Comprehensive analysis of circRNA expression profiles and circRNA-associated competing endogenous RNA networks in IgA nephropathy

Background Immunoglobulin A nephropathy (IgAN) is immune-mediated primary glomerulonephritis, which is the most common reason leading to renal failure worldwide. The exact pathogenesis of IgAN is not well defined. Accumulating evidence indicates that circular RNAs (circRNAs) play crucial roles in the immune disease by involving in the competing endogenous RNA (ceRNA) network mechanism. At present, the studies of the circRNA profiles and circRNA-associated ceRNA networks in the IgAN are still scarce. This study aimed to elucidate the potential roles of circRNA-associated ceRNA networks of peripheral blood mononuclear cells (PBMCs) in IgAN patients Method CircRNA sequencing was used to identify the differential expressed circRNAs (DEcircRNAs) of PBMCs in IgAN and healthy controls; limma packages from data sets GSE25590 and GSE73953 in the Gene Expression Omnibus (GEO) database, were used to identify differentially expressed micro RNAs (miRNAs) and message RNAs (mRNAs). A circRNA-miRNA-mRNA ceRNA network was constructed to further investigate the mechanisms of IgAN. Then, GO analysis and KEGG enrichment analyses were used to annotate the genes involved in the circRNA-associated ceRNA network. Further, Protein-protein interaction (PPI) networks were established to screen potential hub genes, by using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Last, a quantitative real-time polymerase chain reaction (qRT-PCR) was applied to verify the hub genes in the ceRNA network. Result A total of 145 circRNAs, 22 miRNAs, and 1,117 mRNAs were differentially expressed in IgAN compared with controls (P < 0.05). A ceRNA network was constructed which contained 16 DEcircRNAs, 72 differential expressed mRNAs (DEmRNAs) and 11 differential expressed miRNAs (DEmiRNAs). KEGG pathway enrichment analysis illustrated the underlying biological functions of the ceRNA-associated genes, such as Nitrogen compound metabolic process, COPII-coated ER to Golgi transport vesicle, CAMP response element protein binding process (P < 0.01); meanwhile, Hepatitis B, GnRH signaling, and Prion disease were the most significant enrichment GO terms (P < 0.01). PPI network based on STRING analysis identified 4 potentially hub genes. Finally, Ankyrin repeat and SOCS box containing 16 (ASB16), SEC24 homolog C, COPII coat complex component (SEC24C) were confirmed by qRT-PCR (P < 0.05) and were identified as the hub genes of the ceRNA network in our study. Conclusion Our study identified a novel circRNA-mediated ceRNA regulatory network mechanisms in the pathogenesis of IgAN.

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Comprehensive analysis of an lncRNA-miRNA-mRNA competing endogenous RNA network in pulpitis

PeerJ ◽

10.7717/peerj.7135 ◽

2019 ◽

Vol 7 ◽

pp. e7135 ◽

Cited By ~ 5

Author(s):

Fangcao Lei ◽

Han Zhang ◽

Xiaoli Xie

Keyword(s):

