中东呼吸综合征冠状病毒(MERS-CoV)的研究进展

中东呼吸综合征冠状病毒(Middle East Respiratory Syndrome-Coronavirus, MERS-CoV)是继SARS冠状病毒(SARS-CoV)之后发现的一种能引起人严重急性呼吸道疾病且具有高致死率的新型病毒。目前还没有有效的抗病毒治疗药物或疫苗。现已从主要流行的中东地区逐渐蔓延至多个国家,具有全球流行的潜在趋势,引起了世界各国的极大关注及众多的调查研究。本文主要对MERS-CoV的传播源及途径、致病机理和抗病毒药物及疫苗等的研究进展做一综述,以期对研制特异的抗病毒药物及疫苗和实施切实有效的预防及控制措施提供参考。     

心肌肥厚信号传导通路的研究进展

肥厚型心肌病是年轻人心源性猝死的首要原因,继发性左心室肥厚是心血管病发病率和死亡率增加的独立危险因素。尽管两者的发病机制不同,但存在共同的信号传导通路。参与心肌肥厚的信号传导通路包括：G蛋白异构体、低分子量GTPases(Ras,RhoA,Rac)、有丝分裂原激活蛋白激酶系统(MAPK)、蛋白激酶C、钙调磷酸酶(Calcineurin)、gp130-信号传导和转录激活子(gp130- STAT)、胰岛素样生长因子Ⅰ型受体(IGF I receptor)、成纤维生长因子(FGF),以及转化生长因子β(TGFβ)等。参与心肌肥厚重要的转录因子为：NFκB,MEF2,GATA4和NFAT。本文就上述的信号通路和转录因子在心肌肥厚中的作用及近几年的最新进展进行详细阐述。     

Rel／NF-kB信号传导通路与溃疡性结肠炎生物治疗策略的关系

目前认为溃疡性结肠炎(UC)是特定免疫功能障碍与遗传因素、环境因素相互作用的结果，其主要治疗药物是类固醇激素和抗炎药。但这些药物不能彻底治愈UC，并有副作用。NF-KB是一种与许多基因的转录启动有关的核因子。它是Rel／NF-kB信号传导通路的关键成员。通过靶基因的表达产物，NF-kB参与免疫反应、感染、炎症以及细胞调亡、细胞周期和分化的调控，故与人类多种疾病，如炎症、肿瘤的发病关系极为密切。如何通过调控该信号通路来控制相关疾病是当前研究的热点。现将Rel／NF-kB信号传导通路与UC的生物治疗策略作一综述。     

基于蛋白相互作用网络的帕金森病相关信号通路关键蛋白的筛选

目的 通过构建帕金森病(PD)信号通路蛋白相互作用网络,探讨PD相关信号通路网络关键蛋白.方法 通过文献检索、信号通路数据库、STRING数据库及cytoscape软件,构建PD相关信号通路蛋白相互作用网络.利用cytoscape软件拓扑分析功能寻找信号通路相互作用网络中的关键蛋白.结果 共纳入9条PD信号通路,包括P...     

结核分枝杆菌感染细胞的信号传导通路研究进展

结核病是由结核分枝杆菌（Mycobacterium tuberculosis，Mtb）经呼吸道、消化道或皮肤损伤等多种途径侵入人体而引起的多种组织器官传染病，但其致病的分子和细胞机制至今未完全明了。Mtb是一种典型的胞内致病菌，能在巨噬细胞内长期生存，并诱导细胞转化为朗罕细胞而形成结核结节。业已肯定，结核结节及结核肉芽肿是结核病最基本、最重要的病理特征，是组织细胞对Mtb感染的炎性反应性增殖。因此，在Mtb感染过程中，必然存在Mtb与宿主细胞的相互作用，并涉及相关信号传导通路。本文就近年有关Mtb感染宿主细胞的相关信号传导通路及其致病意义的研究进展作一综述。     

血管生长因子及其信号传导通路的研究进展

血管内皮生长因子在生理性和病理性血管生成中都起着重要作用,与血管内皮生长因子相应受体结合后,通过特定的信号传导途径刺激内皮细胞的增殖、迁移,从而促进血管新生。研究血管内皮生长因子与相应受体结合及其相关的下游信号通路,进一步探讨血管新生的可能机制,对治疗恶性肿瘤、缺血性疾病、创伤恢复等意义重大。现对血管内皮生长因子及其信号传导通路的研究进展做一综述。     

肝癌分子分型和相关信号通路的研究进展

肝细胞癌是一种原发于肝脏的恶性肿瘤,占原发性肝癌的85%~90%。随着高通量检测下一代测序(NGS)检测技术的不断发展,了解肝癌的分子分型和不同信号通路的调控机制,并针对靶点进行分子靶向治疗和免疫治疗,是目前肝癌领域的一大研究热点。该文综述其研究现状,归纳了肝癌发病中主要作用的信号通路,以期为肝癌的精准治疗与研究带来新的思路。     

STING信号通路参与NAFLD的研究进展

非酒精性脂肪肝疾病(non-alcoholic fatty liver disease,NAFLD)是全球范围内的主要慢性肝病之一,严重威胁人类健康,已成为一个重大的公共卫生问题.免疫机制在NAFLD的发生发展中起着关键作用.干扰素基因刺激因子(interferon gene stimulating factor,ST...     

