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<p>Liver hepatocellular carcinoma (LIHC) is a leading cause of cancer-related mortality worldwide, with limited therapeutic options and poor prognosis, particularly at advanced stages. Identifying key molecular drivers involved in LIHC progression is critical for improving diagnosis and treatment strategies. In this study, we performed an integrated bioinformatics analysis using four independent GEO datasets (GSE19665, GSE54236, GSE55092, and GSE84598) to identify differentially expressed genes (DEGs) associated with LIHC. A total of 147 common DEGs were identified, and protein–protein interaction network analysis revealed CCNA2, MAD2L1, AURKA, and PTTG1 as central hub genes. Functional enrichment analyses indicated that these genes are primarily involved in cell cycle regulation, mitosis, and chromosomal stability. Expression analyses using TCGA-based databases demonstrated significant upregulation of these hub genes at both mRNA and protein levels in LIHC tissues compared with normal liver tissues. Elevated expression was associated with advanced tumor stage, poor overall survival, immune cell infiltration, and altered drug sensitivity, highlighting their clinical relevance. Promoter methylation analysis suggested that epigenetic regulation may contribute to gene dysregulation, while genetic alterations were infrequent. Experimental validation using RT-qPCR confirmed overexpression of hub genes in LIHC cell lines. Furthermore, siRNA-mediated knockdown of these genes significantly suppressed proliferation, colony formation, and migration in HepG2 and Huh7 cells. Collectively, these findings identify CCNA2, MAD2L1, AURKA, and PTTG1 as key oncogenic drivers and potential biomarkers and therapeutic targets in LIHC.</p>

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CCNA2, MAD2L1, AURKA, and PTTG1 promote proliferation and migration in hepatocellular carcinoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月28日

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  • Wang Jinli,
  • Hu Shiping

摘要

Liver hepatocellular carcinoma (LIHC) is a leading cause of cancer-related mortality worldwide, with limited therapeutic options and poor prognosis, particularly at advanced stages. Identifying key molecular drivers involved in LIHC progression is critical for improving diagnosis and treatment strategies. In this study, we performed an integrated bioinformatics analysis using four independent GEO datasets (GSE19665, GSE54236, GSE55092, and GSE84598) to identify differentially expressed genes (DEGs) associated with LIHC. A total of 147 common DEGs were identified, and protein–protein interaction network analysis revealed CCNA2, MAD2L1, AURKA, and PTTG1 as central hub genes. Functional enrichment analyses indicated that these genes are primarily involved in cell cycle regulation, mitosis, and chromosomal stability. Expression analyses using TCGA-based databases demonstrated significant upregulation of these hub genes at both mRNA and protein levels in LIHC tissues compared with normal liver tissues. Elevated expression was associated with advanced tumor stage, poor overall survival, immune cell infiltration, and altered drug sensitivity, highlighting their clinical relevance. Promoter methylation analysis suggested that epigenetic regulation may contribute to gene dysregulation, while genetic alterations were infrequent. Experimental validation using RT-qPCR confirmed overexpression of hub genes in LIHC cell lines. Furthermore, siRNA-mediated knockdown of these genes significantly suppressed proliferation, colony formation, and migration in HepG2 and Huh7 cells. Collectively, these findings identify CCNA2, MAD2L1, AURKA, and PTTG1 as key oncogenic drivers and potential biomarkers and therapeutic targets in LIHC.