Differentially Expressed Genes ◽

Protein Interaction ◽

Dental Pulp ◽

Expression Profiles ◽

Differentially Expressed ◽

Hub Genes ◽

Regulatory Relationship ◽

Protein Protein Interaction ◽

Qrt Pcr ◽

Ppi Networks

Background Pulpitis is a common inflammatory disease that affects dental pulp. It is important to understand the molecular signals of inflammation and repair associated with this process. Increasing evidence has revealed that long noncoding RNAs (lncRNAs), via competitively sponging microRNAs (miRNAs), can act as competing endogenous RNAs (ceRNAs) to regulate inflammation and reparative responses. The aim of this study was to elucidate the potential roles of lncRNA, miRNA and messenger RNA (mRNA) ceRNA networks in pulpitis tissues compared to normal control tissues. Methods The oligo and limma packages were used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs, respectively) based on expression profiles in two datasets, GSE92681 and GSE77459, from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were further analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein–protein interaction (PPI) networks and modules were established to screen hub genes using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the Molecular Complex Detection (MCODE) plugin for Cytoscape, respectively. Furthermore, an lncRNA-miRNA-mRNA-hub genes regulatory network was constructed to investigate mechanisms related to the progression and prognosis of pulpitis. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was applied to verify critical lncRNAs that may significantly affect the pathogenesis in inflamed and normal human dental pulp. Results A total of 644 upregulated and 264 downregulated differentially expressed genes (DEGs) in pulpitis samples were identified from the GSE77459 dataset, while 8 up- and 19 downregulated probes associated with lncRNA were identified from the GSE92681 dataset. Protein–protein interaction (PPI) based on STRING analysis revealed a network of DEGs containing 4,929 edges and 623 nodes. Upon combined analysis of the constructed PPI network and the MCODE results, 10 hub genes, including IL6, IL8, PTPRC, IL1B, TLR2, ITGAM, CCL2, PIK3CG, ICAM1, and PIK3CD, were detected in the network. Next, a ceRNA regulatory relationship consisting of one lncRNA (PVT1), one miRNA (hsa-miR-455-5p) and two mRNAs (SOCS3 and PLXNC1) was established. Then, we constructed the network in which the regulatory relationship between ceRNA and hub genes was summarized. Finally, our qRT-PCR results confirmed significantly higher levels of PVT1 transcript in inflamed pulp than in normal pulp tissues (p = 0.03). Conclusion Our study identified a novel lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of pulpitis.

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Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

10.21203/rs.3.rs-1023446/v1 ◽

2021 ◽

Author(s):

Li Guoquan ◽

Du Junwei ◽

He Qi ◽

Fu Xinghao ◽

Ji Feihong ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Inflammatory Responses ◽

Expression Profiles ◽

Treatment Options ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Chronic Lymphocytic Thyroiditis ◽

Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

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A Comprehensive Data Analysis of Differentially Regulated Genes in Melanoma

10.21203/rs.3.rs-19035/v1 ◽

2020 ◽

Author(s):

Yanjie Han ◽

Xinxin Li ◽

Jiliang Yan ◽

Chunyan Ma ◽

Xin Wang ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Growth Factor Receptor ◽

Principal Component ◽

Distant Metastases ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Hub Genes ◽

Ppi Networks

Abstract Background: Melanoma is the most deadly tumor in skin tumors and is prone to distant metastases. The incidence of melanoma has increased rapidly in the past few decades, and current trends indicate that this growth is continuing. This study was aimed to explore the molecular mechanisms of melanoma pathogenesis and discover underlying pathways and genes associated with melanoma.Methods: We used high-throughput expression data to study differential expression profiles of related genes in melanoma. The differentially expressed genes (DEGs) of melanoma in GSE15605, GSE46517, GSE7553 and the Cancer Genome Atlas (TCGA) datasets were analyzed. Differentially expressed genes (DEGs) were identified by paired t-test. Then the DEGs were performed cluster and principal component analyses and protein–protein interaction (PPI) network construction. After that, we analyzed the differential genes through bioinformatics and got hub genes. Finally, the expression of hub genes was confirmed in the TCGA databases and collected patient tissue samples.Results: Total 144 up-regulated DEGs and 16 down-regulated DEGs were identified. A total of 17 gene ontology analysis (GO) terms and 11 pathways were closely related to melanoma. Pathway of pathways in cancer was enriched in 8 DEGs, such as junction plakoglobin (JUP) and epidermal growth factor receptor (EGFR). In the PPI networks, 9 hub genes were obtained, such as loricrin (LOR), filaggrin (FLG), keratin 5 (KRT5), corneodesmosin (CDSN), desmoglein 1 (DSG1), desmoglein 3 (DSG3), keratin 1 (KRT1), involucrin (IVL) and EGFR. The pathway of pathways in cancer and its enriched DEGs may play important roles in the process of melanoma. The hub genes of DEGs may become promising melanoma candidate genes. Five key genes FLG, DSG1, DSG3, IVL and EGFR were identified in the TCGA database and melanoma tissues.Conclusions: The results suggested that FLG, DSG1, DSG3, IVL and EGFR might play important roles and potentially be valuable in the prognosis and treatment of melanoma.