利巴韦林联合IFN治疗冠状病毒感染的研究进展

2019年底以来新型冠状病毒肺炎(新冠肺炎)席卷全球,病毒学分类委员会将新型冠状病毒命名为SARSCoV-2。目前对SARS-CoV-2知之甚少,尚未研发出针对该疾病的特效药物。但其与严重急性呼吸综合征冠状病毒、中东呼吸综合征冠状病毒同为β属冠状病毒,具有核苷酸同源性。既往严重急性呼吸综合征和中东呼吸综合征相关研究提示利巴韦林(ribavirin, RBV)联合IFN抗病毒治疗有效,为新冠肺炎的治疗提供了新的方向,但联合治疗的效果及安全性有待进一步临床试验证实。本文回顾总结了RBV联合IFN治疗冠状病毒感染的研究进展,以期为新冠肺炎的治疗提供参考。     

Identification of key biomarkers and functional pathways in osteosarcomas with lung metastasis: Evidence from bioinformatics analysis

Background:In osteosarcoma, the lung is the most common metastatic organ. Intensive work has been made to illuminate the pathogeny, but the specific metastatic mechanism remains unclear. Thus, we conducted the study to seek to find the key genes and critical functional pathways associated with progression and treatment in lung metastasis originating from osteosarcoma.Methods:Two independent datasets (GSE14359 and GSE85537) were screened out from the Gene Expression Omnibus (GEO) database and the overlapping differentially expressed genes (DEGs) were identified using GEO2R online platform. Subsequently, the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were conducted using DAVID. Meanwhile, the protein-protein interaction (PPI) network constructed by STRING was visualized using Cytoscape. Afterwards, the key module and hub genes were extracted from the PPI network using the MCODE and cytoHubba plugin. Moreover, the raw data obtained from GSE73166 and GSE21257 were applied to verify the expression differences and conduct the survival analyses of hub genes, respectively. Finally, the interaction network of miRNAs and hub genes constructed by ENCORI was visualized using Cytoscape.Results:A total of 364 DEGs were identified, comprising 96 downregulated genes and 268 upregulated genes, which were mainly involved in cancer-associated pathways, adherens junction, ECM-receptor interaction, focal adhesion, MAPK signaling pathway. Subsequently, 10 hub genes were obtained and survival analysis demonstrated SKP2 and ASPM were closely related to poor prognosis of patients with osteosarcoma. Finally, hsa-miR-340-5p, has-miR-495-3p, and hsa-miR-96-5p were found to be most closely associated with these hub genes according to the interaction network of miRNAs and hub genes.Conclusion:The key genes and functional pathways identified in the study may contribute to understanding the molecular mechanisms involved in the carcinogenesis and progression of lung metastasis originating from osteosarcoma, and provide potential diagnostic and therapeutic targets.     

Identification of candidate biomarkers correlated with the pathogenesis and prognosis of breast cancer via integrated bioinformatics analysis

Background:This study was carried out to identify potential key genes associated with the pathogenesis and prognosis of breast cancer (BC).Methods:Seven GEO datasets ({"type":"entrez-geo","attrs":{"text":"GSE24124","term_id":"24124"}}GSE24124, {"type":"entrez-geo","attrs":{"text":"GSE32641","term_id":"32641"}}GSE32641, {"type":"entrez-geo","attrs":{"text":"GSE36295","term_id":"36295"}}GSE36295, {"type":"entrez-geo","attrs":{"text":"GSE42568","term_id":"42568"}}GSE42568, {"type":"entrez-geo","attrs":{"text":"GSE53752","term_id":"53752"}}GSE53752, {"type":"entrez-geo","attrs":{"text":"GSE70947","term_id":"70947"}}GSE70947, {"type":"entrez-geo","attrs":{"text":"GSE109169","term_id":"109169"}}GSE109169) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between BC and normal breast tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Hub genes related to the pathogenesis and prognosis of BC were verified by employing protein–protein interaction (PPI) network.Results:Ten hub genes with high degree were identified, including CDK1, CDC20, CCNA2, CCNB1, CCNB2, BUB1, BUB1B, CDCA8, KIF11, and TOP2A. Lastly, the Kaplan–Meier plotter (KM plotter) online database demonstrated that higher expression levels of these genes were related to lower overall survival. Experimental validation showed that all 10 hub genes had the same expression trend as predicted.Conclusion:The findings of this research would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of BC, which could be used as a new biomarker for diagnosis and to guide the combination medicine of BC.     

