scholarly journals Identifying Serum Exosomal-Associated lncRNA/circRNA-miRNA-mRNA Network in Coronary Heart Disease

2020 ◽  
Author(s):  
Jia Mao ◽  
Yufei Zhou ◽  
Licheng Lu ◽  
Ping Zhang ◽  
Runhua Ren ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Regulation Of Gene Expression ◽  
Cellular Protein ◽  
Functional Enrichment ◽  
Signal Pathways ◽  
Ppi Network ◽  
Hub Genes ◽  
Cerna Network ◽  
Normal Controls

Abstract Background: Accumulating evidence has indicated that the importance of noncoding RNAs and exosomes in coronary heart disease (CHD). However, the exosomal-associated competing endogenous RNA (ceRNA)-mediated regulatory mechanism in CHD is still unknown. The present study aimed to explore exosomal-associated ceRNA network in CHD.Methods: The dataset, including 6 CHD patients and 32 normal controls, were downloaded from the ExoRBase database. Differentially expressed mRNAs (DEMs), lncRNAs (DELs) and circRNAs (DECs) in the serum exosomes between CHD and normal controls were screened. MicroRNAs (miRNAs) targeting DEMs were predicted by Targetscan and miRanda, miRNAs targeting DELs and DECs were predicted with miRcode and starBase, respectively. The biological functions and related signal pathways of DEMs were analyzed using David and KOBAS database. Subsequently, the protein-protein interaction (PPI) network was established to screen out hub genes, enrichment analyses of hub genes were performed and the ceRNA network (lncRNA/circRNA-miRNA-mRNA) was constructed to elucidate ceRNA axes in CHD.Results: A total of 312 DEMs, 43 DELs and 85 DECs were identified between CHD patients and normal controls. Functional enrichment analysis showed that DEMs were significantly enriched in “chromatin silencing at rDNA”, “telomere organization”, “negative regulation of gene expression, epigenetic”. The PPI network analysis showed that 25 hub DEMs were closely related to CHD, of which, ubiquitin C (UBC) was the most important. The biological function of hub genes showed that they were mainly enriched in “cellular protein metabolic process”. The exosomal-associated ceRNA regulatory network incorporated 48 DEMs, 72 predicted miRNAs, 10 DELs and 15 DECs. LncRNA/circRNA-miRNA-mRNA interaction axes (RPL7AP11/hsa-miR-17-5p/UBC, RPL7AP11/hsa-miR-20b-5p/UBC) were obtained from the network. Conclusions: Our findings have provided a novel perspective on the potential roles of exosomal-associated ceRNA network regulating the pathogenesis of CHD.

scholarly journals Identifying Serum Exosomal-Associated lncRNA/circRNA-miRNA-mRNA Network in Coronary Heart Disease

2021 ◽  
Author(s):  
Jia Mao ◽  
Yufei Zhou ◽  
Licheng Lu ◽  
Ping Zhang ◽  
Runhua Ren ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Regulation Of Gene Expression ◽  
Cellular Protein ◽  
Functional Enrichment ◽  
Signal Pathways ◽  
Ppi Network ◽  
Hub Genes ◽  
Cerna Network ◽  
Normal Controls

Abstract Background: Accumulating evidence has indicated that the importance of noncoding RNAs and exosomes in coronary heart disease (CHD). However, the exosomal-associated competing endogenous RNA (ceRNA)-mediated regulatory mechanism in CHD is still unknown. The present study aimed to explore exosomal-associated ceRNA network in CHD.Methods: The dataset, including 6 CHD patients and 32 normal controls, were downloaded from the ExoRBase database. Differentially expressed mRNAs (DEMs), lncRNAs (DELs) and circRNAs (DECs) in the serum exosomes between CHD and normal controls were screened. MicroRNAs (miRNAs) targeting DEMs were predicted by Targetscan and miRanda, miRNAs targeting DELs and DECs were predicted with miRcode and starBase, respectively. The biological functions and related signal pathways of DEMs were analyzed using David and KOBAS database. Subsequently, the protein-protein interaction (PPI) network was established to screen out hub genes, enrichment analyses of hub genes were performed and the ceRNA network (lncRNA/circRNA-miRNA-mRNA) was constructed to elucidate ceRNA axes in CHD.Results: A total of 312 DEMs, 43 DELs and 85 DECs were identified between CHD patients and normal controls. Functional enrichment analysis showed that DEMs were significantly enriched in “chromatin silencing at rDNA”, “telomere organization”, “negative regulation of gene expression, epigenetic”. The PPI network analysis showed that 25 hub DEMs were closely related to CHD, of which, ubiquitin C (UBC) was the most important. The biological function of hub genes showed that they were mainly enriched in “cellular protein metabolic process”. The exosomal-associated ceRNA regulatory network incorporated 48 DEMs, 72 predicted miRNAs, 10 DELs and 15 DECs. LncRNA/circRNA-miRNA-mRNA interaction axes (RPL7AP11/hsa-miR-17-5p/UBC, RPL7AP11/hsa-miR-20b-5p/UBC) were obtained from the network. Conclusions: Our findings have provided a novel perspective on the potential roles of exosomal-associated ceRNA network regulating the pathogenesis of CHD.

