Genome-wide identification of a competing endogenous RNA network in cholangiocarcinoma

Cholangiocarcinoma (CCA) is the second widespread liver tumor with relatively poor survival. Increasing evidence in recent studies showed long noncoding RNAs (lncRNAs) exert a crucial impact on the development and progression of CCA based on the mechanism of competing endogenous RNAs (ceRNAs). However, functional roles and regulatory mechanisms of lncRNA-regulated ceRNA in CCA, are only partially understood. The expression profile of messenger RNAs (mRNAs), lncRNAs, and microRNAs (miRNAs) downloaded from The Cancer Genome Atlas were comprehensively investigated. Differential expression of these three types of RNA between CCA and corresponding precancerous tissues were screened out for further analysis. On the basis of interactive information generated from miRDB, miRTarBase, TargetScan, and miRcode public databases, we then constructed an mRNA-miRNA-lncRNA regulatory network. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were conducted to identify the biological function of the ceRNA network involved in CCA. As a result, 2883 mRNAs, 136 miRNAs, and 993 lncRNAs were screened out as differentially expressed RNAs in CCA. In addition, a ceRNA network in CCA was constructed, composing of 50 up and 27 downregulated lncRNAs, 14 up and 7 downregulated miRNAs, 29 up and 25 downregulated mRNAs. Finally, gene set enrichment and pathway analysis indicated our CCA-specific ceRNA network was related with cancer-related pathway and molecular function. In conclusion, our research identified a novel lncRNA-related ceRNA network in CCA, which might act as a potential therapeutic target for patients with CCA.     

Integrated analysis of co‐expression and ceRNA network identifies five lncRNAs as prognostic markers for breast cancer

Long non‐coding RNAs (lncRNAs), which competitively bind miRNAs to regulate target mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for breast cancer. LncRNA, mRNA and miRNA expression profiles of breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all miRNAs to perform weighted gene co‐expression network analysis. The correlation between modules and clinical information of breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a ceRNA network of breast cancer. Additionally, the standard Kaplan‐Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and miRNAs co‐expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of miRNAs, our constructed ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2‐AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of breast cancer and provided novel insights into the use of breast cancer drugs and prognosis.     

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.     

Identification of messenger and long noncoding RNAs associated with gallbladder cancer via gene expression profile analysis

The present study aimed to investigate the long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) involved in the progression of gallbladder cancer and explore the potential physiopathologic mechanisms of gallbladder cancer in terms of competing endogenous RNAs (ceRNAs). The original lncRNA and mRNA expression profile data (nine gallbladder cancer tissues samples and nine normal gallbladder samples) in GSE76633 was downloaded from the Gene Expression Omnibus database. Differentially expressed mRNAs and lncRNAs between gallbladder cancer tissue and normal control were selected and the pathways in which they are involved were analyzed using bioinformatics analyses. MicroRNAs (miRNAs) were also predicted based on the differentially expressed mRNAs. Finally, the co-expression relation between lncRNA and mRNA was analyzed and the ceRNA network was constructed by combining the lncRNA-miRNA, miRNA-mRNA, and lncRNA-mRNA pairs. Overall, 373 significantly differentially expressed mRNAs and 47 lncRNAs were identified between cancer and normal tissue samples. The upregulated genes were significantly enriched in the extracellular matrix (ECM)-receptor interaction pathway, while the downregulated genes were involved in the complement and coagulation cascades. Altogether, 128 co-expression relations between lncRNA and mRNA were obtained. In addition, 196 miRNA-mRNA regulatory relations and 145 miRNA-lncRNA relation pairs were predicted. Finally, the lncRNA-miRNA-gene ceRNA network was constructed by combining the three types of relation pairs, such as XLOC_011309-miR-548c-3p-SPOCK1 and XLOC_012588-miR-765-CEACAM6. mRNAs and lncRNAs may be involved in gallbladder cancer progression via ECM-receptor interaction pathways and the complement and coagulation cascades. Moreover, ceRNAs such as XLOC_011309-miR-548c-3p-SPOCK1 and XLOC_012588-miR-765-CEACAM6 can also be implicated in the pathogenesis of gallbladder cancer.     

