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dc.contributor.authorNan Jiangen_US
dc.contributor.authorXinzhuo Zhangen_US
dc.contributor.authorDalian Qinen_US
dc.contributor.authorJing Yangen_US
dc.contributor.authorAnguo Wuen_US
dc.contributor.authorLong Wangen_US
dc.contributor.authorYueshan Sunen_US
dc.contributor.authorHong Lien_US
dc.contributor.authorXin Shenen_US
dc.contributor.authorJing Linen_US
dc.contributor.authorFahsai Kantawongen_US
dc.contributor.authorJianming Wuen_US
dc.date.accessioned2022-10-16T07:02:17Z-
dc.date.available2022-10-16T07:02:17Z-
dc.date.issued2021-02-23en_US
dc.identifier.issn16648021en_US
dc.identifier.other2-s2.0-85102384527en_US
dc.identifier.other10.3389/fgene.2021.608017en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85102384527&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/75724-
dc.description.abstractBackground: Hepatocellular carcinoma (HCC) is one of the most leading causes of cancer death with a poor prognosis. However, the underlying molecular mechanisms are largely unclear, and effective treatment for it is limited. Using an integrated bioinformatics method, the present study aimed to identify the key candidate prognostic genes that are involved in HCC development and identify small-molecule drugs with treatment potential. Methods and Results: In this study, by using three expression profile datasets from Gene Expression Omnibus database, 1,704 differentially expressed genes were identified, including 671 upregulated and 1,033 downregulated genes. Then, weighted co-expression network analysis revealed nine modules are related with pathological stage; turquoise module was the most associated module. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway analyses (KEGG) indicated that these genes were enriched in cell division, cell cycle, and metabolic related pathways. Furthermore, by analyzing the turquoise module, 22 genes were identified as hub genes. Based on HCC data from gene expression profiling interactive analysis (GEPIA) database, nine genes associated with progression and prognosis of HCC were screened, including ANLN, BIRC5, BUB1B, CDC20, CDCA5, CDK1, NCAPG, NEK2, and TOP2A. According to the Human Protein Atlas and the Oncomine database, these genes were highly upregulated in HCC tumor samples. Moreover, multivariate Cox regression analysis showed that the risk score based on the gene expression signature of these nine genes was an independent prognostic factor for overall survival and disease-free survival in HCC patients. In addition, the candidate small-molecule drugs for HCC were identified by the CMap database. Conclusion: In conclusion, the nine key gene signatures related to HCC progression and prognosis were identified and validated. The cell cycle pathway was the core pathway enriched with these key genes. Moreover, several candidate molecule drugs were identified, providing insights into novel therapeutic approaches for HCC.en_US
dc.subjectBiochemistry, Genetics and Molecular Biologyen_US
dc.subjectMedicineen_US
dc.titleIdentification of Core Genes Related to Progression and Prognosis of Hepatocellular Carcinoma and Small-Molecule Drug Predicationen_US
dc.typeJournalen_US
article.title.sourcetitleFrontiers in Geneticsen_US
article.volume12en_US
article.stream.affiliationsLuzhou Medical Collegeen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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