scholarly journals Identifying a Serum Exosomal-Associated lncRNA/circRNA-miRNA-mRNA Network in Coronary Heart Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jia Mao ◽  
Yufei Zhou ◽  
Licheng Lu ◽  
Ping Zhang ◽  
Runhua Ren ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Regulation Of Gene Expression ◽  
Enrichment Analysis ◽  
Cellular Protein ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes ◽  
Cerna Network ◽  
Normal Controls

Background. Accumulating evidence supports the importance of noncoding RNAs and exosomes in coronary heart disease (CHD). However, exosomal-associated competing endogenous RNA- (ceRNA-) mediated regulatory mechanisms in CHD are largely unexplored. The present study aimed to explore exosomal-associated ceRNA networks in CHD. Methods. Data from 6 CHD patients and 32 normal controls were downloaded from the ExoRBase database. CHD and normal controls were compared by screening differentially expressed mRNAs (DEMs), lncRNAs (DELs), and circRNAs (DECs) in serum exosomes. MicroRNAs (miRNAs) targeting DEMs were predicted using the Targetscan and miRanda databases, and miRNAs targeted by DELs and DECs were predicted using the miRcode and starBase databases, respectively. The biological functions and related signaling pathways of DEMs were analyzed using the David and KOBAS databases. Subsequently, a protein-protein interaction (PPI) network was established to screen out on which hub genes enrichment analyses should be performed, and a ceRNA network (lncRNA/circRNA-miRNA-mRNA) was constructed to elucidate ceRNA axes in CHD. Results. A total of 312 DEMs, 43 DELs, and 85 DECs were identified between CHD patients and normal controls. Functional enrichment analysis showed that DEMs were significantly enriched in “chromatin silencing at rDNA,” “telomere organization,” and “negative regulation of gene expression, epigenetic.” PPI network analysis showed that 25 hub DEMs were closely related to CHD, of which ubiquitin C (UBC) was the most important. Hub genes were mainly enriched in “cellular protein metabolic process” functions. The exosomal-associated ceRNA regulatory network incorporated 48 DEMs, 73 predicted miRNAs, 10 DELs, and 15 DECs. The LncRNA/circRNA-miRNA-mRNA interaction axes (RPL7AP11/hsa-miR-17-5p/UBC and RPL7AP11/hsa-miR-20b-5p/UBC) were obtained from the network. Conclusions. Our findings provide a novel perspective on the potential role of exosomal-associated ceRNA network regulation of the pathogenesis of CHD.

scholarly journals Identification of Potentially Functional Circular RNAs hsa_circ_0070934 and hsa_circ_0004315 as Prognostic Factor of Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

2021 ◽  
Author(s):  
Pejman Morovat ◽  
Saman Morovat ◽  
Arash M. Ashrafi ◽  
Shahram Teimourian
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Prognostic Factor ◽  
Sequence Data ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Circular Rnas ◽  
Ppi Network ◽  
Hub Genes ◽  
Cerna Network

