急性髓系白血病mRNA与非编码RNA差异表达谱及CeRNA调控网络分析

利用GEO数据库(gene expression omnibus database)通过生物信息学分析方法探讨急性髓系白血病(acute myelogenous leukemia,AML)的发病机制。检索GEO数据库中AML相关芯片数据集GSE142698、GSE142699和GSE96535。利用GEO2R分析得到差异mRNAs、miRNAs以及差异lncRNAs。利用在线生物信息学分析工具DAVID对差异mRNAs进行GO富集分析和KEGG通路分析。利用miRWalk数据库预测AML相关miRNAs的靶向mRNAs,利用Spongescan数据库预测AML相关miRNAs的靶向lncRNAs,构建lncRNA-miRNA-mRNA竞争性内源RNA （competing endogenous RNA,ceRNA）调控网络。共筛选出29个显著差异mRNAs、70个显著差异miRNAs和20 005个显著差异lncRNAs。GO富集分析和KEGG通路分析显示,差异表达基因主要涉及蛋白磷酸化、细胞分裂、细胞增殖的负调控、基因表达的正向调节、周期蛋白依赖的丝氨酸/苏氨酸激酶活性的调节等生物过程以及细胞周期、细胞衰老、癌症通路、PI3K-Akt通路等信号通路。将miRWalk数据库预测的靶向mRNAs与差异mRNAs取交集,Spongescan数据库预测的靶向lncRNAs与差异lncRNAs取交集,分别确定了25个mRNAs、6个lncRNAs参与AML相关ceRNA调控网络的构建。结果表明,lncRNAs可能作为关键的ceRNA,通过调控miRNA和相关靶基因参与AML的发生与发展,研究结果为AML诊断和治疗的分子生物学研究提供了新的依据。     

lncRNA作为竞争性内源RNA在非小细胞肺癌中的作用

长链非编码RNA(long non-coding RNA,lncRNA)参与肿瘤的多种生理、病理进程.研究表明,lncRNA可通过与微小RNA (microRNA, mi RNA)反应元件相互作用,并与其他RNA分子形成竞争性内源RNA (competing endogenous RNA,ceRNA)的调控网络,参与基因的表达调控.lncRNA以ceRNA方式参与非小细胞肺癌(non-small cell lung cancer,NSCLC)的发生发展过程,为揭示NSCLC的分子机理开拓了新的思路,也为NSCLC的治疗提供新的靶点.本文在课题组前期发现NSCLC相关ceRNA基础上,主要讨论lncRNA作为ceRNA在NSCLC中高表达、低表达及治疗相关方面的作用.     

Identification and development of long non‐coding RNA‐associated regulatory network in colorectal cancer

Colorectal cancer (CRC) is one of the leading causes of cancer‐associated death globally. Long non‐coding RNAs (lncRNAs) have been identified as micro RNA (miRNA) sponges in a competing endogenous RNA (ceRNA) network and are involved in the regulation of mRNA expression. This study aims to construct a lncRNA‐associated ceRNA network and investigate the prognostic biomarkers in CRC. A total of 38 differentially expressed (DE) lncRNAs, 23 DEmiRNAs and 27 DEmRNAs were identified by analysing the expression profiles of CRC obtained from The Cancer Genome Atlas (TCGA). These RNAs were chosen to develop a ceRNA regulatory network of CRC, which comprised 125 edges. Survival analysis showed that four lncRNAs, six miRNAs and five mRNAs were significantly associated with overall survival. A potential regulatory axis of ADAMTS9‐AS2/miR‐32/PHLPP2 was identified from the network. Experimental validation was performed using clinical samples by quantitative real‐time PCR (qRT‐PCR), which showed that expression of the genes in the axis was associated with clinicopathological features and the correlation among them perfectly conformed to the ‘ceRNA theory’. Overexpression of ADAMTS9‐AS2 in colon cancer cell lines significantly inhibited the miR‐32 expression and promoted PHLPP2 expression, while ADAMTS9‐AS2 knockdown had the opposite effects. The constructed novel ceRNA network may provide a comprehensive understanding of the mechanisms of CRC carcinogenesis. The ADAMTS9‐AS2/miR‐32/PHLPP2 regulatory axis may serve as a potential therapeutic target for CRC.     

