Suppr超能文献

通过生物信息学分析鉴定肝细胞癌和2型糖尿病中的关键铁死亡基因。

Identification of key ferroptosis genes in hepatocellular carcinoma and type 2 diabetes mellitus through bioinformatics analysis.

作者信息

Zhou Jinjin, Shi Yage, Jian Yulun, Li Yuhan, Yu Wenya, Mu Wei, Ge Yang

机构信息

School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.

出版信息

Discov Oncol. 2025 May 25;16(1):916. doi: 10.1007/s12672-025-02758-y.

Abstract

Ferroptosis is a programmed cell death mode associated with iron metabolism, with accumulation of intracellular lipid peroxides, which is closely related to the occurrence and development of multiple diseases, including type 2 diabetes mellitus (T2DM) and hepatocellular carcinoma (HCC). T2DM is a chronic metabolic disorder characterized by a combination of impaired insulin sensitivity and insufficient insulin production, frequently accompanied by obesity and fatty liver, which increases the risk of developing HCC. To explore the complex interactions between ferritin deposition, T2DM, and HCC, we performed bioinformatics analysis on publicly available gene expression data and identified 23 differentially expressed genes (DEGs) that are commonly expressed in both T2DM and HCC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that these DEGs are primarily enriched in fatty acid metabolism and ferroptosis pathways. The weighted gene co-expression network analysis (WGCNA) identified 6 key genes associated with the pathogenesis of both diseases. Taking the intersection of DEGs and iron deposition-related genes, we identified ACSL4 as a key ferroptosis gene involved in the co-morbidity of T2DM and HCC. To validate the bioinformatics findings, we assessed the expression of ACSL4 using Receiver operating characteristic (ROC) curve analysis, which revealed an Area Under the Curve (AUC) of 0.886 for HCC and 0.745 for T2DM. Additionally, an insulin resistance model was established in HepG2 cells by treatment with 350 µM palmitic acid (PA), resulting in significant changes in cell morphology. Oil Red O staining showed a marked increase in lipid accumulation. RT-PCR analysis further confirmed the significant alteration in ACSL4 gene expression. In conclusion, this study is the first to integrate bioinformatics tools to investigate the potential mechanistic links between iron metabolism and the comorbidity of T2DM and HCC, uncovering a novel pathogenic pathway. These findings provide new directions for drug development and therapeutic strategies in the future.

摘要

铁死亡是一种与铁代谢相关的程序性细胞死亡模式,伴有细胞内脂质过氧化物的积累,与包括2型糖尿病(T2DM)和肝细胞癌(HCC)在内的多种疾病的发生发展密切相关。T2DM是一种慢性代谢紊乱疾病,其特征为胰岛素敏感性受损和胰岛素分泌不足,常伴有肥胖和脂肪肝,这增加了患HCC的风险。为了探究铁蛋白沉积、T2DM和HCC之间的复杂相互作用,我们对公开可用的基因表达数据进行了生物信息学分析,并鉴定出23个在T2DM和HCC中均共同表达的差异表达基因(DEG)。基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集分析表明,这些DEG主要富集于脂肪酸代谢和铁死亡途径。加权基因共表达网络分析(WGCNA)确定了6个与这两种疾病发病机制相关的关键基因。通过取DEG与铁沉积相关基因的交集,我们确定ACSL4是参与T2DM和HCC共病的关键铁死亡基因。为了验证生物信息学研究结果,我们使用受试者工作特征(ROC)曲线分析评估了ACSL4的表达,结果显示HCC的曲线下面积(AUC)为0.886,T2DM为0.745。此外,通过用350µM棕榈酸(PA)处理在HepG2细胞中建立了胰岛素抵抗模型,导致细胞形态发生显著变化。油红O染色显示脂质积累显著增加。RT-PCR分析进一步证实了ACSL4基因表达的显著改变。总之,本研究首次整合生物信息学工具来探究铁代谢与T2DM和HCC共病之间的潜在机制联系,揭示了一条新的致病途径。这些发现为未来的药物开发和治疗策略提供了新方向。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验