Abstract Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, which has a high mortality rate and poor treatment outcomes with yet unknown molecular basis. It seems that gene expression plays a pivotal role in the pathogenesis of the disease. Circular RNAs (circRNAs) can interact with microRNAs (miRNAs) to regulate gene expression in various malignancies by acting as competitive endogenous RNAs (ceRNAs). However, the potential pathogenesis roles of the ceRNA network among circRNA/miRNA/mRNA in HCC are unclear. In this study, first, the HCC circRNA expression data were obtained from three Gene Expression Omnibus microarray datasets (GSE164803, GSE94508, GSE97332), and the differentially expressed circRNAs (DECs) were identified using R limma package. Also, the liver hepatocellular carcinoma (LIHC) miRNA and mRNA sequence data were retrieved from TCGA, and differentially expressed miRNAs (DEMIs) and mRNAs (DEGs) were determined using the R DESeq2 package. Second, CSCD website was used to uncover the binding sites of miRNAs on DECs. The DECs' potential target miRNAs were revealed by conducting an intersection between predicted miRNAs from CSCD and downregulated DEMIs. Third, some related genes were uncovered by intersecting targeted genes predicted by miRWalk and targetscan online tools with upregulated DEGs. The ceRNA network was then built using the Cytoscape software. The functional enrichment and the overall survival time of these potential targeted genes were analyzed, and a PPI network was constructed in the STRING database. Network visualization was performed by Cytoscape, and ten hub genes were detected using the CytoHubba plugin tool. Four DECs (hsa_circ_0000520, hsa_circ_0008616, hsa_circ_0070934, hsa_circ_0004315) were obtained and six miRNAs (hsa-miR-542-5p, hsa-miR-326, hsa-miR-511-5p, hsa-miR-195-5p, hsa-miR-214-3p, and hsa-miR-424-5p) which are regulated by the above DECs were identified. Then 543 overlapped genes regulated by six miRNAs mentioned above were predicted. Functional enrichment analysis showed that these genes are mostly associated with cancer regulation functions. Ten hub genes (TTK،AURKB, KIF20A، KIF23، CEP55، CDC6، DTL، NCAPG، CENPF، PLK4) have been screened from the PPI network of the 204 survival-related genes. KIF20A, NCAPG, TTK, PLK4, and CDC6 were selected for the highest significant p-values. In the end, a circRNA-miRNA-mRNA regulatory axis was established for five final selected hub genes. This study implies the potential pathogenesis of the obtained network and proposes that the two DECs (has_circ_0070934 and has_circ_0004315) may be important prognostic factor for HCC.

scholarly journals Pharmacological Network Reveals the Active Mechanism of Qi-Replenishing, Spleen-Strengthening, Phlegm-Dispelling, and Blood-Nourishing Fufang on Coronary Heart Disease

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Fan Zhang ◽  
Yue Liu ◽  
Sicheng Zheng ◽  
Boyi Dang ◽  
Jianan Wang ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Signaling Pathway ◽  
Salvia Miltiorrhiza ◽  
Functional Enrichment ◽  
Tanshinone Iia ◽  
Ppi Network ◽  
Active Components ◽  
Active Compounds ◽  
Magnesium Lithospermate B

This study aimed to investigate the potential targets and pathways of qi-replenishing, spleen-strengthening, phlegm-dispelling, and blood-nourishing Fufang in the treatment of coronary heart disease (CHD). The composition of Fufang was identified, followed by screening of the active components using ADME. The targets of active components were predicted and screened based on the TCMSP and BATMAN databases and were cross-validated using the CTD database and DisGeNET. A functional enrichment analysis was performed using the ClueGO + CluePedia plugins and clusterProfiler in the R package. The protein-protein interaction (PPI) network was constructed using the STRING database and Cytoscape. Finally, a pharmacological network was constructed. A total of 27 overlapping targets were obtained after cross-validation. ALB, IL-6, and TNF were the hub genes in the PPI network. The pharmacological network included 59 nodes and 189 relation pairs. Among the 59 nodes, there were 2 herbal medicine nodes (Salvia miltiorrhiza and Astragalus mongholicus), 8 chemical component nodes (magnesium lithospermate B, neocryptotanshinone II, heteratisine, daphneolone, tanshinone IIA, tanshinone IIB, soyasapogenol B, and astragaloside II), 27 target protein nodes (such as ALB, TNF, IL-6, NFKB1, APOA1, APOA2, CYP1A1, and CYP1A2), and 22 pathway nodes (such as the toll-like receptor signaling pathway, IL-17 signaling pathway, and TNF signaling pathway). Therefore, we found that the genes TNF, IL-6, NFKB1, ALB, CYP1A1, CYP1A2, APOA1, and APOA2 might be important targets of the key active compounds neocryptotanshinone II and astragaloside II. These genes targeted by the key active compounds might regulate inflammation-related pathways and the level of albumin and cholesterol in CHD.

