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The Oncogenic Role of CENPA in Hepatocellular Carcinoma Development: Evidence from Bioinformatic Analysis
OBJECTIVE: This study is aimed at investigating the predictive value of CENPA in hepatocellular carcinoma (HCC) development. METHODS: Using integrated bioinformatic analysis, we evaluated the CENPA mRNA expression in tumor and adjacent tissues and correlated it with HCC survival and clinicopathologi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7168693/ https://www.ncbi.nlm.nih.gov/pubmed/32337237 http://dx.doi.org/10.1155/2020/3040839 |
Sumario: | OBJECTIVE: This study is aimed at investigating the predictive value of CENPA in hepatocellular carcinoma (HCC) development. METHODS: Using integrated bioinformatic analysis, we evaluated the CENPA mRNA expression in tumor and adjacent tissues and correlated it with HCC survival and clinicopathological features. A Cox regression hazard model was also performed. RESULTS: CENPA mRNA was significantly upregulated in tumor tissues compared with that in adjacent tissues, which were validated in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) series (all P < 0.01). In the Kaplan-Meier plotter platform, the high level of CENPA mRNA was significantly correlated with overall survival (OS), disease-free survival (DFS), recurrence-free survival (RFS), and progression-free survival (PFS) in HCC patients (all log rank P < 0.01). For validation in GSE14520 and pan-TCGA dataset, HCC patients with CNEPA mRNA overexpression had poor OS compared with those with low CENPA mRNA (log rank P = 0.025 and P < 0.0001, respectively), and those with high CENPA had poor DFS in TCGA (log rank P = 0.0001). Additionally, CENPA mRNA were upregulated in HCC patients with alpha-fetoprotein (AFP) elevation, advanced TNM stage, larger tumor size, advanced AJCC stage, advanced pathology grade, and vascular invasion (all P < 0.05). A Cox regression model including CENPA, OIP5, and AURKB could predict OS in HCC patients effectively (AUC = 0.683). CONCLUSION: Overexpressed in tumors, CENPA might be an oncogenic factor in the development of HCC patients. |
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