Identification of Core Genes Related to Progression and Prognosis of Hepatocellular Carcinoma and Small-Molecule Drug Predication

被引:6
作者
Jiang, Nan [1 ,2 ,3 ]
Zhang, Xinzhuo [3 ]
Qin, Dalian [4 ]
Yang, Jing [4 ]
Wu, Anguo [4 ]
Wang, Long [4 ]
Sun, Yueshan [4 ]
Li, Hong [4 ]
Shen, Xin [4 ]
Lin, Jing [4 ]
Kantawong, Fahsai [1 ]
Wu, Jianming [2 ]
机构
[1] Chiang Mai Univ, Fac Associated Med Sci, Dept Med Technol, Chiang Mai, Thailand
[2] Southwest Med Univ, Sch Pharm, Luzhou, Peoples R China
[3] Southwest Med Univ, Int Educ Sch, Luzhou, Peoples R China
[4] Southwest Med Univ, Key Lab Med Electrophysiol, Sichuan Key Med Lab New Drug Discovery & Drugabil, Educ Minist,Luzhou Key Lab Act Screening & Drugab, Luzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
hepatocellular carcinoma; prognosis; weighted gene co-expression network analysis; risk score; multivariate cox; CELL-CYCLE; SORAFENIB RESISTANCE; PHASE-II; CANCER; TANESPIMYCIN; EXPRESSION; COMBINATION; SURVIVIN; PROVIDES; GROWTH;
D O I
10.3389/fgene.2021.608017
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Background 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.
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页数:19
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