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Construction and Comprehensive Analysis of Dysregulated Long Noncoding RNA-Associated Competing Endogenous RNA Network in Moyamoya Disease

Computational and Mathematical Methods in Medicine ◽

10.1155/2020/2018214 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Xuefeng Gu ◽

Dongyang Jiang ◽

Yue Yang ◽

Peng Zhang ◽

Guoqing Wan ◽

...

Keyword(s):

Moyamoya Disease ◽

Cerebral Artery ◽

Regulatory Network ◽

Noncoding Rna ◽

Expression Profiles ◽

Differentially Expressed ◽

Competing Endogenous Rna ◽

Cerna Network ◽

And Control ◽

Control Samples

Background. Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by chronic progressive stenosis or occlusion of the bilateral internal carotid artery (ICA), the anterior cerebral artery (ACA), and the middle cerebral artery (MCA). MMD is secondary to the formation of an abnormal vascular network at the base of the skull. However, the etiology and pathogenesis of MMD remain poorly understood. Methods. A competing endogenous RNA (ceRNA) network was constructed by analyzing sample-matched messenger RNA (mRNA), long non-coding RNA (lncRNA), and microRNA (miRNA) expression profiles from MMD patients and control samples. Then, a protein-protein interaction (PPI) network was constructed to identify crucial genes associated with MMD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were employed with the DAVID database to investigate the underlying functions of differentially expressed mRNAs (DEmRNAs) involved in the ceRNA network. CMap was used to identify potential small drug molecules. Results. A total of 94 miRNAs, 3649 lncRNAs, and 2294 mRNAs were differentially expressed between MMD patients and control samples. A synergistic ceRNA lncRNA-miRNA-mRNA regulatory network was constructed. Core regulatory miRNAs (miR-107 and miR-423-5p) and key mRNAs (STAT5B, FOSL2, CEBPB, and CXCL16) involved in the ceRNA network were identified. GO and KEGG analyses indicated that the DEmRNAs were involved in the regulation of the immune system and inflammation in MMD. Finally, two potential small molecule drugs, CAY-10415 and indirubin, were identified by CMap as candidate drugs for treating MMD. Conclusions. The present study used bioinformatics analysis of candidate RNAs to identify a series of clearly altered miRNAs, lncRNAs, and mRNAs involved in MMD. Furthermore, a ceRNA lncRNA-miRNA-mRNA regulatory network was constructed, which provides insights into the novel molecular pathogenesis of MMD, thus giving promising clues for clinical therapy.

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Bioinformatics Analysis for Identifying Micro-RNAs, Long Noncoding RNAs, Transcription Factors, Immune Genes Regulatory Networks, and Potential Therapeutic Agents for Diabetic Cardiomyopathy Using an Integrated Bioinformatics Analysis

10.21203/rs.3.rs-1118638/v1 ◽

2021 ◽

Author(s):

Jiefang Zhou ◽

Xiaowei Ji ◽

Xiuwei Shen ◽

Kefeng Yan ◽

Peng Huang ◽

...

Keyword(s):

Gene Expression ◽

Signaling Pathways ◽

Diabetic Cardiomyopathy ◽

Bioinformatics Analysis ◽

Expression Profiles ◽

Therapeutic Agents ◽

Hub Genes ◽

Ppi Networks ◽

Micro Rnas ◽

Rna Interaction

Abstract Objectives We identified functional genes and studied the underlying molecular mechanisms of diabetic cardiomyopathy (DCM) using bioinformatics tools. Methods Original gene expression profiles were obtained from the GSE21610 and GSE112556 datasets. We used GEO2R to screen the differentially expressed genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on DEGs. Protein–protein interaction (PPI) networks of DEGs were constructed using STRING and hub genes of signaling pathways were identified using Cytoscape. Aberrant hub gene expression was verified using The Cancer Genome Atlas dataset. Connectivity Map was used to predict the drugs that could treat DCM. Results The DEGs in DCM were mainly enriched in the nuclei and cytoplasm and involved in DCM- and chemokine-related signaling pathways. In the PPI network, 32 nodes were chosen as hub nodes and an RNA interaction network was constructed with 517 interactions. The expression of key genes (JPIK3R1, CCR9, XIST, WDFY3.AS2, hsa-miR-144-5p, and hsa-miR-146b-5p) was significantly different between DCM and normal tissues. Danazol, ikarugamycin, and semustine were identified as therapeutic agents against DCM using CMAP. Conclusion The identified hub genes could be associated with DCM pathogenesis and the above drugs could be used for treating DCM.

