微RNA调节肺癌转移的分子机制

微RNA(microRNA,miRNA)是一类长约22 nt的非编码小分子RNA,在转录后水平上通过基因沉默调节靶基因的活性。近年来,miRNA与肿瘤转移关系的研究成为探讨肿瘤转移调控机制的热点。越来越多的研究提示miRNA在肿瘤转移过程中发挥着重要作用。肺癌转移是影响肺癌预后的关键,是一种复杂的多因素、多步骤、多基因参与调控的过程。研究miRNA对肺癌转移的作用有助于我们找到阻断肺癌转移的靶点。本文就miRNA和肺癌转移关系的研究进展作一综述。     

MicroRNA与肺癌发生、诊断及治疗

微小RNA(miRNAs)是一大类小的非编码RNA,它通过与靶mRNA 3′非翻译区部分互补配对来调节特定基因的表达。近来研究表明,miRNA可作为癌基因或抑癌基因在肺癌发生发展过程中起重要作用。比较癌组织和非癌组织中miRNA表达谱的差异可筛选出部分miRNA分子作为肺癌诊断和预后判断的潜在生物标记。调节具有致癌或抑癌功能的miRNA表达可能成为肺癌治疗新方法,而结合传统放化疗及其敏感性miRNA标志也为肺癌治疗研究提供了新的策略。该文对miRNA在肺癌发生与发展、基因诊断和治疗中的作用做一综述。     

数据挖掘探究肝-肾-肺纤维化的关键基因

当前用于纤维化治疗的方法很少且疗效有限,为进一步了解纤维化的消退机制以发现潜在的治疗靶点。从Gene Expression Omnibus(GEO)数据库中选取了三个具有代表性的小鼠肝、肾、肺纤维化样本的mRNA数据集,使用GEO2R工具和Venn分析识别了差异表达基因(Differentially Expressed Genes, DEGs)。通过Webgestalt在线工具对DEGs进行基因功能富集。蛋白质-蛋白质相互作用(Protein-Protein Interactions, PPI)网络是由STRING数据库生成的。然后利用CytoHubba插件探索了关键基因,分别选取了三器官共有DEG和肝特异性DEG中MCC (Maximal Clique Centrality)得分最高的前10个作为关键基因。研究中整合分析了基于小鼠模型的肝-肾-肺纤维化的数据集,GSE36066和GSE97546用于第一轮的DEG分析,由于研究除了探究三种器官纤维化共有差异基因,也进一步探究了肝纤维化特有关键基因,所以引入另外一个肝纤维化数据集GSE55747用于验证分析。结果识别出58个肝肺肾纤维化...     

基于生物信息学方法识别非小细胞肺癌(NSCLC)潜在治疗靶基因

本研究运用生物信息学方法识别非吸烟女性非小细胞肺癌(NSCLC)潜在的靶基因,并从分子水平探索其潜在的发病机制。从GEO数据库下载非吸烟女性非小细胞肺癌相关基因芯片数据集,经癌症组和癌旁对照组差异表达基因识别,并利用R软件对差异基因进行层次聚类分析,DAVID进行基因本体(gene ontology)和KEGG通路富集分析,STRING和Cytoscape软件构建蛋白-蛋白交互(PPI)网络,以及运用PASTAA分析,识别NSCLC相关转录因子,构建转录因子-基因共表达网络。结果表明,185个基因在NSCLC中差异表达,其中40个上调,145个下调;通过PASTAA分析识别出5个NSCLC基因相关转录因子。差异基因与胶原分解代谢过程、炎症反应的正调控等生物过程密切相关,基因的产物主要参与蛋白质细胞外基质、胶原三聚体等细胞组分,且主要发挥调节金属内肽酶活性、肝素结合和调节受体活性等分子功能;KEGG通路富集分析表明差异基因显著富集到胞外基质-受体信号通路、粘着斑信号通路、PPAR信号通和PI3K-Akt信号通路等,与非小细胞肺癌的发生发展密切相关。通过生物信息学方法,最终筛选到4个NSCLC关键基因:IL6、MMP1、COL1A1、CD36,其可能是非吸烟女性NSCLC潜在的治疗靶点。     

