Dataset Information

Bioinformatics Analysis of Domain 1 of HCV-Core Protein: Iran.

ABSTRACT: Hepatitis C virus (HCV) infection is a serious global health problem and a cause of chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma (HCC). Bioinformatics software has been an effective tool to study the HCV genome as well as core domains. Our research was based on employing several bioinformatics software applications to find important mutations in domain 1 of core protein in Iranian HCV infected samples from 2006 to 2017, and an investigation of general properties, B-cell and T-cell epitopes, modification sites, and structure of domain 1. Domain 1 sequences of 188 HCV samples isolated from 2006 to 2017, Iran, were retrieved from NCBI gene bank. Using several tools, all sequences were analyzed for determination of mutations, physicochemical analysis, B-cell epitopes prediction, T-cell and CTL epitopes prediction, post modification, secondary and tertiary structure prediction. Our analysis determined several mutations in some special positions (70, 90, 91, and 110) that are associated with HCC and hepatocarcinogenesis, efficacy of triple therapy and sustained virological response, and interaction between core and CCR6. Several B-cell, T-cell, and CTL epitopes were recognized. Secondary and tertiary structures were mapped fordomain1 and core proteins. Our study, as a first report, offered inclusive data about frequent mutation in HCV-core gene domain 1 in Iranian sequences that can provide helpful analysis on structure and function of domain 1 of the core gene.

SUBMITTER: Dehghani B

PROVIDER: S-EPMC7223762 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Bioinformatics Analysis of Domain 1 of HCV-Core Protein: Iran.

Dehghani Behzad B Hashempour Tayebeh T Hasanshahi Zahra Z Moayedi Javad J

International journal of peptide research and therapeutics 20190420 1

Hepatitis C virus (HCV) infection is a serious global health problem and a cause of chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma (HCC). Bioinformatics software has been an effective tool to study the HCV genome as well as core domains. Our research was based on employing several bioinformatics software applications to find important mutations in domain 1 of core protein in Iranian HCV infected samples from 2006 to 2017, and an investigation of general properties, B-cell and T ...[more]

PMID: 32435167

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Project description:Background Gastric cancer is the third leading cause of cancer-related mortality in China. Most patients with gastric cancer have no obvious early symptoms; thus, many of them are in the middle and late stages of gastric cancer at first diagnosis and miss the best treatment opportunity. Molecular targeted therapy is particularly important in changing this status quo. Methods Three microarray datasets (GSE29272, GSE33651, and GSE54129) were selected from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using GEO2R. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to analyze the functional features of these DEGs and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. The protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape software. The expressions of hub genes were evaluated based on Gene Expression Profiling Interactive Analysis (GEPIA). Moreover, we used the online Kaplan-Meier plotter survival analysis tool to evaluate the prognostic values of hub genes. The Target Scan database was used to predict microRNAs that could regulate the target gene, collagen type IV alpha 1 chain (COL4A1). The OncomiR database was used to analyze the expression levels of three microRNAs, as well as the relationships with tumor stage, grade, and prognosis. Results We identified 78 DEGs, including 53 upregulated genes and 25 downregulated genes. The DEGs were mainly enriched in extracellular matrix organization, extracellular structure organization, and response to wounding. Moreover, three KEGG pathways were markedly enriched, including focal adhesion, complement and coagulation cascades, and extracellular matrix (ECM)-receptor interaction. Among these 78 genes, we selected 10 hub genes. The overexpression levels of these hub genes were closely related to poor prognosis and the development of gastric cancer (except for COL3A1, LOX, and CXCL8). Moreover, we found that microRNA-29a-3p, miR-29b-3p, and miR-29c-3p were the potential microRNAs that could regulate the target gene, COL4A1. Conclusions Our results showed that FN1, COL1A1, TIMP1, COL1A2, SPARC, COL4A1, and SERPINE1 could contribute to the development of novel molecular targets and biomarker-driven treatments for gastric cancer.

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Bioinformatics Analysis of Domain 1 of HCV-Core Protein: Iran.

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Bioinformatics Analysis of Domain 1 of HCV-Core Protein: Iran.

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