利用TCGA数据库构建肾透明细胞癌相关miRNA预后模型

利用TCGA数据库中肾透明细胞癌的miRNA与mRNA数据及临床信息,构建由miRNA组成的预后风险评分模型,并筛选与生存预后相关的miRNA-mRNA调控关系对,为研究提供理论依据。下载并整理TCGA[JP+1]数据库中肾透明细胞癌的miRNA与mRNA数据;对数据进行差异分析,将差异表达的miRNA与临床信息进行合并,利用单因素与多因素Cox回归分析,构建预后模型并进行模型评价;对模型中的miRNA进行靶基因预测,结果与差异表达的mRNA进行取交集,构建miRNA-mRNA调控网络;对网络中的mRNA进行生存分析,筛选生存相关的miRNA-mRNA调控关系对。共得到49个差异表达的miRNA与3 613个差异表达的mRNA;预后模型计算公式为:风险值(risk score)=hsa-miR-21-5p表达量×0.603＋hsa-miR-1251-5p表达量×-0.093;调控网络中共纳入31个miRNA-mRNA调控关系对;对mRNA进行生存分析,共得到7个有价值的关系对。所构建预后模型可有效预测肾透明细胞癌患者生存预后情况,筛选到的miRNA-mRNA调控关系对可为相关研究与治疗提供参考。     

microRNAs在肝细胞癌中的调控机制及临床应用

microRNA（miRNA）在人类恶性肿瘤的发生发展过程中起着重要作用。近期研究表明,miRNA通过结合特定靶标参与调控肝细胞癌（hepatocellularcarcinoma,HCC）的发生,可作为辅助生物标志物用于指导肝细胞癌的诊断和治疗,并为有效地监控和预防肝病提供了新途径。寻找miRNA靶标,阐明miRNA参与肝癌发生的调控机理,有利于肝癌的临床靶向基因治疗。通过总结miRNA在肝细胞癌中的调控机制及临床应用的研究进展,为寻找肝细胞癌早期诊断的生物标志物及介入治疗的靶点提供了参考。     

miRNA在肝细胞癌中的研究进展和展望

微小RNA(microRNA, miRNA)是一类长度为二十几个核苷酸的内源性非编码调控RNA,通过序列特异性翻译抑制或mRNA裂解来调控基因表达,参与细胞发育、增殖、分化、凋亡等一系列重要生物学进程。近期的研究发现,miRNA具有癌基因和抑癌基因的作用,在肿瘤的发生和发展中起着重要的作用。已发现若干miRNA直接参与肝细胞癌的发生和发展,miRNA表达谱与肝细胞癌的诊断、分期、进展和预后等相关。作为一类新的分子靶标,miRNA应用于肝细胞癌的诊断和生物治疗具有广阔的前景。     

肾透明细胞癌预后相关miRNAs的生物信息学分析

目的寻找可作为肾透明细胞癌（ccRCC）生物标志物的miRNA,以及ccRCC与正常组织间miRNA差异表达情况。 方法利用TCGA数据库下载ccRCC中miRNA表达数据,分析肿瘤与正常组织间差异表达miRNA。使用Kaplan-Meier曲线对患者进行生存分析,筛选出表达情况与临床预后相关的miRNA。通过生物信息学对miRNA的靶基因进行预测,然后运用FunRich软件和ClueGO对靶基因进行GO和KEGG富集分析。 结果通过TCGA数据库分析发现,ccRCC较正常组织差异表达miRNA共54个,其中上调33个,下调21个。通过生存分析发现hsa-miR-21和hsa-miR-155与患者预后相关,P≤0.05。进一步通过Perl软件在Targetscan、miRDB、miRTarBase、miRPath这四个数据库中预测miRNA靶基因并将结果取交集,共发现129个靶基因。GO和KEGG分析结果表明,这些靶基因主要与转录因子活性、信号转导以及FoxO、TNF等信号通路密切相关。 结论通过生物信息学分析发现了ccRCC与正常组织的差异表达miRNA;其中hsa-miR-21和hsa-miR-155与患者总体生存率相关,并通过调控靶基因参与相关的信号通路进而影响ccRCC的发生发展进程,提示hsa-miR-21和hsa-miR-155可能是ccRCC潜在的生物标志物。     