To construct a ceRNA regulatory network as prognostic biomarkers for bladder cancer

Emerging evidence demonstrates that competing endogenous RNA (ceRNA) hypothesis has played a role in molecular biological mechanisms of cancer occurrence and development. But the effect of ceRNA network in bladder cancer (BC), especially lncRNA‐miRNA‐mRNA regulatory network of BC, was not completely expounded. By means of The Cancer Genome Atlas (TCGA) database, we compared the expression of RNA sequencing (RNA‐Seq) data between 19 normal bladder tissue and 414 primary bladder tumours. Then, weighted gene co‐expression network analysis (WGCNA) was conducted to analyse the correlation between two sets of genes with traits. Interactions between miRNAs, lncRNAs and target mRNAs were predicted by MiRcode, miRDB, starBase, miRTarBase and TargetScan. Next, by univariate Cox regression and LASSO regression analysis, the 86 mRNAs obtained by prediction were used to construct a prognostic model which contained 4 mRNAs (ACTC1 + FAM129A + OSBPL10 + EPHA2). Then, by the 4 mRNAs in the prognostic model, a ceRNA regulatory network with 48 lncRNAs, 14 miRNAs and 4 mRNAs was constructed. To sum up, the ceRNA network can further explore gene regulation and predict the prognosis of BC patients.     

The exploration of new therapeutic targets for HPV-negative head and neck squamous cell cancer through the construction of a ceRNA network and immune microenvironment analysis

Previous studies have shown that human papillomavirus (HPV)-negative patients with head and neck squamous cell cancer (HNSCC) suffer from an unsatisfactory prognosis. Long noncoding RNAs (lncRNAs) have been verified to participate in many biological processes, including regulating gene expression as competing endogenous RNAs (ceRNAs), while few studies focused the ceRNA network regulation mechanism in patients with HPV-negative HNSCC tumor. Meanwhile, the immune microenvironment may be critical in the development and prognosis of HPV-negative tumors. Our study aimed to further investigate the pathogenesis and potential biomarkers for the diagnosis, therapy and prognosis of HPV-negative HNSCC through a ceRNA network. Comprehensively analyzing the sequencing data of lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) in The Cancer Genome Atlas HNSCC dataset, we constructed a differentially expressed ceRNA network containing 131 lncRNAs, 35 miRNAs and 162 mRNAs. Then, survival analysis in the network was cited to explore the prognostic biomarkers. Eight mRNAs, nine lncRNAs, and one miRNA were identified to be associated with prognosis. Neuropilin (NRP) binding function, retinoid X receptor (RXR) binding, and the vascular endothelial growth factor (VEGF) signaling pathway were associated with the enrichment analysis, and they also related to the immune microenvironment. Combined with the analysis of the immune microenvironment differences, we obtained new targeted therapies using an RXR agonist, or a combination of the VEGF monoclonal antibody and an NRP antagonist, which may provide a promising future for HPV-negative HNSCC patients.     

Dysregulated ceRNA network modulated by copy number variation-driven lncRNAs in breast cancer: A comprehensive analysis

Breast cancer is a malignancy harmful to physical and mental health in women, with quite high mortality. Copy number variations (CNVs) are vital factors affecting the progression of breast cancer. Detecting CNVs in breast cancer to predict the prognosis of patients has become a promising approach to accurate treatment in recent years. The differential analysis was performed on CNVs of long noncoding RNAs (lncRNAs) as well as the expression of lncRNAs, microRNAs (miRNAs) and mRNAs in normal tissue and breast tumor tissue based on The Cancer Genome Atlas (TCGA) database. The CNV-driven lncRNAs were identified by the Kruskal–Wallis test. Meanwhile, a competitive endogenous RNA (ceRNA) network regulated by CNV-driven lncRNA was constructed. As the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed, the mRNAs in the dysregulated ceRNA network were mainly enriched in the biological functions and signaling pathways, including the Focal Adhesion-PI3K-Akt–mTOR-signaling pathway, the neuronal system, metapathway biotransformation Phase I and II and blood circulation, etc. The relationship between the CNVs of five lncRNAs and their gene expression in the ceRNA network was analyzed via a chi-square test, which confirmed that except for LINC00243, the expression of four lncRNAs was notably correlated with the CNVs. The survival analysis revealed that only the copy number gain of LINC00536 was evidently related to the poor prognosis of patients. The CIBERSORT algorithm showed that five lncRNAs were correlated with the abundance of immune cell infiltration and immune checkpoints. In a word, by analyzing CNV-driven lncRNAs and the ceRNA network regulated by these lncRNAs, this study explored the mechanism of breast cancer and provided novel insights into new biomarkers.     

An 11-lncRNA expression could be potential prognostic biomarkers in head and neck squamous cell carcinoma

The aim of our study is to construct the competing endogenous RNA (ceRNA) network of head and neck squamous cell carcinoma (HNSCC) and identify key long noncoding RNAs (lncRNAs) to predict prognosis. The genes whose expression were differentially in HNSCC and normal tissues were explored by the Cancer Genome Atlas database. The ceRNA network was constructed by the Cytoscape software. The lncRNAs which could estimate the overall survival were explored from Cox proportional hazards regression. There are 1997, 589, and 82 mRNAs, lncRNAs, and miRNAs whose expression were statistically significant different, respectively. Then, the network between miRNA and mRNA or miRNA and lncRNA was constructed by miRcode, miRDB, TargetScan, and miRanda. Five mRNAs, 10 lncRNAs, and 3 miRNAs were associated with overall survival. Then, 11-lncRNAs were found to be prognostic factors. Therefore, our research analyzed the potential signature of novel 11-lncRNA as candidate prognostic biomarker from the ceRNA network for patients with HNSCC.     