家族性高胆固醇血症HDL-miRNAs调节血单核细胞功能机制

本研究通过生物信息学方法分析家族性高胆固醇血症患者外周血单核细胞差异表达基因、HDL载体差异表达miRNA及其生物学功能,研究差异HDL-miRNA与单核细胞差异基因的相关性,探讨HDL-miRNA调控外周血单核细胞功能机制,寻找动脉粥样硬化防治新靶点。运用R语言分析GEO数据库共享平台家族性高胆固醇血症外周血单核细胞基因及HDL-miRNA探针芯片得到差异基因及差异miRNA,利用miRwalk2. 0预测miRNA靶基因,并利用STRING进行蛋白互作分析,构建差异miRNA与差异基因之间的调控网络。运用GO及KEGG分析研究基因功能。利用GEO数据(GSE6054)筛选出834个差异表达基因,利用GEO数据(GSE25108)筛选出HDL上差异miRNA28个。交叉匹配得到由19个差异miRNA和56个差异基因组配对的74对miRNA-靶基因。GO富集分析56个差异基因主要富集于肾上腺素受体信号等分子功能。KEGG分析56个差异基因主要富集于造血谱系通路上。家族性高胆固醇血症差异HDL-miRNA与外周血单核细胞差异mRNA具有相关性,HDL-miRNA有通过调控血单核细胞功能的可能性,可能参与高胆固醇血症导致动脉粥样硬化过程。     

基于生物信息学分析寻找胰腺癌新的诊断和治疗靶点

胰腺癌作为一种消化系统高度恶性的肿瘤性疾病,其发生和进展的分子机制仍不确定。为寻找与胰腺癌发生和进展有关的新的有效治疗靶点和潜在的生物标志物。利用GEO数据库中的GEO2R在线工具对胰腺癌组织和正常对照组织的基因表达进行差异分析并对差异表达基因(DEGs)进行GO功能和KEGG通路富集分析。然后通过GEPIA数据库中胰腺癌的转录数据对候选基因的表达进行验证。Kaplan-Meier法分析各候选基因的预后价值。利用starBase数据库中的7个预测程序对候选基因上游潜在的miRNAs进行预测。此外,还使用miRNet和starBase预测了hsa-miR-20b-5p的上游lncRNAs并利用lncATLAS数据库对潜在的lncRNAs进行亚细胞定位。在本研究中,我们发现胰腺癌组织中LAMA3基因的转录水平明显高于健康对照组织。同时,LAMA3的过表达与胰腺癌患者较差的临床预后相关。随后,预测了21个可能靶向LAMA3的潜在上游miRNAs。在预测到的miRNA-mRNA调控轴中,has-miR-20b-5p-LAMA3轴在胰腺癌的发生和进展中具有较高的潜力。进一步研究发现,FGD5-AS1潜在的抑制has-miR-20b-5p-LAMA3调控轴的作用可能能够在胰腺癌中作为诊断和治疗的有效靶点。FGD5-AS1-has-miR-20b-5p-LAMA3调控网络在胰腺癌发生和发展中的具有关键作用,可作为胰腺癌临床诊断和治疗的潜在靶点和生物标志物。     

三阴性乳腺癌相关miRNA筛选及其靶基因的生物信息学分析

应用生物信息学方法筛选并分析三阴性乳腺癌（triple-negative breast cancer,TNBC）相关miRNA及其靶基因,为TNBC的研究提供潜在的分子靶点。采用GEO2R分析TNBC相关miRNA芯片数据集,筛选差异表达倍数最大的5个上调和5个下调miRNA。miRWalk、TargetScan和miRDB预测靶基因并进行Veen分析取交集。利用DAVID对靶基因进行GO富集分析和KEGG通路分析。利用STRING数据库构建蛋白互作网络,并结合Cytoscape构建miRNA-靶基因调控网络,从而筛选出关键的miRNA及其关键靶基因。利用GEPIA2数据库对靶基因进行生存分析。GEO2R筛选出486个差异miRNA,上调和下调的miRNA分别有298个和188个。对差异倍数最大的5个上调和5个下调miRNA的靶基因进行富集分析显示,靶基因主要参与ErbB信号通路、癌症中转录调控紊乱和cGMP-PKG信号通路等。miRNA-靶基因调控网络显示,表达上调的关键miRNA为miR-611,其关键靶基因为CDC27、UBE2D2、UBR1、SPSB1、HERC2和RLIM;表达下调的关键miRNA为miR-1205,其关键靶基因为WSB1、FBXL8、UBE2W、PTPN11、ARF6、DNAJC6和COPS2。生存分析表明,UBR1（P=0.007 2）和PTPN11（P=0.029）表达上调可显著降低TNBC患者的整体生存率。经筛选获得的关键miRNA及其关键靶基因可作为潜在分子标记物用于TNBC的早期诊断、治疗靶点选择和预后判断,并为后续的研究提供参考依据。     

