Identification of Prognostic Biomarkers and Correlation With Immune Infiltrates in Hepatocellular Carcinoma Based on a Competing Endogenous RNA Network

被引:4
作者
Pu, Zhangya [1 ]
Zhu, Yuanyuan [2 ]
Wang, Xiaofang [1 ]
Zhong, Yun [1 ]
Peng, Fang [1 ,2 ]
Zhang, Yiya [3 ,4 ]
机构
[1] Cent South Univ, Xiangya Hosp, Hunan Key Lab Viral Hepatitis, Dept Infect Dis, Changsha, Peoples R China
[2] Cent South Univ, Xiangya Hosp, NHC Key Lab Canc Prote, Changsha, Peoples R China
[3] Cent South Univ, Xiangya Hosp, Natl Clin Res Ctr Geriatr Disorders, Changsha, Peoples R China
[4] Xiangya Hosp, Dept Dermatol, Changsha, Peoples R China
关键词
hepatocellular carcinoma; competing endogenous RNA network; immune infiltration; prognostic prediction model; biomarkers; CELL-PROLIFERATION; CANCER-CELL; RESOURCE;
D O I
10.3389/fgene.2021.591623
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 common malignant tumors worldwide. Recently, competing endogenous RNAs (ceRNA) have revealed a significant role in the progression of HCC. Herein, we aimed to construct a ceRNA network to identify potential biomarkers and illustrate its correlation with immune infiltration in HCC. Methods RNA sequencing data and clinical traits of HCC patients were downloaded from TCGA. The limma R package was used to identify differentially expressed (DE) RNAs. The predicted prognostic model was established using univariate and multivariate Cox regression. A K-M curve, TISIDB and GEPIA website were utilized for survival analysis. Functional annotation was determined using Enrichr and Reactome. Protein-to-protein network analysis was implemented using SRTNG and Cytoscape. Hub gene expression was validated by quantitative polymerase chain reaction, Oncomine and the Hunan Protein Atlas database. Immune infiltration was analyzed by TIMMER, and Drugbank was exploited to identify bioactive compounds. Results The predicted model that was established revealed significant efficacy with 3- and 5-years of the area under ROC at 0.804 and 0.744, respectively. Eleven DEmiRNAs were screened out by a K-M survival analysis. Then, we constructed a ceRNA network, including 56 DElncRNAs, 6 DEmiRNAs, and 28 DEmRNAs. The 28 DEmRNAs were enriched in cancer-related pathways, for example, the TNF signaling pathway. Moreover, six hub genes, CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1, were all overexpressed in HCC tissues and independently correlated with survival rate. Furthermore, expression of hub genes was related to immune cell infiltration in HCC, including B cells, CD8(+) T cells, CD4(+) T cells, monocytes, macrophages, neutrophils, and dendritic cells. Conclusion The findings from this study demonstrate that CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1 are closely associated with prognosis and immune infiltration, representing potential therapeutic targets or prognostic biomarkers in HCC.
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页数:16
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