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Identification of lncRNA–mRNA Regulatory Network Associated With Isolated Systolic Hypertension and Atherosclerotic Cerebral Infarction

10.21203/rs.3.rs-391143/v1 ◽

2021 ◽

Author(s):

jie Yang ◽

Yan-Nan Tao ◽

Fang-Xiao Hu ◽

Yong-Zhi Chen ◽

Xue-Song Yang ◽

...

Keyword(s):

Cerebral Infarction ◽

Regulatory Network ◽

Systolic Hypertension ◽

Expression Profiles ◽

Pearson Correlation ◽

Interaction Network ◽

Differentially Expressed ◽

Isolated Systolic Hypertension ◽

Hub Genes ◽

Qrt Pcr

Abstract Background: Increasing evidences uncover that lncRNAs play an important role in Isolated systolic hypertension (ISH). However, a systematic lncRNA-mRNA regulatory network is still absent in isolated systolic hypertension and atherosclerotic cerebral infarction patients (ISH & ACI).Aim:This research aims to establish a lncRNA-mRNA co-expression network in patients with ISH & ACI, to probe into the potential functions of lncRNA in those patients.Design and Setting:Expression profiles of lncRNA and mRNAs are collected and compared respectively from 8 patients with ISH and 8 patients with ISH & ACI by RNA-seq data.Methods: Differentially expressed lncRNAs and mRNAs were screened out via high-throughput sequencing in the plasma of ISH/ACI patients and control ISH patients. Then, a lncRNA-mRNA interaction network was built using the Pearson correlation coefficient by Cytoscape software. The expression levels of the hub genes and lncRNAs were verified by qRT-PCR in another 10 ISH/ACI patients and 10 control patients. Results: 2768 differentially expressed lncRNAs and 747 differentially expressed mRNAs were identified. 2 hub genes (CD226 and PARVB) and 11 lncRNAs were identified in the lncRNA-mRNA interaction network. qRT-PCR and cell assay results verified that lncRNAs ENST00000590604 and CD226 are highly expressed in patients of ISH & ACI. CD226 was associated with vascular endothelial cells growth and stability through platelet activation and focal adhesion pathway.Conclusion: We established a novel mRNA-lncRNA interaction network. lncRNAs ENST00000590604 and CD226 might be the potential biomarkers of ISH & ACI.

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Comprehensive analysis of DNA methylation and gene expression profiles in cholangiocarcinoma

Cancer Cell International ◽

10.1186/s12935-019-1080-y ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 2

Author(s):

Cheng Zhang ◽

Bingye Zhang ◽

Di Meng ◽

Chunlin Ge

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Differentially Expressed Genes ◽

Expression Profiles ◽

Functional Enrichment ◽

Differentially Expressed ◽

Hub Genes ◽

Ppi Networks ◽

Differentially Methylated Genes ◽

Tumorigenesis And Progression

Abstract Background The incidence of cholangiocarcinoma (CCA) has risen in recent years, and it has become a significant health burden worldwide. However, the mechanisms underlying tumorigenesis and progression of this disease remain largely unknown. An increasing number of studies have demonstrated crucial biological functions of epigenetic modifications, especially DNA methylation, in CCA. The present study aimed to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) involved in CCA tumorigenesis and progression by bioinformatics analysis. Methods The gene expression profiling dataset (GSE119336) and gene methylation profiling dataset (GSE38860) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified using the limma packages of R and GEO2R, respectively. The MeDEGs were obtained by overlapping the DEGs and DMGs. Functional enrichment analyses of these genes were then carried out. Protein–protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape to determine hub genes. Finally, the results were verified based on The Cancer Genome Atlas (TCGA) database. Results We identified 98 hypermethylated, downregulated genes and 93 hypomethylated, upregulated genes after overlapping the DEGs and DMGs. These genes were mainly enriched in the biological processes of the cell cycle, nuclear division, xenobiotic metabolism, drug catabolism, and negative regulation of proteolysis. The top nine hub genes of the PPI network were F2, AHSG, RRM2, AURKB, CCNA2, TOP2A, BIRC5, PLK1, and ASPM. Moreover, the expression and methylation status of the hub genes were significantly altered in TCGA. Conclusions Our study identified novel methylation-regulated differentially expressed genes (MeDEGs) and explored their related pathways and functions in CCA, which may provide novel insights into a further understanding of methylation-mediated regulatory mechanisms in CCA.