子宫内膜癌中的lncRNA-miRNA-mRNA ceRNA网络的整合分析

子宫内膜癌(uterine corpus endometrial carcinoma, UCEC)是危害女性健康的癌症之一,但其发生发展机制尚不完全清楚。基因的异常表达在细胞癌变过程中发挥着重要的作用。本研究利用生物信息学方法对UCEC中异常表达的基因进行网络调控分析,为UCEC的机制研究及预后治疗提供理论依据。首先,利用"limma"包筛选得到差异表达的RNA分子;接着,利用R软件中的"GDCRNATools"包构建lncRNA-miRNA-mRNAceRNA网络;最后,利用DAVID(TheDatabasefor Annotation,Visualization and Integrated Discovery)、R软件中的"survival"包、MCODE(Molecular COmplex Detection)插件、StarBase数据库等对ceRNA网络中的RNA分子进行综合分析。结果显示,在UCEC中,我们鉴定了1 319个mRNA、68个lncRNA及100个miRNA为差异表达的RNA分子。同时,利用这些UCEC中的差异表达RNA分子,成功构建了ceRNA网络,结果表明,HCG11、LINC00958、LINC00667、MAGI2-AS3和AC093010.3可能具有ceRNA的功能。通过进一步对该网络成员的分析,结果发现,该网络中的mRNA分子聚集于内皮细胞增殖、细胞骨架和锌离子结合负调控等生物学过程中。生存分析显示,hsa-miR-449a、LINC00958、PKIA和DPYSL2等19个差异表达的RNA分子与UCEC患者预后显著相关。最后,利用MCODE插件对ceRNA网络进行筛选,共获得一个子网络,其成员分别是LINC00667、hsa-miR-449a、hsa-miR-34a-5p和RECK。该研究结果提示,在UCEC的发生发展中存在lncRNA、miRNA和mRNA的差异表达,并且这些RNA分子之间存在ceRNA网络模式的调控,其中一些关键分子与患者的预后相关,这将为进一步研究与理解UCEC的发病机制及预后提供理论依据。     

Construction of lncRNA-associated ceRNA networks to identify prognostic lncRNA biomarkers for glioblastoma

Long noncoding RNAs (lncRNAs) serve as competitive endogenous RNAs (ceRNAs) that play significant regulatory roles in the pathogenesis of tumors. However, the role of lncRNAs, especially the lncRNA-related ceRNA regulatory network, in glioblastoma (GBM) has not been fully elucidated. The goal of the current study was to construct lncRNA-microRNA-mRNA-related ceRNA networks for further investigation of their mechanism of action in GBM. We downloaded data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases and identified differential lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) associated with GBM. A ceRNA network was constructed and analyzed to examine the relationship between lncRNAs and patients’ overall survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGGs) were used to analyze the related mRNAs to indirectly explain the mechanism of action of lncRNAs. The potential effective drugs for the treatment of GBM were identified using the connectivity map (CMap). After integrated analysis, we obtained a total of 210 differentially expressed lncRNAs, 90 differentially expressed miRNAs, and 2508 differentially expressed mRNAs (DEmRNAs) from the TCGA and GEO databases. Using these differential genes, we constructed a lncRNA-associated ceRNA network. Six lncRNAs in the ceRNA network were associated with the overall survival of patients with GBM. Through KEGG analysis, it was found that the DEmRNAs involved in the network are related to cancer-associated pathways, for instance, mitogen-activated protein kinase and Ras signaling pathways. CMap analysis revealed four small-molecule compounds that could be used as drugs for the treatment of GBM. In this study, a multi-database joint analysis was used to construct a lncRNA-related ceRNA network to help identify the regulatory functions of lncRNAs in the pathogenesis of GBM.     

ceRNA network construction and comparison of gastric cancer with or without Helicobacter pylori infection