Identification of functional lncRNAs in atrial fibrillation by integrative analysis of the lncRNA-mRNA network based on competing endogenous RNAs hypothesis

A mounting body of evidence has suggested that long noncoding RNAs (lncRNAs) play critical roles in human diseases by acting as competing endogenous RNAs (ceRNAs). However, the functions and ceRNA mechanisms of lncRNAs in atrial fibrillation (AF) remain to date unclear. In this study, we constructed an AF-related lncRNA-mRNA network (AFLMN) based on ceRNA theory, by integrating probe reannotation pipeline and microRNA (miRNA)-target regulatory interactions. Two lncRNAs with central topological properties in the AFLMN were first obtained. By using bidirectional hierarchical clustering, we identified two modules containing four lncRNAs, which were significantly enriched in many known pathways of AF. To elucidate the ceRNA interactions in certain disease or normal condition, the dysregulated lncRNA-mRNA crosstalks in AF were further analyzed, and six hub lncRNAs were obtained from the network. Furthermore, random walk analysis of the AFLMN suggested that lncRNA RP11-296O14.3 may function importantly in the pathological process of AF. All these eight lncRNAs that were identified from previous steps (RP11-363E7.4, GAS5, RP11-410L14.2, HAGLR, RP11-421L21.3, RP11-111K18.2, HOTAIRM1, and RP11-296O14.3) exhibited a strong diagnostic power for AF. The results of our study provide new insights into the functional roles and regulatory mechanisms of lncRNAs in AF, and facilitate the discovery of novel diagnostic biomarkers or therapeutic targets.     

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.     

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.     

Comprehensive analysis of a ceRNA network reveals potential prognostic cytoplasmic lncRNAs involved in HCC progression

The aberrant expression of long noncoding RNAs (lncRNAs) has drawn increasing attention in the field of hepatocellular carcinoma (HCC) biology. In the present study, we obtained the expression profiles of lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) in 371 HCC tissues and 50 normal tissues from The Cancer Genome Atlas (TCGA) and identified hepatocarcinogenesis-specific differentially expressed genes (DEGs, log fold change ≥ 2, FDR < 0.01), including 753 lncRNAs, 97 miRNAs, and 1,535 mRNAs. Because the specific functions of lncRNAs are closely related to their intracellular localizations and because the cytoplasm is the main location for competitive endogenous RNA (ceRNA) action, we analyzed not only the interactions among these DEGs but also the distributions of lncRNAs (cytoplasmic, nuclear or both). Then, an HCC-associated deregulated ceRNA network consisting of 37 lncRNAs, 10 miRNAs, and 26 mRNAs was constructed after excluding those lncRNAs located only in the nucleus. Survival analysis of this network demonstrated that 15 lncRNAs, 3 miRNAs, and 16 mRNAs were significantly correlated with the overall survival of HCC patients (p < 0.01). Through multivariate Cox regression and lasso analysis, a risk score system based on 13 lncRNAs was constructed, which showed good discrimination and predictive ability for HCC patient survival time. This ceRNA network-construction approach, based on lncRNA distribution, not only narrowed the scope of target lncRNAs but also provided specific candidate molecular biomarkers for evaluating the prognosis of HCC, which will help expand our understanding of the ceRNA mechanisms involved in the early development of HCC.     

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.     

Analysis of competing endogenous RNA network identifies a poorly differentiated cancer-specific RNA signature for hepatocellular carcinoma

Plenty of evidence has suggested that long noncoding RNAs (lncRNAs) play a vital role in competing endogenous RNA (ceRNA) networks. Poorly differentiated hepatocellular carcinoma (PDHCC) is a malignant phenotype. This paper aimed to explore the effect and the underlying regulatory mechanism of lncRNAs on PDHCC as a kind of ceRNA. Additionally, prognosis prediction was assessed. A total of 943 messenger RNAs (mRNAs), 86 miRNAs, and 468 lncRNAs that were differentially expressed between 137 PDHCCs and 235 well-differentiated HCCs were identified. Thereafter, a ceRNA network related to the dysregulated lncRNAs was established according to bioinformatic analysis and included 29 lncRNAs, 9 miRNAs, and 96 mRNAs. RNA-related overall survival (OS) curves were determined using the Kaplan-Meier method. The lncRNA ARHGEF7-AS2 was markedly correlated with OS in HCC (P = .041). Moreover, Cox regression analysis revealed that patients with low ARHGEF7-AS2 expression were associated with notably shorter survival time (P = .038). In addition, the area under the curve values of the lncRNA signature for 1-, 3-, and 5-year survival were 0.806, 0.741, and 0.701, respectively. Furthermore, a lncRNA nomogram was established, and the C-index of the internal validation was 0.717. In vitro experiments were performed to demonstrate that silencing ARHGEF7-AS2 expression significantly promoted HCC cell proliferation and migration. Taken together, our findings shed more light on the ceRNA network related to lncRNAs in PDHCC, and ARHGEF7-AS2 may be used as an independent biomarker to predict the prognosis of HCC.     