基于加权基因共表达网络分析探索肝纤维化关键基因

本研究旨在基于加权基因共表达网络分析(weighted gene co-expression network analysis, WGCNA)筛选肝纤维化发生及发展过程中的关键基因及潜在机制。从GEO数据库获得肝纤维化患者全基因组芯片数据(GSE84044),采用WGCNA发掘与肝纤维化发生发展相关的重要模块及关键基因,通过GO注释和KEGG富集揭示潜在的关键机制。对肝纤维化患者基因组芯片数据进行WGCNA分析,22 876个基因被分为8个模块,其中有两个模块与肝纤维化相关性较大,GO注释和KEGG富集的结果表明,这两个模块主要与细胞外基质和胶原蛋白的产生有关。分析WGCNA关键基因在肝纤维化4个时期的表达差异,结果发现,LIPC、DCN、LUM、COL1A1等10个基因呈现出明显变化趋势。本研究采用WGCNA对肝纤维化患者的基因芯片进行分析,挖掘肝纤维化发生发展过程中的重要基因,为肝纤维化预防与治疗提供生物标志物和潜在靶点的新筛选方向。     

基于GEO数据库的肝癌相关基因的筛选及验证

肝细胞癌(hepatocellular carcinoma,HCC)是中国高发的恶性肿瘤之一,识别肝细胞癌发生发展相关基因,对于深入研究肝癌发病机制和开发诊疗靶点均具有重要意义.本研究利用GEO2R工具从基因表达汇编数据库(Gene Expression Omnibus Database,GEO)筛选5个数据集中共有的差异表达基因作为潜在的肝癌相关基因.利用Metascape网站,对差异表达基因进行功能富集及信号通路分析.结合GEPIA(Gene Expres-sion Profiling Interaction Analysis)网站筛选具有临床意义的基因.利用荧光定量PCR技术验证与肝癌预后相关的差异表达基因,候选肝癌相关基因,为后续的深入研究奠定扎实的基础.结果显示,从5个数据集中共发现94个共有的差异表达基因.文献检索后发现24个基因与肝癌发生发展的关系少见文献报道,属于肝癌中未知功能基因.利用GEPIA分析癌症基因组图谱(the cancer genome atlas,TCGA)中数据后发现,GINS1在肝癌组织中高表达,与肝癌患者生存期呈负相关;CFHR4和DNASE1L3在肝癌组织中显著低表达,与肝癌患者生存期呈正相关.荧光定量PCR技术证实GINS1在81.3％的肝癌组织中呈现高表达,CFHR4和DNAS-E1L3分别在71.9％和93.8％肝癌组织中低表达.因此,本研究发现GINS1、CFHR4和DNASE 1L3在肝癌组织中显著差异表达,与肝癌患者的预后密切相关,可能作为潜在的判断肝癌患者预后的分子标志物和研发肝癌治疗的潜在靶标.     

基于网络药理学和分子对接探讨黄芪治疗特发性肺纤维化的分子机制

本研究旨在以黄芪活性成分为切入点,基于网络药理学及分子对接研究黄芪治疗特发性肺纤维化的分子机制。首先,通过TCMSP筛选黄芪的活性成分;利用Swiss Target Prediction预测黄芪化学成分潜在靶点;使用GeneCards和CTD筛选出特发性肺纤维化的相关基因,交集获得黄芪治疗特发性肺纤维化的潜在靶点,对潜在靶点进行生物信息学分析明确关键靶点。然后,通过采用分子对接(SYBYL 2.1.1)验证关键靶点与黄芪化学成分的结合程度。最后通过HE染色、Masson染色及ELISA实验验证网络药理学富集分析结果。最终,通过网络药理学初步筛选得到黄芪治疗特发性肺纤维化的信号通路29条(P0.05),靶点25个,其中IL-17信号通路、EGFR信号通路和HIF-1信号通路为疾病相关通路,PTGS2、VEGFA、MMP-9、STAT3和EGFR为关键靶点;通过分子对接明确黄芪中6个化学成分与5个关键靶点均有较好的结合;HE染色和Masson染色均提示黄芪及其活性成分叶酸对博来霉素诱导的大鼠特发性肺纤维化具有治疗作用,可降低大鼠特发性肺纤维化程度;ELISA实验证明黄芪及其活性成分叶酸能够降低大鼠血清IL-17、MMP-9的表达。本研究通过网络药理学、分子对接及实验验证结果可以明确黄芪治疗特发性肺纤维化的关键靶点及主要化学成分,为开发黄芪抗特发性肺纤维化的有效成分及作用机制提供新的思路方法,为临床有效应用黄芪治疗特发性肺纤维化提供理论依据。     