Abstract 62: Molecular Basis of Regulatory Variation at Coronary Heart Disease-Associated Loci

2015 ◽  
Vol 35 (suppl_1) ◽  
Author(s):  
Clint L Miller ◽  
Milos Pjanic ◽  
Jonathan D Lee ◽  
Boxiang Liu ◽  
William J Greenleaf ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Chromatin Immunoprecipitation ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Regulatory Mechanisms ◽  
Tgf Beta ◽  
Genome Wide ◽  
Context Specific ◽  
Accessible Chromatin

Genome-wide association studies have identified 46 replicated genetic loci for coronary heart disease (CHD), and 104 loci associated at a 5% false discovery rate. However, the regulatory mechanisms of these associations largely remain elusive. Given that the majority of these CHD-associated loci reside in non-coding regions, they are predicted to function via context-specific gene regulation. Recent high-throughput assays of regulatory function include the assay for transposase-accessible chromatin using sequencing (ATAC-seq) and chromatin immunoprecipitation-sequencing (ChIP-seq). ATAC-seq utilizes a Tn5 transposase to fragment and tag accessible DNA sequences, which are often coupled to transcription factor occupancy identified by ChIP-seq. Importantly, this assay may reveal the spatio-temporal regulatory profiles in limited numbers of primary cells. Using ATAC-seq in human coronary artery smooth muscle cells (HCASMC) we identified 147,173 accessible chromatin peaks in control versus 198,976 peaks in TGF-beta-stimulated cells (136,446 shared peaks). Using de novo motif enrichment analysis we identified significant enrichment of specific AP-1 family members (29.2% vs. 5.1% background), chromatin remodeling, and SMC differentiation transcription factors. Using functional enrichment analysis of ChIP-seq and CHD-overlapping regions we observed enrichment of the hypoxia inducible factor 1 (HIF-1) and TGF-beta signaling pathways (1.5x10 -22 and 5.6x10 -18 , respectively) and relevant phenotypes, including cell migration and blood vessel morphology. Finally, we utilized these regulatory maps to explore the causal mechanisms underlying CHD-associated variants at four loci using haplotype-specific chromatin immunoprecipitation (haploChIP) and luciferase reporter assays. Taken together, these results suggest that genome-wide approaches such as ATAC-seq can be leveraged to map context-specific regulatory mechanisms of non-coding variants associated with complex diseases such as CHD, and reveal new biological and molecular insights into targeting heritable disease risk.

scholarly journals Identification of differentially expressed genes between the colon and ileum of patients with inflammatory bowel disease by gene co-expression analysis

2019 ◽  
Vol 48 (5) ◽  
pp. 030006051988726
Author(s):  
Yuting Zhang ◽  
Bo Shen ◽  
Liya Zhuge ◽  
Yong Xie
Keyword(s):  
Inflammatory Bowel Disease ◽  
Differentially Expressed Genes ◽  
Bowel Disease ◽  
Gene Expression Pattern ◽  
Functional Enrichment ◽  
Wilcoxon Test ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Hub Genes ◽  
Inflammatory Bowel

Objective We aimed to identify differentially expressed genes (DEG) in patients with inflammatory bowel disease (IBD). Methods RNA-seq data were obtained from the Array Express database. DEG were identified using the edgeR package. A co-expression network was constructed and key modules with the highest correlation with IBD inflammatory sites were identified for analysis. The Cytoscape MCODE plugin was used to identify key sub-modules of the protein–protein interaction (PPI) network. The genes in the sub-modules were considered hub genes, and functional enrichment analysis was performed. Furthermore, we constructed a drug–gene interaction network. Finally, we visualized the hub gene expression pattern between the colon and ileum of IBD using the ggpubr package and analyzed it using the Wilcoxon test. Results DEG were identified between the colon and ileum of IBD patients. Based on the co-expression network, the green module had the highest correlation with IBD inflammatory sites. In total, 379 DEG in the green module were identified for the PPI network. Nineteen hub genes were differentially expressed between the colon and ileum. The drug–gene network identified these hub genes as potential drug targets. Conclusion Nineteen DEG were identified between the colon and ileum of IBD patients.

