ArticleAmerican journal of translational research2024
Exploring potential key genes and pathways associatedwith hepatocellular carcinoma prognosis through bioinformatics analysis, followed by experimental validation.
Article in American journal of translational research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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10 authors.
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Abstract
backgroundLiver Hepatocellular Carcinoma (LIHC) is a prevalent and aggressive liver cancer with limited therapeutic options. Identifying key genes involved in LIHC can enhance our understanding of its molecular mechanisms and aid in the development of targeted therapies. This study aims to identify differentially expressed genes (DEGs) and key hub genes in LIHC using bioinformatics approaches and experimental validation.
methodWe analyzed two LIHC-related datasets, GSE84598 and GSE19665, from the Gene Expression Omnibus (GEO) database to identify DEGs. Differential expression analysis was performed using the limma package in R to identify DEGs between cancerous and non-cancerous liver tissues. A Protein-Protein Interaction (PPI) network was constructed using STRING to determine key hub genes. Further validation of these hub genes was conducted through UALCAN, OncoDB, and the Human Protein Atlas (HPA) databases for mRNA and protein expression levels. Promoter methylation and mutational analyses were performed using cBioPortal. Kaplan-Meier survival analysis assessed the impact of hub gene expression on patient survival. Correlations with immune cell abundance and drug sensitivity were explored using GSCA. Finally, AURKA was knocked down in HepG2 cells, and cell proliferation, colony formation, and wound healing assays were performed.
resultsAnalysis identified 180 DEGs, with four key hub genes, including AURKA, BUB1B, CCNA2, and PTTG1 showing significant overexpression and hypomethylation in LIHC tissues. AURKA knockdown in HepG2 cells led to decreased cell proliferation, reduced colony formation, and impaired wound healing, confirming its role in LIHC progression. These hub genes were also hypomethylated and their elevated expression correlated with poor overall survival.
conclusionAURKA, BUB1B, CCNA2, and PTTG1 are crucial for LIHC pathogenesis and may serve as potential biomarkers or therapeutic targets. Our findings provide new insights into LIHC mechanisms and suggest promising avenues for future research and therapeutic development.
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