Integrated bioinformatics analysis revealed the regulation of angiogenesis by tumor cells in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer mortality, metastasis accounts for most of the cases. Angiogenesis plays an important role in cancer metastasis, but how tumor cells affect the function of endothelial cells by dictating their microRNA (miRNA) expression remains largely unknown.Differentially expressed miRNAs (DEMs) were identified through dataset downloaded from the Gene Expression Omnibus (GEO) database and analyzed by GEO2R. We then used online tools to obtain potential targets of candidate miRNAs and functional enrichment analysis, as well as the protein-protein interaction (PPI). Finally, the function of miR-302c-3p was validated through in vitro assay.In the current study, we found that HCC cells altered miRNA expression profiles of human umbilical vein endothelial cells (HUVECs) and miR-302c-3p was the most down-regulated miRNA in HUVECs when they were co-cultured with HCC-LM3 cells. Functional enrichment analysis of the candidate targets revealed that these genes were involved in epigenetic regulation of gene expression, in particular, cytosine methylation. In addition, PPI network demonstrated distinct roles of genes targeted by miR-302c-3p. Importantly, inhibition of angiogenesis, migration and permeability by the most down-regulated miR-302c-3p in HUVECs was confirmed in vitro. These findings brought us novel insight into the regulation of angiogenesis by HCC cells and provided potential targets for the development of therapeutic strategies.     

An in silico analytical study of lung cancer and smokers datasets from gene expression omnibus (GEO) for prediction of differentially expressed genes

Smoking is the leading cause of lung cancer development and several genes have been identified as potential biomarker for lungs cancer. Contributing to the present scientific knowledge of biomarkers for lung cancer two different data sets, i.e. GDS3257 and GDS3054 were downloaded from NCBI׳s GEO database and normalized by RMA and GRMA packages (Bioconductor). Diffrentially expressed genes were extracted by using and were R (3.1.2); DAVID online tool was used for gene annotation and GENE MANIA tool was used for construction of gene regulatory network. Nine smoking independent gene were found whereas average expressions of those genes were almost similar in both the datasets. Five genes among them were found to be associated with cancer subtypes. Thirty smoking specific genes were identified; among those genes eight were associated with cancer sub types. GPR110, IL1RN and HSP90AA1 were found directly associated with lung cancer. SEMA6A differentially expresses in only non-smoking lung cancer samples. FLG is differentially expressed smoking specific gene and is related to onset of various cancer subtypes. Functional annotation and network analysis revealed that FLG participates in various epidermal tissue developmental processes and is co-expressed with other genes. Lung tissues are epidermal tissues and thus it suggests that alteration in FLG may cause lung cancer. We conclude that smoking alters expression of several genes and associated biological pathways during development of lung cancers.     

Relationship of the lung microbiome with PD-L1 expression and immunotherapy response in lung cancer

IL-35 subunit EBI3 is up-regulated in pulmonary fibrosis tissues. In this study, we investigated the pathological role of EBI3 in pulmonary fibrosis and dissected the underlying molecular mechanism. Bleomycin-induced pulmonary fibrosis mouse model was established, and samples were performed gene expression analyses through RNAseq, qRT-PCR and Western blot. Wild type and EBI3 knockout mice were exposed to bleomycin to investigate the pathological role of IL-35, via lung function and gene expression analyses. Primary lung epithelial cells were used to dissect the regulatory mechanism of EBI3 on STAT1/STAT4 and STAT3. IL-35 was elevated in both human and mouse with pulmonary fibrosis. EBI3 knockdown aggravated the symptoms of pulmonary fibrosis in mice. EBI3 deficiency enhanced the expressions of fibrotic and extracellular matrix-associated genes. Mechanistically, IL-35 activated STAT1 and STAT4, which in turn suppressed DNA enrichment of STAT3 and inhibited the fibrosis process. IL-35 might be one of the potential therapeutic targets for bleomycin-induced pulmonary fibrosis.     