通过miRNA基因表达谱的基因共表达网络构建对星形细胞瘤的基因靶标进行预测

星形细胞瘤为浸润性生长肿瘤,生长缓慢,多为隐形症状,难以早期发现。多数肿瘤切除后有复发可能,且复发后肿瘤可演变成间变性星形细胞瘤或多形性胶质母细胞瘤。因此寻找其生物标志物早期诊断,并研究新的治疗方法就十分重要。方法:通过选用GEO数据库的星形细胞瘤miRNA表达谱数据,进行差异分析以及靶基因预测,通过2者共表达网络的构建对筛选出的miRNA的研究价值进行探讨。结果:得出hsa-miR-29b-2-5p;hsa-miR-339-5p与hsa-miR-362-3p3个较为关键的miRNA及与3者关系密切的8个mRNA。结论:通过对8个mRNA在癌症中的作用的讨论,肯定了这3个关键miRNA作为潜在靶点的研究价值。     

基于生物信息学筛选染料木素抗骨肉瘤靶基因

染料木素是一种天然的小分子物质,在多种肿瘤中显示出抗肿瘤作用,探究染料木素作用于骨肉瘤的靶基因。从DrugBank下载与染料木素有关的靶基因,分别导入string数据库中进行分析,用Cytoscape作出蛋白质相互作用(PPI)网络,同时用插件Cytohubb分析PPI,获得25个关键基因,再用WebGestalt分析25个基因的KEGG通路,选取与骨肉瘤相关通路的靶基因,得到的靶基因用HCMDB数据库验证,最后用miRDB预测靶基因的miRNA并在GSE65071数据库中进行验证。一共筛选出13个与染料木素有关的靶基因,选择其中药理作用不明的11个基因进行后续分析,string数据库中获得284个与11个靶基因有关的基因,使用WebGestalt分析25个关键基因,随后选取NF-kappaB和Rap1信号通路的靶基因在HCMDB数据库中进行验证,最后使用miRDB和GES65071数据库得到hsa-miR-23b-3p,hsa-miR-23a-3p,hsa-miR-141-3p和hsa-miR-200a-3p。研究显示CXCL8,CXCL12,LPAR1和CNR1;hsa-miR-23b-3p,hsa-miR-23a-3p,hsa-miR-141-3p和hsa-miR-200a-3p可能成为骨肉瘤的治疗靶基因。     

肝细胞癌中抑癌基因的发现与研究进展

肝细胞癌（HCC）的发病率高、治疗效果差。HCC的发病机制复杂,主要有2类：肝炎、酒精、黄曲霉素、代谢紊乱引起的肝损伤,进而导致的肝硬化;致癌基因和抑癌基因的突变或对应染色体区域的扩增或缺失。细胞内一些信号通路参与了HCC的发生发展,包括RAF／MEK／ERK、P13K／AKT／mTOR、WNT/β-catenin、胰岛素样生长因子、肝细胞生长因子／c-MET、生长因子调节的血管新生等6类信号通路。抑癌基因通过调节信号通路而调节细胞增殖、细胞周期、细胞凋亡等对肿瘤的发生、发展起重要作用的过程。我们简要概述HCC相关的肿瘤抑制分子及其所在的信号通路及作用的分子机制。     

综述:慢性感染非可控炎症引发肝癌的机制与治疗策略

免疫应答在调控肝癌等肿瘤发生中发挥双刃剑作用,只有慢性非可控炎症才引发肝细胞癌(HCC),这得到了大量动物模型和临床数据的支持.在慢性肝炎中浸润的免疫细胞直接杀伤肝细胞、炎症因子引发的细胞凋亡和坏死诱发肝细胞持续性炎症坏死与再生,这直接增加肝细胞突变的风险.NF-κB、JAK-STAT、MAPK/ERK等通路以及miR-122、miR-124、miR-637、miR-520e、miR-195等小RNA均参与慢性炎症-HCC的转化.阻断引发非可控炎症的诱因、直接靶向炎症因子以及干预慢性炎症引发HCC的关键信号通路,对于研发新型HCC的网络治疗方案至关重要.     