scholarly journals Bioinformatics analysis reveals novel hub gene pathways associated with IgA nephropathy

2020 ◽  
Vol 25 (1) ◽  
Author(s):  
Xue Jiang ◽  
Zhijie Xu ◽  
Yuanyuan Du ◽  
Hongyu Chen
Keyword(s):  
Gene Ontology ◽  
Inflammatory Response ◽  
Molecular Mechanism ◽  
Bioinformatics Analysis ◽  
Functional Enrichment ◽  
Control Group ◽  
Integrin Subunit ◽  
Ppi Network ◽  
Hub Genes ◽  
Ppi Networks

Abstract Background Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulopathy worldwide. However, the molecular events underlying IgAN remain to be fully elucidated. This study aimed to identify novel biomarkers of IgAN through bioinformatics analysis and elucidate the possible molecular mechanism. Methods Based on the microarray datasets GSE93798 and GSE37460 downloaded from the Gene Expression Omnibus database, the differentially expressed genes (DEGs) between IgAN samples and normal controls were identified. Using the DEGs, we further performed a series of functional enrichment analyses. Protein–protein interaction (PPI) networks of the DEGs were constructed using the STRING online search tool and were visualized using Cytoscape. Next, hub genes were identified and the most important module among the DEGs, Biological Networks Gene Ontology tool (BiNGO), was used to elucidate the molecular mechanism of IgAN. Results In total, 148 DEGs were identified, comprising 53 upregulated genes and 95 downregulated genes. Gene Ontology (GO) analysis indicated that the DEGs for IgAN were mainly enriched in extracellular exosome, region and space, fibroblast growth factor stimulus, inflammatory response, and innate immunity. Module analysis showed that genes in the top 1 significant module of the PPI network were mainly associated with innate immune response, integrin-mediated signaling pathway and inflammatory response. The top 10 hub genes were constructed in the PPI network, which could well distinguish the IgAN and control group in monocyte and tissue samples. We finally identified the integrin subunit beta 2 (ITGB2) and Fc fragment of IgE receptor Ig (FCER1G) genes that may play important roles in the development of IgAN. Conclusions We identified key genes along with the pathways that were most closely related to IgAN initiation and progression. Our results provide a more detailed molecular mechanism for the development of IgAN and novel candidate gene targets of IgAN.

scholarly journals Identification of key genes, pathways and potential therapeutic agents for IgA nephropathy using an integrated bioinformatics analysis

2020 ◽  
Vol 21 (2) ◽  
pp. 147032032091963
Author(s):  
Xiaoxue Chen ◽  
Mindan Sun
Keyword(s):  
Differentially Expressed Genes ◽  
Immunoglobulin A ◽  
Therapeutic Targets ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Signal Pathways ◽  
Immunoglobulin A Nephropathy ◽  
Hub Genes ◽  
Limma Package

Purpose: This study aims to identify immunoglobulin-A-nephropathy-related genes based on microarray data and to investigate novel potential gene targets for immunoglobulin-A-nephropathy treatment. Methods: Immunoglobulin-A-nephropathy chip data was obtained from the Gene Expression Omnibus database, which included 10 immunoglobulin-A-nephropathy and 22 normal samples. We used the limma package of R software to screen differentially expressed genes in immunoglobulin-A-nephropathy and normal glomerular compartment tissues. Functional enrichment (including cellular components, molecular functions, biological processes) and signal pathways were performed for the differentially expressed genes. The online analysis database (STRING) was used to construct the protein-protein interaction networks of differentially expressed genes, and Cytoscape software was used to identify the hub genes of the signal pathway. In addition, we used the Connectivity Map database to predict possible drugs for the treatment of immunoglobulin-A-nephropathy. Results: A total of 348 differentially expressed genes were screened including 107 up-regulated and 241 down-regulated genes. Functional analysis showed that up-regulated differentially expressed genes were mainly concentrated on leukocyte migration, and the down-regulated differentially expressed genes were significantly enriched in alpha-amino acid metabolic process. A total of six hub genes were obtained: JUN, C3AR1, FN1, AGT, FOS, and SUCNR1. The small-molecule drugs thapsigargin, ciclopirox and ikarugamycin were predicted therapeutic targets against immunoglobulin-A-nephropathy. Conclusion: Differentially expressed genes and hub genes can contribute to understanding the molecular mechanism of immunoglobulin-A-nephropathy and providing potential therapeutic targets and drugs for the diagnosis and treatment of immunoglobulin-A-nephropathy.