Identification of downregulated circRNAs from tissue and plasma of patients with gastric cancer and construction of a circRNA-miRNA-mRNA network

The connection between circular RNAs (circRNAs) and gastric cancer has been reported widely in recent years. However, previous studies have focused mainly on circRNAs from gastric cancer tissue. The objectives of the present study were to detect dysregulated circRNAs from both tissue and plasma of patients with gastric cancer and to explore their potential roles in the pathogenesis of gastric cancer. Expression profiles of circRNAs were obtained from the Gene Expression Omnibus (GEO) and analyzed using the GEO2R tool to identify differential expressed circRNAs. The significance threshold was set as |log2 (fold change)| > 2 and adjusted P < .05. The microRNA (miRNA) binding sites of the differentially expressed circRNAs were predicted using the Circular RNA Interactome web tool. TargetScan and the miRNet database were used to predict the miRNA target genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed using Database for Annotation Visualization and Integrated Discovery. Hub genes were identified and a network was constructed with Cytoscape. The overall survival rates for the selected miRNAs and messenger RNAs were evaluated by Kaplan-Meier Plotter. A total of three downregulated circRNAs (hsa_circ_0001190, hsa_circ_0036287, and hsa_circ_0048607) were identified in this study. Six miRNAs and eight hub genes met the significance criteria and were selected for further analysis. A circRNA-miRNA-hub gene network was constructed based on three circRNAs, six miRNAs, and eight hub genes. Evaluation of overall survival rates for the hub genes showed that low expression levels of GADD45A, PPP1CB, PJA2, and KLF2 were associated with poor overall survival. This study identified potential novel plasma circRNA biomarkers and provides insights into the underlying mechanisms of gastric cancer pathogenesis.     

星形细胞瘤生存预后相关miRNA-mRNA调控关系对筛选

利用GEO数据库中的芯片数据,筛选与星形细胞瘤生存预后相关的miRNA-mRNA调控关系对,为后续研究提供理论支持.下载芯片数据利用R语言进行差异表达分析,得到星形细胞瘤较正常组织表达显著改变的miRNA与mRNA;通过miRNA靶基因预测,将靶基因与差异表达mRNA取交集,明确mRNA与miRNA之间的关系;利用GE...     

Molecular characterization of lung cancer: A two-miRNA prognostic signature based on cancer stem-like cells related genes

Lung cancer is one of the deadliest cancers worldwide. To increase the survival rate of lung cancer, it is necessary to explore specific prognosis markers. More and more evidence finds that noncoding RNA is closely associated with the survival of lung cancer, and cancer stem cells (CSCs) also play a significant role in the progress of lung cancer. The objective of this study is to find CSLCs genes that affect the prognosis of lung cancer. The differential expression of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), messenger RNAs (mRNAs) in the Cancer Genome Atlas (TCGA) database and differential expression data from microarray of CD326⁺ and CD326⁻ A549 cell are intersected to identify stable and consistent expression genes (2 lncRNAs, 15 miRNAs, and 134 mRNAs). The intersection of lncRNAs and miRNAs is analyzed by univariate and multivariate Cox regression to obtained prognostic genes. Two miRNAs (miR-30b-5p and miR-29c-3p) are significantly correlated with the overall survival rate. Then using these two miRNAs to construct a risk score model as a prognosis signature of lung cancer. Subsequently, we analyzed the association between two miRNAs and clinical information of lung cancer patients, of which T stage, Neoplasm cancer and risk score (P < .05) can be used as independent prognostic indicators of lung cancer. Finally, target genes of 2 miRNAs and 134 mRNAs were annotated with Gene Ontology and analyzed with Kyoto Encyclopedia of Genes and Genomes pathway, and verified with the GEO database. In summary, this study illustrates the role of miRNAs in the promotion of lung cancer by CSCs, which is important to find molecular biomarkers of lung cancer.