4.4 Article

Identification of potential crucial genes associated with the pathogenesis and prognosis of liver hepatocellular carcinoma

期刊

JOURNAL OF CLINICAL PATHOLOGY
卷 74, 期 8, 页码 504-512

出版社

BMJ PUBLISHING GROUP
DOI: 10.1136/jclinpath-2020-206979

关键词

biomarkers; tumor; carcinoma; liver neoplasms

资金

  1. National Natural Science Foundation of China [81 873 190]

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This study identified genes involved in the pathophysiology of LIHC and biomarkers for predicting the prognosis of LIHC. Ten hub genes and a six gene prognosis signature were identified, which can effectively predict survival in LIHC patients. These findings are important for understanding the molecular basis of LIHC and guiding the development of treatments.
Aims Liver hepatocellular carcinoma (LIHC) is the main manifestation of primary liver cancer, with low survival rate and poor prognosis. Medical decision-making process of LIHC is so complex that new biomarkers for diagnosis and prognosis have yet to be explored, this study aimed to identify the genes involved in the pathophysiology of LIHC and biomarkers that can be used to predict the prognosis of LIHC. Methods Six Gene Expression Omnibus (GEO) datasets selected from GEO were screened and integrated to find out the differential expression genes (DEGs) obtained from LIHC and normal hepatic tissues. The Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analysis of DEGs was implemented by DAVID. The Protein-protein interaction network was performed via STRING. In addition, Cox regression model was used to construct a gene prognostic signature. Results We ascertained 10 hub genes, nine of them (CDK1, CDC20, CCNB1, Thymidylate synthetase, Nuclear division cycle80, NUF2, MAD2L1, CCNA2 and BIRC5) as biomarkers of progression in LIHC patients. We also build a six gene prognosis signature (SOCS2, GAS2L3, NLRP5, TAF3, UTP11 and GAGE2A), which can be implemented to predict over survival effectively. Conclusions We revealed promising genes that may participate in the pathophysiology of LIHC, and found available biomarkers for LIHC prognosis prediction, which were significant for researchers to further understand the molecular basis of LIHC and direct the synthesis medicine of LIHC.

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