scholarly journals Integrated analysis identifies a pathway-related competing endogenous RNA network in the progression of pancreatic cancer

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Fuqiang Zu ◽  
Peng Liu ◽  
Huaitao Wang ◽  
Ting Zhu ◽  
Jian Sun ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Tumor Formation ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Competing Endogenous Rna ◽  
Hub Genes ◽  
Cerna Network ◽  
Competing Endogenous Rna Network

Abstract Background It is well acknowledged that cancer-related pathways play pivotal roles in the progression of pancreatic cancer (PC). Employing Integrated analysis, we aim to identify the pathway-related ceRNA network associated with PC progression. Methods We divided eight GEO datasets into three groups according to their platform, and combined TCGA and GTEx databases as a group. Additionally, we screened out the differentially expressed genes (DEGs) and performed functional enrichment analysis in each group, and recognized the top hub genes in the most enriched pathway. Furthermore, the upstream of miRNAs and lncRNAs were predicted and validated according to their expression and prognostic roles. Finally, the co-expression analysis was applied to identify a pathway-related ceRNA network in the progression of PC. Results A total of 51 significant pathways that common enriched in all groups were spotted. Enrichment analysis indicated that pathway in cancer was greatly linked with tumor formation and progression. Next, the top 20 hug genes in this pathway were recognized, and stepwise prediction and validation from mRNA to lncRNA, including 11 hub genes, 4 key miRNAs, and 2 key lncRNAs, were applied to identify a meaningful ceRNA network according to ceRNA rules. Ultimately, we identified the PVT1/miR-20b/CCND1 axis as a promising pathway-related ceRNA axis in the progression of PC. Conclusion Overall, we elucidate the pathway-related ceRNA regulatory network of PVT1/miR-20b/CCND1 in the progression of PC, which can be considered as therapeutic targets and encouraging prognostic biomarkers for PC.

scholarly journals Identification of Potentially Therapeutic Target Genes of Hepatocellular Carcinoma

2020 ◽  
Vol 17 (3) ◽  
pp. 1053
Author(s):  
Chengzhang Li ◽  
Jiucheng Xu
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Expression Profiles ◽  
Differential Expression Analysis ◽  
Gene Expression Profiles ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes ◽  
Gene Differential Expression ◽  
Oncomine Database

Background: Hepatocellular carcinoma (HCC) is a major threat to public health. However, few effective therapeutic strategies exist. We aimed to identify potentially therapeutic target genes of HCC by analyzing three gene expression profiles. Methods: The gene expression profiles were analyzed with GEO2R, an interactive web tool for gene differential expression analysis, to identify common differentially expressed genes (DEGs). Functional enrichment analyses were then conducted followed by a protein-protein interaction (PPI) network construction with the common DEGs. The PPI network was employed to identify hub genes, and the expression level of the hub genes was validated via data mining the Oncomine database. Survival analysis was carried out to assess the prognosis of hub genes in HCC patients. Results: A total of 51 common up-regulated DEGs and 201 down-regulated DEGs were obtained after gene differential expression analysis of the profiles. Functional enrichment analyses indicated that these common DEGs are linked to a series of cancer events. We finally identified 10 hub genes, six of which (OIP5, ASPM, NUSAP1, UBE2C, CCNA2, and KIF20A) are reported as novel HCC hub genes. Data mining the Oncomine database validated that the hub genes have a significant high level of expression in HCC samples compared normal samples (t-test, p < 0.05). Survival analysis indicated that overexpression of the hub genes is associated with a significant reduction (p < 0.05) in survival time in HCC patients. Conclusions: We identified six novel HCC hub genes that might be therapeutic targets for the development of drugs for some HCC patients.

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