肝细胞癌患者血清外泌体microRNA表达鉴定

目的:探讨肝癌细胞外泌体中差异表达的microRNAs(miRNAs)在肝细胞癌(HCC)诊断中的应用价值。方法:通过高通量测序筛选肝癌细胞外泌体中差异表达的miRNAs。实时定量PCR验证差异表达分子;检测差异表达的miRNAs在健康人(Health)、慢性乙型肝炎患者(CHB)、肝硬化患者(LC)及乙型肝炎病毒阳性的肝细胞癌患者(HCC)血清外泌体中的表达。结果:高通量测序筛选到肝癌细胞外泌体中差异表达的miRNA共88种,其中58种表达上调,30种表达下调。选择其中8种差异表达的miRNAs进行q RT-PCR验证,结果显示,此8种miRNAs在细胞上清外泌体、细胞内、癌与癌旁组织中的表达趋势与测序结果一致。miR-221-3p和miR-224-5p在HCC组外泌体中的表达水平显著高于Health组、CHB组和LC组(P0.01),miR-124-3p和let-7a-5p在HCC组外泌体中的表达水平显著低于其他各组(P0.05)。四个组中,miR-21-5p、miR-191-5p、miR-34a-5p和miR-122-5p的表达水平不存在显著性差异(P0.05)。结论:血清外泌体中的miR-221-3p、miR-224-5p、miR-124-3p和let-7a-5p可能成为肝细胞癌的候选标志物。     

肝细胞癌组织miR-124-3p、miR-212-5p表达与PI3K/Akt信号通路和预后的关系研究

摘要 目的：探讨肝细胞癌组织中微小核糖核酸（miR）-124-3p、miR-212-5p表达与磷脂酰肌醇3-激酶（PI3K）/蛋白激酶B（Akt）信号通路和预后的关系。方法：选择2017年9月至2019年9月徐州医科大学附属医院肝胆外科收治的93例肝细胞癌患者,采用实时荧光定量聚合酶链反应（qRT-PCR）检测肝细胞癌组织中miR-124-3p、miR-212-5p、PI3K 信使RNA（mRNA）、Akt mRNA的表达。Pearson相关性分析miR-124-3p、miR-212-5p表达与PI3K/Akt信号通路相关mRNA表达的相关性。绘制Kaplan-Meier生存曲线,Log-Rank检验不同miR-124-3p、miR-212-5p表达肝细胞癌患者3年总生存率（OS）的差异。结果：肝细胞癌组织中miR-124-3p表达低于癌旁组织（P＜0.05）,miR-212-5p、PI3K mRNA、Akt mRNA表达高于癌旁组织（P＜0.05）。肝细胞癌组织中miR-124-3p表达与PI3K mRNA、Akt mRNA表达呈负相关（P＜0.05）,miR-212-5p表达与PI3K mRNA、Akt mRNA表达呈正相关（P＜0.05）。Ⅱa期、低分化患者肝细胞癌组织中miR-124-3p表达低于Ⅰa-Ⅰb期、中高分化患者（P＜0.05）,miR-212-5p表达高于Ⅰa-Ⅰb期、中高分化患者（P＜0.05）。随访期间死亡37例, miR-124-3p低表达组3年OS为42.55%,低于miR-124-3p高表达组的78.26%（P＜0.05）,miR-212-5p高表达组3年OS为50.00%,低于miR-212-5p低表达组的71.11%（P＜0.05）。结论：肝细胞癌组织中miR-124-3p表达下调,miR-212-5p表达上调,且与肝细胞癌PI3K/Akt信号通路激活,PI3K mRNA和Akt mRNA高表达,低分化,CNLC分期Ⅱa期以及低OS有关。     

The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma

The aim of this study was to identify novel prognostic mRNA and microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) using methods in systems biology. Differentially expressed mRNAs, miRNAs, and long non-coding RNAs (lncRNAs) were compared between HCC tumor tissues and normal liver tissues in The Cancer Genome Atlas (TCGA) database. Subsequently, a prognosis-associated mRNA co-expression network, an mRNA–miRNA regulatory network, and an mRNA–miRNA–lncRNA regulatory network were constructed to identify prognostic biomarkers for HCC through Cox survival analysis. Seven prognosis-associated mRNA co-expression modules were obtained by analyzing these differentially expressed mRNAs. An expression module including 120 mRNAs was significantly correlated with HCC patient survival. Combined with patient survival data, several mRNAs and miRNAs, including CHST4, SLC22A8, STC2, hsa-miR-326, and hsa-miR-21 were identified from the network to predict HCC patient prognosis. Clinical significance was investigated using tissue microarray analysis of samples from 258 patients with HCC. Functional annotation of hsa-miR-326 and hsa-miR-21-5p indicated specific associations with several cancer-related pathways. The present study provides a bioinformatics method for biomarker screening, leading to the identification of an integrated mRNA–miRNA–lncRNA regulatory network and their co-expression patterns in relation to predicting HCC patient survival.     