Gastric cancer (GC) is a lethal disease, and among its variety of etiological factors, Helicobacter pylori (H. pylori) infection is the strongest risk factor. However, the genetic and molecular mechanisms underlying H. pylori-related GC need further elucidation. We investigated the competing endogenous RNA (ceRNA) network differences between H. pylori (+) and H. pylori (−) GC. The long noncoding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) expression data from 32 adjacent noncancerous samples and 18 H. pylori (+) and 141 H. pylori (−) stomach adenocarcinoma samples were downloaded from the TCGA database. After construction of lncRNA–miRNA–mRNA ceRNA networks of H. pylori (+) and H. pylori (−) GC, Panther and Kobas databases were used to analyze the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Finally, survival analysis was used to discover the key genes. In H. pylori (+) GC, we identified a total of 1,419 lncRNAs, 82 miRNAs, and 2,501 mRNAs with differentially expressed profiles. In H. pylori (−) GC, 2,225 lncRNAs, 130 miRNAs, and 3,146 mRNAs were differentially expressed. Furthermore, three unique pathways (cytokine–cytokine receptor interaction, HIF-1 signaling pathway, and Wnt signaling pathway) were enriched in H. pylori (+) GC. According to the overall survival analysis, three lncRNAs (AP002478.1, LINC00111, and LINC00313) and two mRNAs (MYB and COL1A1) functioned as prognostic biomarkers for patients with H. pylori (+) GC. In conclusion, our study has identified the differences in ceRNA regulatory networks between H. pylori (+) and H. pylori (−) GC and provides a rich candidate reservoir for future studies.     

Integrative analysis of competing endogenous RNA networks reveals the functional lncRNAs in heart failure

Heart failure has become one of the top causes of death worldwide. It is increasing evidence that lncRNAs play important roles in the pathology processes of multiple cardiovascular diseases. Additionally, lncRNAs can function as ceRNAs by sponging miRNAs to affect the expression level of mRNAs, implicating in numerous biological processes. However, the functional roles and regulatory mechanisms of lncRNAs in heart failure are still unclear. In our study, we constructed a heart failure‐related lncRNA‐mRNA network by integrating probe re‐annotation pipeline and miRNA‐target interactions. Firstly, some lncRNAs that had the central topological features were found in the heart failure‐related lncRNA‐mRNA network. Then, the lncRNA‐associated functional modules were identified from the network, using bidirectional hierarchical clustering. Some lncRNAs that involved in modules were demonstrated to be enriched in many heart failure‐related pathways. To investigate the role of lncRNA‐associated ceRNA crosstalks in certain disease or physiological status, we further identified the lncRNA‐associated dysregulated ceRNA interactions. And we also performed a random walk algorithm to identify more heart failure‐related lncRNAs. All these lncRNAs were verified to show a strong diagnosis power for heart failure. These results will help us to understand the mechanism of lncRNAs in heart failure and provide novel lncRNAs as candidate diagnostic biomarkers or potential therapeutic targets.     

Competing endogenous RNA network and prognostic nomograms for hepatocellular carcinoma patients who underwent R0 resection

The prognosis of hepatocellular carcinoma (HCC) after R0 resection is unsatisfactory due to the high rate of recurrence. In this study, we investigated the recurrence-related RNAs and the underlying mechanism. The long noncoding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) expression data and clinical information of 247 patients who underwent R0 resection patients with HCC were obtained from The Cancer Genome Atlas. Comparing the 1-year recurrence group (n = 56) with the nonrecurrence group (n = 60), we detected 34 differentially expressed lncRNAs (DElncRNAs), five DEmiRNAs, and 216 DEmRNAs. Of these, three DElncRNAs, hsa-mir-150-5p, and 11 DEmRNAs were selected for constructing the competing endogenous RNA (ceRNA) network. Next, two nomogram models were constructed based separately on the lncRNAs and mRNAs that were further selected by Cox and least absolute shrinkage and selection operator regression analysis. The two nomogram models that showed a high prediction accuracy for disease-free survival with the concordance indexes at 0.725 and 0.639. Further functional enrichment analysis of DEmRNAs showed that the mRNAs in the ceRNA network and nomogram models were associated with immune pathways. Hence, we constructed a hsa-mir-150-5p-centric ceRNA network and two effective nomogram prognostic models, and the related RNAs may be useful as potential biomarkers for predicting recurrence in patients with HCC.     

Construction of competitive endogenous RNA network reveals regulatory role of long non‐coding RNAs in type 2 diabetes mellitus

Increasing epidemic of type 2 diabetes mellitus (T2DM) and its comorbidities makes it urgent to understand the pathogenesis and regulatory mechanism. However, little is known about the regulatory role of lncRNAs in diabetes. Here, we constructed a T2DM‐related competitive endogenous RNA (ceRNA) network (DMCN) to explore biological function of lncRNAs during the development of diabetes mellitus. This network contained 351 nodes including 98 mRNAs, 86 microRNAs and 167 lncRNAs. Functional analysis showed that the mRNAs in DMCN were annotated into some diabetes‐related pathways. Furthermore, mTOR‐centred subnetwork was extracted and ncRNA‐involved mTOR pathway was established. Finally, we validated that NEAT1 was potentially communicated with mTOR signalling target protein mLST8 via the association with miR‐181b. These findings provide significant insight into lncRNA regulatory network in T2DM.