Integrated bioinformatics analysis reveals CDK1 and PLK1 as potential therapeutic targets of lung adenocarcinoma

This study is to identify potential biomarkers and therapeutic targets for lung adenocarcinoma (LUAD).{"type":"entrez-geo","attrs":{"text":"GSE6044","term_id":"6044"}}GSE6044 and {"type":"entrez-geo","attrs":{"text":"GSE118370","term_id":"118370"}}GSE118370 raw data from the Gene Expression Omnibus database were normalized with Robust Multichip Average. After merging these two datasets, the combat function of sva packages was used to eliminate batch effects. Then, limma packages were used to filtrate differentially expressed genes. We constructed protein–protein interaction relationships using STRING database and hub genes were identified based on connectivity degrees. The cBioportal database was used to explore the alterations of the hub genes. The promoter methylation of cyclin dependent kinase 1 (CDK1) and polo-like Kinase 1 (PLK1) and their association with tumor immune infiltration in patients with LUAD were investigated using DiseaseMeth version 2.0 and TIMER databases. The Cancer Genome Atlas-LUAD dataset was used to perform gene set enrichment analysis.We identified 10 hub genes, which were upregulated in LUAD, among which 8 were successfully verified in the Cancer Genome Atlas and Oncomine databases. Kaplan–Meier analysis indicated that the expressions of CDK1 and PLK1 in LUAD patients were associated with overall survival and disease-free survival. The methylation levels in the promoter regions of these 2 genes in LUAD patients were lower than those in normal lung tissues. Their expressions in LUAD were associated with tumor stages and relative abundance of tumor infiltrating immune cells, such as B cells, CD4+ T cells, and macrophages. Moreover, cell cycle, DNA replication, homologous recombination, mismatch repair, P53 signaling pathway, and small cell lung cancer signaling were significantly enriched in CDK1 and PLK1 high expression phenotype.CDK1 and PLK1 may be used as potential biomarkers and therapeutic targets for LUAD.     

活动性肺结核患者与潜伏感染者差异表达基因的生物信息学分析

目的寻找活动性肺结核患者与潜伏感染者免疫功能差异的重要分子。方法收集活动性肺结核患者和潜伏感染者PBMCs进行转录组测序,分析数据获得差异表达基因,对差异表达基因使用软件MeV进行聚类分析,用DAVID数据库进行GO分析,用STRING数据库进行蛋白相互作用网络分析,用Cytocapase软件进行KEGG分析和蛋白质复合物分析。结果共获得差异表达基因98个,其中上调基因67个,下调基因31个;GO分析生物进程富集的词条是“免疫反应”、“天然免疫反应”和“中性粒细胞趋化”;KEGG分析结果显示富集词条是“自然杀伤细胞介导的细胞毒作用”、“抗原处理和递呈”和“IL17信号通路”等信号通路,其中IFNG、ITGAM、MMP1和FOS基因连接多个信号通路;构建蛋白相互作用网络,筛选到聚集程度高的分子ELANE、ITGAM、MMP9和ARG1;而蛋白复合物分析显示由上调基因组成的复合物1和复合物2、由下调基因组成的复合物3。结论连接多个信号通路或者聚集程度高的重要分子和大分子复合物可能在活动性肺结核患者与潜伏感染者免疫功能差异具有重要的作用,有待我们进一步的实验验证及功能研究。     

Identification of potential biomarkers of peripheral blood mononuclear cell in hepatocellular carcinoma using bioinformatic analysis: A protocol for systematic review and meta-analysis

Background:Hepatocellular carcinoma (HCC) is the cause of an overwhelming number of cancer-related deaths across the world. Developing precise and noninvasive biomarkers is critical for diagnosing HCC. Our research was designed to explore potentially useful biomarkers of host peripheral blood mononuclear cell (PBMC) in HCC by integrating comprehensive bioinformatic analysis.Methods:Gene expression data of PBMC in both healthy individuals and patients with HCC were extracted from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied to annotate the function of DEGs. Protein-protein interaction analysis was performed to screen the hub genes from DEGs. cBioportal database analysis was performed to assess the prognostic significance of hub genes. The Cancer Cell Line Encyclopedia (CCLE) and The Human Protein Atlas (HPA) database analyses were performed to confirm the expression levels of the hub genes in HCC cells and tissue.Results:A total of 95 DEGs were screened. Results of the GO analysis revealed that DEGs were primarily involved in platelet degranulation, cytoplasm, and protein binding. Results of the KEGG analysis indicated that DEGs were primarily enriched in focal adhesion. Five genes, namely, myosin light chain kinase (MYLK), interleukin 1 beta (IL1B), phospholipase D1 (PLD1), cortactin (CTTN), and moesin (MSN), were identified as hub genes. A search in the CCLE and HPA database showed that the expression levels of these hub genes were remarkably increased in the HCC samples. Survival analysis revealed that the overexpression of MYLK, IL1B, and PLD1 may have a significant effect on HCC survival. The aberrant high expression levels of MYLK, IL1B, and PLD1 strongly indicated worse prognosis in patients with HCC.Conclusions:The identified hub genes may be closely linked with HCC tumorigenicity and may act as potentially useful biomarkers for the prognostic prediction of HCC in PBMC samples.     