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An integrated analysis of the competing endogenous RNA network and co-expression network revealed seven hub long non-coding RNAs in osteoarthritis

Bone and Joint Research ◽

10.1302/2046-3758.93.bjr-2019-0140.r2 ◽

2020 ◽

Vol 9 (3) ◽

pp. 90-98 ◽

Cited By ~ 1

Author(s):

Haitao Chen ◽

Liaobin Chen

Keyword(s):

Extracellular Matrix ◽

Expression Profiles ◽

Osteoclast Differentiation ◽

Signalling Pathway ◽

Differentially Expressed ◽

Integrated Analysis ◽

Knee Cartilage ◽

Competing Endogenous Rna ◽

Cerna Network ◽

Non Coding Rnas

Aims This study aimed to uncover the hub long non-coding RNAs (lncRNAs) differentially expressed in osteoarthritis (OA) cartilage using an integrated analysis of the competing endogenous RNA (ceRNA) network and co-expression network. Methods Expression profiles data of ten OA and ten normal tissues of human knee cartilage were obtained from the Gene Expression Omnibus (GEO) database (GSE114007). The differentially expressed messenger RNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the edgeR package. We integrated human microRNA (miRNA)-lncRNA/mRNA interactions with DElncRNA/DEmRNA expression profiles to construct a ceRNA network. Likewise, lncRNA and mRNA expression profiles were used to build a co-expression network with the WGCNA package. Potential hub lncRNAs were identified based on an integrated analysis of the ceRNA network and co-expression network. StarBase and Multi Experiment Matrix databases were used to verify the lncRNAs. Results We detected 1,212 DEmRNAs and 49 DElncRNAs in OA and normal knee cartilage. A total of 75 dysregulated lncRNA-miRNA interactions and 711 dysregulated miRNA-mRNA interactions were obtained in the ceRNA network, including ten DElncRNAs, 69 miRNAs, and 72 DEmRNAs. Similarly, 1,330 dysregulated lncRNA-mRNA interactions were used to construct the co-expression network, which included ten lncRNAs and 407 mRNAs. We finally identified seven hub lncRNAs, named MIR210HG, HCP5, LINC00313, LINC00654, LINC00839, TBC1D3P1-DHX40P1, and ISM1-AS1. Subsequent enrichment analysis elucidated that these lncRNAs regulated extracellular matrix organization and enriched in osteoclast differentiation, the FoxO signalling pathway, and the tumour necrosis factor (TNF) signalling pathway in the development of OA. Conclusion The integrated analysis of the ceRNA network and co-expression network identified seven hub lncRNAs associated with OA. These lncRNAs may regulate extracellular matrix changes and chondrocyte homeostasis in OA progress. Cite this article: Bone Joint Res. 2020;9(3):90–98.

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Construction and Analysis of Competing Endogenous RNA Networks for Breast Cancer Based on TCGA Dataset

BioMed Research International ◽

10.1155/2020/4078596 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Xue Wang ◽

Chundi Gao ◽

Fubin Feng ◽

Jing Zhuang ◽

Lijuan Liu ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Metastasis ◽

Target Genes ◽

Expression Profiles ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Competing Endogenous Rna ◽

