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Candidate miRNAs and pathogenesis investigation for hepatocellular carcinoma based on bioinformatics analysis.

ABSTRACT: The present study aimed to explore the mechanisms behind the development and progression of hepatocellular carcinoma (HCC) and identify information regarding HCC-related microRNAs (miRNAs) or marker genes for the gene therapy of HCC. Gene expression profile of GSE67882, generated from 4 hepatitis B virus infected HCC tissue samples (HCC group) and 8 chronic hepatitis B tissue samples with no fibrosis (control group) were downloaded from the Gene Expression Omnibus database. The differentially expressed miRNAs functional enrichment and pathway analyses of HCC were revealed, followed by transcription factor-miRNA interaction network construction and analyses. A total of 14 upregulated miRNAs and 16 downregulated miRNAs between HCC and control samples were obtained. Differentially expressed miRNAs were mainly involved in biological processes like the regulation of histone H3-K9 methylation, and the KEGG pathways in cancer map05200 demonstrates their involvement in cancer. A total of 3 outstanding regulatory networks of miRNAs: hsa-miR-15a, hsa-miR-125b and hsa-miR-122 were revealed. A total of 11 differentially expressed miRNAs including hsa-miR-146p-5b that regulated the marker genes of HCC were explored. miRNAs such as hsa-miR-15a, hsa-miR-125b, hsa-miR-122 and hsa-miR-146b-5p may be new biomarkers for the gene therapy of HCC. Furthermore, histone H3-K9 methylation and other pathways in cancer observed in the KEGG map05200 may be closely related with the development of HCC.

SUBMITTER: Ding W

PROVIDER: S-EPMC5431310 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Candidate miRNAs and pathogenesis investigation for hepatocellular carcinoma based on bioinformatics analysis.

Ding Wenbin W Yang Haixia H Gong Shenchu S Shi Weixiang W Xiao Jing J Gu Jinhua J Wang Yilang Y He Bosheng B

Oncology letters 20170327 5

The present study aimed to explore the mechanisms behind the development and progression of hepatocellular carcinoma (HCC) and identify information regarding HCC-related microRNAs (miRNAs) or marker genes for the gene therapy of HCC. Gene expression profile of GSE67882, generated from 4 hepatitis B virus infected HCC tissue samples (HCC group) and 8 chronic hepatitis B tissue samples with no fibrosis (control group) were downloaded from the Gene Expression Omnibus database. The differentially ex ...[more]

PMID: 28521446

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Project description:Background and Objective: Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor of the digestive system worldwide. Chronic hepatitis B virus (HBV) infection and aflatoxin exposure are predominant causes of HCC in China, whereas hepatitis C virus (HCV) infection and alcohol intake are likely the main risk factors in other countries. It is an unmet need to recognize the underlying molecular mechanisms of HCC in China. Methods: In this study, microarray datasets (GSE84005, GSE84402, GSE101685, and GSE115018) derived from Gene Expression Omnibus (GEO) database were analyzed to obtain the common differentially expressed genes (DEGs) by R software. Moreover, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the protein-protein interaction (PPI) network was constructed, and hub genes were identified by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape, respectively. The hub genes were verified using Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Kaplan-Meier Plotter online databases were performed on the TCGA HCC dataset. Moreover, the Human Protein Atlas (HPA) database was used to verify candidate genes' protein expression levels. Results: A total of 293 common DEGs were screened, including 103 up-regulated genes and 190 down-regulated genes. Moreover, GO analysis implied that common DEGs were mainly involved in the oxidation-reduction process, cytosol, and protein binding. KEGG pathway enrichment analysis presented that common DEGs were mainly enriched in metabolic pathways, complement and coagulation cascades, cell cycle, p53 signaling pathway, and tryptophan metabolism. In the PPI network, three subnetworks with high scores were detected using the Molecular Complex Detection (MCODE) plugin. The top 10 hub genes identified were CDK1, CCNB1, AURKA, CCNA2, KIF11, BUB1B, TOP2A, TPX2, HMMR and CDC45. The other public databases confirmed that high expression of the aforementioned genes related to poor overall survival among patients with HCC. Conclusion: This study primarily identified candidate genes and pathways involved in the underlying mechanisms of Chinese HCC, which is supposed to provide new targets for the diagnosis and treatment of HCC in China.