基因组水平筛选冠状动脉病变部位参与急性心肌梗死急性期的信号通路

目的利用基因芯片技术筛选冠状动脉病变部位参与急性心肌梗死急性期过程的信号通路,探讨急性冠脉综合征斑块破裂病变的发生机制。方法收集急性心肌梗死患者急性期和冠状动脉造影结果正常者的冠状动脉血,用人类基因组U133A寡核苷酸芯片筛选差异表达基因,然后采用DAVID功能注释生物信息学芯片分析系统对2倍差异表达基因进行基因富集分析,并用定量多聚酶连反应（RT-qPCR）验证化学因子信号通路部分筛选基因的表达。结果与冠状动脉造影正常者相比,急性心肌梗死患者在急性期的2倍上调基因有2897个,2倍下调基因有1974个。GO信号通路富集分析显示96个信号通路参与急性心肌梗死急性期过程（BenjaminiP〉0.01）。KEGG信号通路富集分析显示6个信号通路参与急性心肌梗死急性期过程（BenjaminiP〉0.01）。选择化学因子信号通路6个上下游基因进行验证,与芯片结果高度一致。其中CXCR1、CXCR2、Src、Raf和ERK1/2基因在急性期表达显著增高,与对照组比较,差异有统计学意义（P〈0.001）,而PI3K表达也有增高的趋势。结论在急性心肌梗死急性期过程中有许多信号通路参与,其中Chemokine信号通路与其发病机制密切相关。     

Microarray analysis of hub genes and pathways in damaged cartilage tissues of knee

The aim of this study was to identify genes and functional pathways associated with damaged cartilage tissues of knee using microarray analysis.The gene expression profile {"type":"entrez-geo","attrs":{"text":"GSE129147","term_id":"129147"}}GSE129147 including including 10 knee cartilage tissues from damaged side and 10 knee nonweight-bearing healthy cartilage was downloaded and bioinformatics analysis was made.A total of 182 differentially-expressed genes including 123 up-regulated and 59 down-regulated genes were identified from the {"type":"entrez-geo","attrs":{"text":"GSE129147","term_id":"129147"}}GSE129147 dataset. Gene ontology and pathway enrichment analysis confirmed that extracellular matrix organization, collagen catabolic process, antigen processing and presentation of peptide or polysaccharide antigen, and endocytic vesicle membrane were strongly associated with cartilage injury. Furthermore, 10 hub differentially-expressed genes with a higher connectivity degree in protein–protein interactions network were found such as POSTN, FBN1, LOX, insulin-like growth factor binding proteins3, C3AR1, MMP2, ITGAM, CDKN2A, COL1A1, COL5A1.These hub genes and pathways provide a new perspective for revealing the potential pathological mechanisms and therapy strategy of cartilage injury.     

基于转录组学数据分析痛风合并动脉粥样硬化的发病机制

目的]采用GEO数据库探讨痛风合并动脉粥样硬化(As)的共同发病机制。 [方法]从GEO数据库中下载痛风(GSE160170)和As(GSE100927)的基因表达矩阵,分析痛风和As的差异表达基因(DEG),并分别进行富集分析。在分析共同差异表达基因(CDEG)后,对其进行功能富集分析、蛋白质-蛋白质相互作用(PPI)网络分析和核心基因(HG)鉴定,并对HG进行共表达分析及验证。最后,分析痛风、As的免疫细胞浸润,同时探索HG与浸润免疫细胞(IIC)之间的相关性。 [结果]GSE160170数据集中获得了1 606个DEG,GSE100927数据集中获得了481个DEG。其中的22个CDEG富集分析结果表明,细胞因子的调控作用可能是痛风合并As的关键机制。通过使用CytoHubba插件识别了6个HG(CCR2、CD2、FCGR3A、FGD3、IL10RA、SIGLEC1),结果显示这些HG尚且可靠。共表达网络显示这些HG可以影响肿瘤坏死因子超家族细胞因子产生的调节作用。免疫细胞浸润分析表明,痛风中的NK细胞表达显著增加,且与CCR2基因呈显著相关;As中的活化肥大细胞表达显著增加,且与CD2基因呈显著相关。 [结论]肿瘤坏死因子超家族细胞因子产生的调节作用很可能是痛风合并As的核心因素。