Cerna Network ◽

Competing Endogenous Rnas ◽

Tcga Dataset

Background. Long noncoding RNAs (lncRNAs) act as competing endogenous RNAs for microRNAs in cancer metastasis. However, the roles of lncRNA-mediated competing endogenous RNA (ceRNA) networks for breast cancer (BC) are still unclear. Material and Methods. The expression profiles of mRNAs, lncRNAs, and miRNAs with BC were extracted from The Cancer Genome Atlas database. Weighted gene coexpression network analysis was conducted to extract differentially expressed mRNAs (DEmRNAs) that might be core genes. Through miRWalk, TargetScan, and miRDB to predict the target genes, an abnormal lncRNA-miRNA-mRNA ceRNA network with BC was constructed. The survival possibilities of mRNAs, miRNAs, and lncRNAs for patients with BC were determined by Kaplan-Meier survival curves and Oncomine. Results. We identified 2134 DEmRNAs, 1059 differentially expressed lncRNAs (DElncRNAs), and 86 differentially expressed miRNAs (DEmiRNAs). We then compose a ceRNA network for BC, including 72 DElncRNAs, 8 DEmiRNAs, and 12 DEmRNAs. After verification, 2 lncRNAs (LINC00466, LINC00460), 1 miRNA (Hsa-mir-204), and 5 mRNAs (TGFBR2, CDH2, CHRDL1, FGF2, and CHL1) were meaningful as prognostic biomarkers for BC patients. In the ceRNA network, we found that three axes were present in 10 RNAs related to the prognosis of BC, namely, LINC00466-Hsa-mir-204-TGFBR2, LINC00466-Hsa-mir-204-CDH2, and LINC00466-Hsa-mir-204-CHRDL1. Conclusion. This study highlighted lncRNA-miRNA-mRNA ceRNA related to the pathogenesis of BC, which might be used for latent diagnostic biomarkers and therapeutic targets for BC.

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Comprehensive Analysis of Competing Endogenous RNA Network Focusing on Long Noncoding RNA Involved in Cirrhotic Hepatocellular Carcinoma

Analytical Cellular Pathology ◽

10.1155/2021/5510111 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Yuli Zhang ◽

Dinggui Chen ◽

Miaomiao Yang ◽

Xianfeng Qian ◽

Chunmei Long ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Survival Analysis ◽

Noncoding Rna ◽

Expression Profiles ◽

The Cancer Genome Atlas ◽

Prognostic Indicators ◽

Competing Endogenous Rna ◽

Regulatory Pathways ◽

Qrt Pcr ◽

Cerna Network

The role of long noncoding RNAs- (lncRNAs-) associated competing endogenous RNA (ceRNA) in the field of hepatocellular carcinoma (HCC) biology is well established, but the involvement of lncRNAs competing interactions in the progression of liver cirrhosis to HCC is still unclear. We aimed to explore the differential expression profiles of lncRNAs, microRNAs (miRNA), and messenger RNAs (mRNAs) to construct a functional ceRNA network in cirrhotic HCC. The lncRNA, miRNA, and mRNA expression datasets were obtained from Gene Expression Omnibus and The Cancer Genome Atlas. Based on miRanda and TargetScan, the HCC-specific ceRNA network was constructed to illustrate the coexpression regulatory relationship of lncRNAs, miRNAs, and mRNAs. The potential prognostic indicators in the network were confirmed by survival analysis and validated by qRT-PCR. A total of 74 lncRNAs, 36 intersection miRNAs, and 949 mRNAs were differentially expressed in cirrhotic HCC samples compared with cirrhosis samples. We constructed a ceRNA network, including 47 lncRNAs, 35 miRNAs, and 168 mRNAs. Survival analysis demonstrated that 2 lncRNAs (EGOT and SERHL), 4 miRNAs, and 40 mRNAs were significantly associated with the overall survival of HCC patients. Two novel regulatory pathways, EGOT-miR-32-5p-XYLT2 axis and SERHL-miR-1269a/miR-193b-3p-BCL2L1/SYK/ARNT/CHST3/LPCAT1 axis, were built up and contribute to the underlying mechanism of HCC pathogenesis. The higher-expressed SERHL was associated with a higher risk of all-cause death. The expressions of SERHL-miR-1269a-BCL2L1 were significantly different using qRT-PCR in vitro studies. lncRNAs EGOT and SERHL might serve as effective prognostic biomarkers and potential therapeutic targets in cirrhotic HCC treatment.

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