Project description:BackgroudIt has been shown that aberrant expression of microRNAs (miRNAs) and transcriptional factors (TFs) is tightly associated with the development of HCC. Therefore, in order to further understand the pathogenesis of HCC, it is necessary to systematically study the relationship between the expression of miRNAs, TF and genes. In this study, we aim to identify the potential transcriptomic markers of HCC through analyzing common microarray datasets, and further establish the differential co-expression network of miRNAs-TF-mRNA to screen for key miRNAs as candidate diagnostic markers for HCC.MethodWe first downloaded the mRNA and miRNA expression profiles of liver cancer from the GEO database. After pretreatment, we used a linear model to screen for differentially expressed genes (DEGs) and miRNAs. Further, we used weighed gene co-expression network analysis (WGCNA) to construct the differential gene co-expression network for these DEGs. Next, we identified mRNA modules significantly related to tumorigenesis in this network, and evaluated the relationship between mRNAs and TFs by TFBtools. Finally, the key miRNA was screened out in the mRNA-TF-miRNA ternary network constructed based on the target TF of differentially expressed miRNAs, and was further verified with external data set.ResultsA total of 465 DEGs and 215 differentially expressed miRNAs were identified through differential genes expression analysis, and WGCNA was used to establish a co-expression network of DEGs. One module that closely related to tumorigenesis was obtained, including 33 genes. Next, a ternary network was constructed by selecting 256 pairs of mRNA-TF pairs and 100 pairs of miRNA-TF pairs. Network mining revealed that there were significant interactions between 18 mRNAs and 25 miRNAs. Finally, we used another independent data set to verify that miRNA hsa-mir-106b and hsa-mir-195 are good classifiers of HCC and might play key roles in the progression of HCC.ConclusionOur data indicated that two miRNAs-hsa-mir-106b and hsa-mir-195-are identified as good classifiers of HCC.

Project description:miR-15b-5p has frequently been reported to function as a biomarker in some malignancies; however, the function of miR-15b-5p in hepatocellular carcinoma (HCC) and its molecular mechanism are still not well understood. The present study was designed to confirm the clinical value of miR-15b-5p and further explore its underlying molecular mechanism. A comprehensive investigation of the clinical value of miR-15b-5p in HCC was investigated by data mining The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets as well as literature. In addition, intersected target genes of miR-15b-5p were predicted using the miRWalk database and differentially expressed genes of HCC from TCGA. Furthermore, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were carried out. Then, a protein-protein interaction network (PPI) was constructed to reveal the interactions between some hub target genes of miR-15b-5p. The miR-15b-5p expression level in HCC was predominantly overexpressed compared with non-HCC tissues samples (SMD=0.618, 95% CI: 0.207, 1.029; P<0.0001) based on 991 HCC and 456 adjacent non-HCC tissue samples. The pooled summary receiver operator characteristic (SROC) of miR-15b-5p was 0.81 (Q*=0.74), and the pooled sensitivity and specificity of miR-15b-5p in HCC were 72% (95% CI: 69-75%) and 68% (95% CI: 65-72%), respectively. Bioinformatically, 225 overlapping genes were selected as prospective target genes of miR-15b-5p in HCC, and profoundly enriched GO terms and KEGG pathway investigation in silico demonstrated that the target genes were associated with prostate cancer, proximal tubule bicarbonate reclamation, heart trabecula formation, extracellular space, and interleukin-1 receptor activity. Five genes (ACACB, RIPK4, MAP2K1, TLR4 and IGF1) were defined as hub genes from the PPI network. The high expression of miR-15b-5p could play an essential part in hepatocarcinogenesis through diverse regulation approaches.

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Candidate miRNAs and pathogenesis investigation for hepatocellular carcinoma based on bioinformatics analysis.

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Candidate miRNAs and pathogenesis investigation for hepatocellular carcinoma based on bioinformatics analysis.

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