclusions The DNA methylation site cg19378330 was significantly associated withthe prognosisof lung adenocarcinoma, and could effectively predict the risk of lung adenocarcinoma.

目的 分析ABCC2基因表达水平与肺腺癌预后之间的关联性,并对其影响机制进行初步探索。 方法 采用TCGA数据库和HPA数据库对肺腺癌病人癌组织和癌旁组织基因表达数据进行差异性分析,单因素及多因素COX回归评估ABCC2与肺腺癌预后之间的关联性,GSEA用于探讨与ABCC2显著关联的信号通路。 结果 ABCC2在肺腺癌肿瘤组织中存在过表达现象,Kaplan-Meier生存分析曲线结果显示ABCC2基因过表达使肺腺癌病人的死亡风险显著升高(HR=1.46,95%CI=1.09~1.95; P=0.010)。单因素及多因素COX回归结果显示ABCC2基因过表达是肺腺癌病人不良预后的独立危险因素。GSEA结果显示ABCC2可能通过调节药物代谢从而对肺腺癌的发展进行调控。 结论 ABCC2基因过表达使肺腺癌病人的死亡风险显著升高,ABCC2可能是肺腺癌不良预后的潜在分子生物标志物。

Objective To estimate the association between ABCC2 mRNA expression and the prognosis of lung adenocarcinoma and explore the potential influencing mechanism.Methods Difference analysis was used to evaluate the gene expression in tumor tissues and adjacent normal tissues based on The Cancer Genome Atlas database and Human Protein Atlas database.Multivariate COX regression and Kaplan-Meier analysis were performed to evaluate the association between ABCC2 gene expression and the prognosis of lung adenocarcinoma.Gene-set enrichment analysis (GSEA) was performed to screen differentially enriched pathways associated with the ABCC2 high expression phenotype.Results ABCC2 was overexpressed in lung adenocarcinoma tumor tissues compared with adjacent normal tissues.Kaplan-Meier survival analysis showed a significant relationship between ABCC2 mRNA expression and lung adenocarcinoma prognosis (HR=1.16,95% CI=1.09-1.95; P=0.010).Univariate and multivariate Cox regression analysis showed that ABCC2 mRNA expression was an independent risk factor affecting the survival of patients with lung adenocarcinoma.The results of GSEA suggested that ABCC2 may influence the development of lung adenocarcinoma by regulating the metabolism of targeted drug the treatment.Conclusions ABCC2 overexpression can significantly increase the risk of death in patients with lung adenocarcinoma,ABCC2 may be a potential molecular marker for poor prognosis in lung adenocarcinoma.