Altered plasma exosome miRNAs and novel potential biomarkers in pediatric fulminant myocarditis

Previous studies have indicated that exosome-mediated intercellular microRNAs (miRNA) can influence fulminant myocarditis (FM) pathogenesis between immune and cardiac cells. This study explored plasma exosome miRNA profile in pediatric FM using a small RNA microarray. As per our analysis, we observed the differential expression of 266 miRNAs, including 197 upregulated and 69 downregulated candidate genes. Differentially expressed mRNAs in pediatric FM patients' peripheral blood mononuclear cells (PBMCs) were intersected with miRNA target genes predicting tools to screen for FM-specific target genes. The hub genes and their biological and mechanistic pathways related to inflammation and/or the immune system were identified. CeRNA networks of lncRNAs, circRNAs, miRNAs, and mRNAs between cardiomyocytes and PBMCs were finally established. Furthermore, we verified that hsa-miR-146a-5p, hsa-miR-23a-3p, and hsa-miR-27a-3p had higher expression levels in exosomes of pediatric FM patients by qRT-PCR, and hsa-miR-146a-5p shown high sensitivities and specificities for FM diagnosis. Overall, the results demonstrate that the exosome miRNAs play a regulatory role between immune and cardiac cells and provide research targets.     

Retracted: Deep integrative analysis of microRNA-mRNA regulatory networks for biomarker and target discovery in chondrosarcoma

Chondrosarcoma (CHS) is a common malignant bone sarcoma and its occurrence increases with age. microRNAs (miRNAs) are a class of noncoding RNAs that participate in various biological processes and disease pathogenesis by targeting functional messenger RNA (mRNA). However, the modulation of miRNAs in CHS remains largely unknown. In this study, we performed integrative analysis to explore the expression profiles of miRNAs and mRNAs, together with their interaction networks in human CHS tissues and cell lines by RNA-seq (miRNA and mRNA). A total of 133 and 796 differentially expressed miRNAs and mRNAs were identified (|Fold change| ≥ 2 and P-value ≤ 0.5). miRNA-mRNA regulatory interactions between 55 miRNAs and 242 mRNAs were screened by the Pearson correlation analysis and target prediction. mRNAs in the network were enriched to 145 Gene Ontology terms and 35 Kyoto Encyclopedia of Genes and Genomes pathways. Specifically, some key regulators (hub-miRNAs) in the network (miR-622, miR-4539, miR-145, miR-25, and miR-96) were suggested to play important regulatory roles in the pathogenesis of CHS. In addition, functional experiments validated that miR-622 regulated CHS cell proliferation by targeting bone morphogenetic protein 1 (BMP1).     

Inferring the perturbed microRNA regulatory networks from gene expression data using a network propagation based method

Background

MicroRNAs (miRNAs) are a class of endogenous small regulatory RNAs. Identifications of the dys-regulated or perturbed miRNAs and their key target genes are important for understanding the regulatory networks associated with the studied cellular processes. Several computational methods have been developed to infer the perturbed miRNA regulatory networks by integrating genome-wide gene expression data and sequence-based miRNA-target predictions. However, most of them only use the expression information of the miRNA direct targets, rarely considering the secondary effects of miRNA perturbation on the global gene regulatory networks.

Results

We proposed a network propagation based method to infer the perturbed miRNAs and their key target genes by integrating gene expressions and global gene regulatory network information. The method used random walk with restart in gene regulatory networks to model the network effects of the miRNA perturbation. Then, it evaluated the significance of the correlation between the network effects of the miRNA perturbation and the gene differential expression levels with a forward searching strategy. Results show that our method outperformed several compared methods in rediscovering the experimentally perturbed miRNAs in cancer cell lines. Then, we applied it on a gene expression dataset of colorectal cancer clinical patient samples and inferred the perturbed miRNA regulatory networks of colorectal cancer, including several known oncogenic or tumor-suppressive miRNAs, such as miR-17, miR-26 and miR-145.

Conclusions

Our network propagation based method takes advantage of the network effect of the miRNA perturbation on its target genes. It is a useful approach to infer the perturbed miRNAs and their key target genes associated with the studied biological processes using gene expression data.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-255) contains supplementary material, which is available to authorized users.