Exploring potential key genes and pathways associatedwith hepatocellular carcinoma prognosis through bioinformatics analysis, followed by experimental validation.

IF 1.7 4区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
American journal of translational research Pub Date : 2024-12-15 eCollection Date: 2024-01-01 DOI:10.62347/WIER4743
Xi Chen, Jianhua Zhao, Jiaming Shu, Xueming Ying, Salman Khan, Sara Sarfaraz, Reza Mirzaeiebrahimabadi, Majid Alhomrani, Abdulhakeem S Alamri, Naif ALSuhaymi
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Abstract

Background: Liver 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.

Method: We 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.

Results: Analysis 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.

Conclusion: AURKA, 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.

通过生物信息学分析,探索与肝癌预后相关的潜在关键基因和通路,并进行实验验证。
背景:肝细胞癌(LIHC)是一种普遍的侵袭性肝癌,治疗方案有限。确定参与LIHC的关键基因可以增强我们对其分子机制的理解,并有助于开发靶向治疗。本研究旨在利用生物信息学方法和实验验证方法鉴定LIHC中差异表达基因(DEGs)和关键枢纽基因。方法:分析基因表达综合数据库(Gene Expression Omnibus, GEO)中两个与lihc相关的数据集GSE84598和GSE19665来鉴定基因。使用R中的limma包进行差异表达分析,以鉴定癌性和非癌性肝组织之间的deg。利用STRING构建蛋白-蛋白相互作用(Protein-Protein Interaction, PPI)网络,确定关键枢纽基因。通过UALCAN、OncoDB和Human Protein Atlas (HPA)数据库进一步验证这些中心基因的mRNA和蛋白表达水平。使用cbiopportal进行启动子甲基化和突变分析。Kaplan-Meier生存分析评估hub基因表达对患者生存的影响。利用GSCA探讨免疫细胞丰度和药物敏感性的相关性。最后,在HepG2细胞中敲除AURKA,进行细胞增殖、集落形成和伤口愈合实验。结果:分析发现180个deg,其中四个关键枢纽基因,包括AURKA, BUB1B, CCNA2和PTTG1在LIHC组织中显着过表达和低甲基化。AURKA在HepG2细胞中的敲低导致细胞增殖减少,集落形成减少,伤口愈合受损,证实了它在LIHC进展中的作用。这些中心基因也是低甲基化的,它们的高表达与较差的总生存率相关。结论:AURKA、BUB1B、CCNA2和PTTG1在LIHC发病机制中起着至关重要的作用,可能是潜在的生物标志物或治疗靶点。我们的发现为LIHC机制提供了新的见解,并为未来的研究和治疗开发提供了有希望的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
American journal of translational research
American journal of translational research ONCOLOGY-MEDICINE, RESEARCH & EXPERIMENTAL
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552
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