Identification of Differentially Expressed Genes Associated with the Prognosis and Diagnosis of Hepatocellular Carcinoma by Integrated Bioinformatics Analysis.
Objective. The goal of this study was to understand the possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis. Methods. GEO contains datasets of gene expression, miRNA, and methylation patterns of diseased and healthy/control patients. The GSE62232 dataset was...
| Publicado en: | BioMed Research International Vol. 2022; pp. 1 - 13 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
10/22/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159859636&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159859636 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 10/22/2022 vid: 2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 159859636 159859636 159859636 10.1155/2022/4237633 159859636 ppf: 1 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Identification of Differentially Expressed Genes Associated with the Prognosis and Diagnosis of Hepatocellular Carcinoma by Integrated Bioinformatics Analysis. aug: au: Kakar, Mohib Ullah Mehboob, Muhammad Zubair Akram, Muhammad Shah, Muddaser Shakir, Yasmeen Ijaz, Hafza Wajeeha Aziz, Ubair Ullah, Zahid Ahmad, Sajjad Ali, Sikandar Yin, Yongxiang affil: Beijing Key Laboratory for Separation and Analysis in Biomedicine and Pharmaceutical, School of life Sciences, Beijing Institute of Technology (BIT), Beijing 100081, China sug: subj: Gene Expression Carcinoma, Hepatocellular Diagnosis Carcinoma, Hepatocellular Prognosis Carcinoma, Hepatocellular Familial and Genetic Bioinformatics Human Health Care Delivery, Integrated MicroRNA Methylation Proteins Metabolism Tumor Markers, Biological Carcinoma, Hepatocellular Drug Therapy Antineoplastic Agents Therapeutic Use ab: Objective. The goal of this study was to understand the possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis. Methods. GEO contains datasets of gene expression, miRNA, and methylation patterns of diseased and healthy/control patients. The GSE62232 dataset was selected by employing the server Gene Expression Omnibus. A total of 91 samples were collected, including 81 HCC and 10 healthy samples as control. GSE62232 was analysed through GEO2R, and Functional Enrichment Analysis was performed to extract rational information from a set of DEGs. The Protein-Protein Relationship Networking search method has been used for extracting the interacting genes. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analysed using GEPIA to estimate the effect of their differential expression on cancer progression. Results. We identified the top 10 hub genes through CytoHubba plugin. These included BUB1, BUB1B, CCNB1, CCNA2, CCNB2, CDC20, CDK1 and MAD2L1, NCAPG, and NDC80. NCAPG and NDC80 reported for the first time in this study while the remaining from a recently reported literature. The pathogenesis of HCC may be directly linked with the aforementioned genes. In this analysis, we found critical genes for HCC that showed recommendations for future prognostic and predictive biomarkers studies that could promote selective molecular therapy for HCC. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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