Integrated analysis of a competing endogenous RNA network reveals key long noncoding RNAs as potential prognostic biomarkers for hepatocellular carcinoma

Growing evidence has revealed that long noncoding RNAs (lncRNAs) have an important impact on tumorigenesis and tumor progression via a mechanism involving competing endogenous RNAs (ceRNAs). However, their use in predicting the survival of a patient with hepatocellular carcinoma (HCC) remains unclear. The aim of this study was to develop a novel lncRNA expression–based risk score system to accurately predict the survival of patients with HCC. In our study, using expression profiles downloaded from The Cancer Genome Atlas database, the differentially expressed messenger RNAs (mRNAs), lncRNAs, and microRNAs (miRNAs) were explored in patients with HCC and normal liver tissues, and then a ceRNA network constructed. A risk score system was established between lncRNA expression of the ceRNA network and overall survival (OS) or recurrence-free survival (RFS); it was further analyzed for associations with the clinical features of patients with HCC. In HCC, 473 differentially expressed lncRNAs, 63 differentially expressed miRNAs, and 1417 differentially expressed mRNAs were detected. The ceRNA network comprised 41 lncRNA nodes, 12 miRNA nodes, 24 mRNA nodes, and 172 edges. The lncRNA expression–based risk score system for OS was constructed based on six lncRNAs (MYLK-AS1, AL359878.1, PART1, TSPEAR-AS1, C10orf91, and LINC00501), while the risk score system for RFS was based on four lncRNAs (WARS2-IT1, AL359878.1, AL357060.1, and PART1). Univariate and multivariate Cox analyses showed the risk score systems for OS or RFS were significant independent factors adjusted for clinical factors. Receiver operating characteristic curve analysis showed the area under the curve for the risk score system was 0.704 for OS, and 0.71 for RFS. Our result revealed a lncRNA expression–based risk score system for OS or RFS can effectively predict the survival of patients with HCC and aid in good clinical decision-making.     

Circular RNA-associated ceRNA network involved in HIF-1 signalling in triple-negative breast cancer: circ_0047303 as a potential key regulator

The aggressive and highly metastatic nature of triple-negative breast cancer (TNBC) causes patients to suffer from the poor outcome. HIF-1 signalling pathway is a prominent pathway that contributes to angiogenesis and metastasis progression in tumours. On the contrary, the undeniable importance of circular RNAs (circRNAs) as multifunctional non-coding RNAs (ncRNAs) has been identified in breast cancer. These ncRNAs owing to their high stability and specificity have been becoming a hotspot in cancer researches. circRNAs act as competing endogenous RNAs (ceRNAs) and compete with mRNAs for shared miRNAs, thus modulate gene expression. Since the most dysregulated biological functions in TNBC are associated with cellular invasion, understanding the molecular pathogenesis of these processes is a crucial step towards the development of new treatment approaches. The purpose of this study is to undermine the circRNA-associated ceRNA network involved in HIF-1 signalling in TNBC using an integrative bioinformatics approach. In the next step, the novel circ_0047303-mediated ceRNA regulatory axes have been extracted and validated across TNBC samples. We show that circ_0047303 has the highest degree in the circRNA-associated ceRNA network and shows a significant up-expression in TNBC. Moreover, our results suggest that circ_0047303 could mediate the upregulation of key angiogenesis-related genes, including HIF-1, EIF4E2 and VEGFA in TNBC through sponging the tumour-suppressive miRNAs. The circ_0047303 could be a promising molecular biomarker and/or therapeutic target for TNBC.     

竞争性内源RNA:一种全新的基因表达调控模式

竞争性内源RNA(ceRNA)假说是一种全新的基因表达调控模式:mRNA、假基因转录物和长链非编码RNA等转录物通过microRNA应答元件竞争结合相同的microRNA来调控各自的表达水平,从而影响细胞的功能.迄今为止,多家实验室已从生物信息学、细胞生物学和动物实验等层面验证了该假说.本文追溯了ceRNA假说提出的历程,讨论了ceRNA调控网络的影响因素,并提出了一些有待进一步完善的内容.ceRNA假说大大拓展了人类基因组中功能遗传信息的范畴,也为解析一些人类疾病发生的机制提供了新线索.     

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.