Screening and function analysis of hub genes and pathways in hepatocellular carcinoma via bioinformatics approaches

Zhang, Liang; Huang, Yi; Ling, Junjun; Wu, Zhuo; Zhen, Yu; Shao, Mengmeng; Luo, Yunbo; Zhu, Yi

doi:10.3233/cbm-171160

Cited by 29 publications

(23 citation statements)

References 44 publications

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“… 51 High expression of CCNA2 is associated with reduced survival in patients with breast cancer and HCC. 52 , 53 CCNB1 and CCNB2 are the principal activators of CDK1 and, together with CDK1, they promote the G 2 /M transition. 54 , 55 Expression of CCNB1 changes periodically throughout the cell cycle, and is a crucial initiator of mitosis.…”

Section: Discussionmentioning

confidence: 99%

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Meng

Liu

et al. 2020

J Int Med Res

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Objective The objective was to identify potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma (HCC). Methods Gene expression profile datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HCC and normal samples were identified via an integrated analysis. A protein–protein interaction network was constructed and analyzed using the STRING database and Cytoscape software, and enrichment analyses were carried out through DAVID. Gene Expression Profiling Interactive Analysis and Kaplan–Meier plotter were used to determine expression and prognostic values of hub genes. Results We identified 11 hub genes ( CDK1, CCNB2, CDC20, CCNB1, TOP2A, CCNA2, MELK, PBK, TPX2, KIF20A, and AURKA) that might be closely related to the pathogenesis and prognosis of HCC. Enrichment analyses indicated that the DEGs were significantly enriched in metabolism-associated pathways, and hub genes and module 1 were highly associated with cell cycle pathway. Conclusions In this study, we identified key genes of HCC, which indicated directions for further research into diagnostic and prognostic biomarkers that could facilitate targeted molecular therapy for HCC.

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Section: Discussionmentioning

confidence: 99%

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Meng

Liu

et al. 2020

J Int Med Res

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“…The function of BUB1 as oncogene or tumor suppressor gene has been observed in various types of cancer, including breast cancer, pancreatic ductal adenocarcinoma, prostate and gastric cancer (12)(13)(14)(15). Several studies have demonstrated the unfavorable prognostic role of BUB1 in liver cancer based on bioinformatics analysis (16)(17)(18). However, the molecular biological function of BUB1 in liver cancer still remains unclear.…”

Section: Introductionmentioning

confidence: 99%

BUB1 promotes proliferation of liver cancer cells by activating SMAD2 phosphorylation

Zhu¹,

Pan²,

Chen

et al. 2020

Oncol Lett

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Budding uninhibited by benzimidazoles 1 (BUB1) is a mitotic checkpoint serine/threonine kinase that has been reported as an oncogene or tumor suppressor gene in various types of cancer, including breast cancer, pancreatic ductal adenocarcinoma, prostate and gastric cancers. However, its role in liver cancer remains unclear. The present study aimed to explore the biological function of BUB1 in liver cancer. The present study demonstrated that BUB1 mRNA expression levels and the intensity of immunohistochemical staining were significantly increased in liver cancer tissues compared with normal tissues. The role of BUB1 in cell proliferation was also determined. Overexpression of BUB1 significantly promoted cell proliferation, whereas knockdown of BUB1 expression inhibited the proliferation of liver cancer cell lines. In experiments investigating the underlying mechanism, overexpression of BUB1 increased the levels of SMAD2 phosphorylation, whereas knockdown of BUB1 reduced the levels of SMAD2 phosphorylation. Therefore, BUB1 may promote proliferation of liver cancer cells by activating phosphorylation of SMAD2, and BUB1 may serve as a potential target in the diagnosis and/or treatment of liver cancer.

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“…Of note, downregulation of NDC80 was able to suppress the replication of HBV-associated HCC cells (42). Bound to MYC, AURKA, which has two functional non-synonymous polymorphisms (lle31Phe and Val57lle), was able to regulate tumor cell growth at the genetic level (43). It has been reported that AURKA lle31Phe enhances the proneness of HBV-infected individuals to develop liver cancer (44).…”

Section: Discussionmentioning

confidence: 98%

Bioinformatics analysis reveals meaningful markers and outcome predictors in HBV‑associated hepatocellular carcinoma

et al. 2020

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Hepatocellular carcinoma (HCC) is the most common type of malignant neoplasm of the liver with high morbidity and mortality. Extensive research into the pathology of HCC has been performed; however, the molecular mechanisms underlying the development of hepatitis B virus-associated HCC have remained elusive. Thus, the present study aimed to identify critical genes and pathways associated with the development and progression of HCC. The expression profiles of the GSE121248 dataset were downloaded from the Gene Expression Omnibus database and the differentially expressed genes (DEGs) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) analyses were performed by using the Database for Annotation, Visualization and Integrated Discovery. Subsequently, protein-protein interaction (PPI) networks were constructed for detecting hub genes. In the present study, 1,153 DEGs (777 upregulated and 376 downregulated genes) were identified and the PPI network yielded 15 hub genes. GO analysis revealed that the DEGs were primarily enriched in 'protein binding', 'cytoplasm' and 'extracellular exosome'. KEGG analysis indicated that DEGs were accumulated in 'metabolic pathways', 'chemical carcinogenesis' and 'fatty acid degradation'. After constructing the PPI network, cyclin-dependent kinase 1, cyclin B1, cyclin A2, mitotic arrest deficient 2 like 1, cyclin B2, DNA topoisomerase IIα, budding uninhibited by benzimidazoles (BUB)1, TTK protein kinase, non-SMC condensin I complex subunit G, NDC80 kinetochore complex component, aurora kinase A, kinesin family member 11, cell division cycle 20, BUB1B and abnormal spindle microtubule assembly were identified as hub genes based on the high degree of connectivity by using Cytoscape software. In addition, overall survival (OS) and disease-free survival (DFS) analyses were performed using the Gene Expression Profiling Interactive Analysis online database, which revealed that the increased expression of all hub genes were associated with poorer OS and DFS outcomes. Receiver operating characteristic curves were constructed using GraphPad prism 7.0 software. The results confirmed that 15 hub genes were able to distinguish HCC form normal tissues. Furthermore, the expression levels of three key genes were analyzed in tumor and normal samples of the Human Protein Atlas database. The present results may provide further insight into the underlying mechanisms of HCC and potential therapeutic targets for the treatment of this disease.

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Screening and function analysis of hub genes and pathways in hepatocellular carcinoma via bioinformatics approaches

Abstract: In conclusion, the present study identified several hub genes, and cell cycle and metabolism-related pathways that may play critical roles in the tumorigenesis of liver cancer. Future validation laboratory experiments are required to confirm the results.

Cited by 29 publications

References 44 publications

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

BUB1 promotes proliferation of liver cancer cells by activating SMAD2 phosphorylation

Bioinformatics analysis reveals meaningful markers and outcome predictors in HBV‑associated hepatocellular carcinoma

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