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 应用生物信息学的方法筛选参与星型胶质细胞瘤的预后生物标志物。方法 首先,下载GEO(gene expression omnibus,GEO)数据库中星型胶质细胞瘤的基因芯片数据,通过R语言将来自4个数据集的基因芯片数据进行合并,将合并后的194人来源的脑组织样本分为:星型胶质细胞瘤组和正常组。然后对原始基因芯片数据进行批次效应去除和标准化处理,并使用密度图和主成分分析监测处理前后的效果。利用R语言中的limma包对处理后的基因芯片数据进行差异表达分析,从而筛选得到星型胶质细胞瘤组和正常组中之间的差异表达基因(differentially expressed genes,DEGs)。接着对差异表达基因进行GO(gene ontology,GO)分析和KEGG(kyoto encyclopedia of genes and genomes,KEGG)分析,并对所有基因的表达矩阵进行GSEA(gene set enrichment analysis,GSEA)分析。通过STRING数据库构建差异表达基因的蛋白—蛋白相互作用网络(protein-protein interaction,PPI),通过Cytoscape中的cytoHubba插件筛选Hub基因。为了探索Hub基因在星型胶质细胞中的诊断价值和预后价值,我们下载TCGA(the cancer genome atlas,TCGA)数据库中的基因表达数据和临床预后资料,使用ROC曲线评价Hub基因的诊断价值,并对诊断价值较高的Hub基因进行COX回归,筛选HR值最有意义的基因进行总生存分析(overall survival,OS)。结果 通过limma包总共分析得到1 043个差异表达基因。GO分析结果表明差异表达基因主通过影响神经突触的功能而发挥作用。KEGG分析结果显示钙信号通路、cAMP信号通路、MAPK信号通路、PI3K-Akt信号通路、Rap1信号通路和Ras信号通路等通路等在星型胶质细胞瘤中发挥着重要的作用。GSEA富集分析结果主要富集于细胞因子-细胞因子受体相互作用、JAK-STAT信号通路、逆行内源性大麻素信号、神经活性配体-受体相互作用、GABA能突触和钙信号通路等通路。通过PPI网络总共分析得到ADCY1、ANXA1和PENK等20个Hub基因。通过对Hub基因的诊断价值和预后价值进行评价,发现SST在星型胶质细胞瘤既可作为诊断标志物,也可作为预后生物标志物。结论 我们通过生物信息学分析发现SST可作为星型胶质细胞的预后生物标志物,又预测了Rap1信号通路有可能成为星型胶质细胞分子机制中的新通路。

Objective To screen biomarkers involved in the prognosis of astrocytoma by bioinformatics. Methods Firstly,the gene chip data of astrocytoma in GEO database were downloaded. The gene chip data from four data sets were combined by R language. The combined 194 human brain samples were divided into astrocytoma group and normal group. Then,the original microarray data were processed by batch effect removal and standardization,and the effects before and after processing were monitored by density map and principal component analysis. The differentially expression genes (DEGs) between astrocytoma group and normal group were screened by using limma package of R language to analyze the differentially expression of the processed gene chip data. Then gene ontology(GO) analysis and Kyoto encyclopedia of genes and genes (KEGG) analysis were carried out for the differentially expressed genes,and gene set enrichment analysis (GSEA) was carried out for the expression matrix of all genes. The protein-protein interaction (PPI) network of differentially expressed genes was constructed by using string database,and the Hub gene was screened by using the cytohubba plug-in of Cytoscape. In order to explore the diagnostic value and prognostic value of Hub gene in astrocytes,we downloaded the gene expression data and clinical prognostic data in the Cancer Genome Atlas(TCGA) database,used ROC curve to evaluate the diagnostic value of hub gene,and Cox regression for Hub gene with high diagnostic value,and screen the most significant gene of HR value for overall survival(OS) analysis. Results A total of 1 043 differentially expressed genes were obtained by limma analysis. Go analysis showed that the differentially expressed genes played an important role by affecting the function of synapses. KEGG analysis showed that calcium signaling pathway,cAMP signaling pathway,MAPK signaling pathway,PI3K Akt signaling pathway,Rap1 signaling pathway and Ras signaling pathway played an important role in astrocytoma. The results of GSEA enrichment analysis were mainly enriched in cytokine cytokine receptor interaction,JAK-STAT signaling pathway,retrograde endogenous cannabinoid signaling,neuroactive ligand receptor interaction,GABAergic synapse and calcium signaling pathway. A total of 20 Hub genes such as ADCY1,ANXA1 and PINK were obtained by PPI network analysis. By evaluating the diagnostic and prognostic value of hub gene,we found that SST could be used as both a diagnostic marker and a prognostic biomarker in astrocytoma. Conclusion We found that SST could be used as a biomarker for the prognosis of astrocytes by bioinformatics analysis,and predicted that Rap1 signaling pathway may be a new pathway in the molecular mechanism of astrocytes.

       药源性心脏毒性是临床常见的药物不良反应，是药物研发和临床治疗需面临的严峻考验。对药源性心脏毒性的评价是目前研究的重点，基于其机制复杂多样、临床表现不一、影响因素多，早期评价具有困难。生物标志物是评价心脏毒性的重要指标之一，文章总结了目前已经报道的多种心脏毒性标志物及其潜在的生物标志物，希望能从中找到特异性强、敏感性高的标志物，以贡献于药物心脏安全性评价工作。

    As a common clinical adverse reaction，pharmacogenic cardiotoxicity is a severe challenge for drug development and clinical treatment．The evaluation of pharmacogenic cardiotoxicity is the focus of current research，and early evaluation is difficult with its complex and diverse mechanisms，varying clinical manifestations，and numerous influencing factors．Biomarker is an important index to evaluate cardiotoxicity．This article summarizes a variety of cardiotoxicity biomarkers and other potential biomarkers that have been reported so far，hoping to find  biomarkers with strong specificity and high sensitivity，so as tocontribute to the evaluation on cardiac safety of drugs．