| 摘要: |
| 目的 通过生物信息学分析探索基底细胞癌中差异表达的铁死亡相关基因,为未来疾病的诊断与治疗提供新思路。材料和方法 在GEO数据库中筛选目标基因芯片GSE7553,并从FerrDb数据库下载铁死亡相关基因(FRGs)数据集。利用GEO2R分析识别GSE7553数据集中的差异表达基因(DEGs)。通过Venn图分析得出差异表达的铁死亡相关基因(DE-FRGs)。对DE-FRGs进行GO和KEGG富集分析,并利用STRING分析基因的蛋白交互作用。使用Cytoscape软件构建蛋白互作网络(PPI),最后利用CytoHubba插件筛选核心基因。结果 共筛选出51个参与基底细胞癌发生与进展的铁死亡相关基因。这些基因在细胞对化学应激、氧化应激和金属离子反应中显著富集。KEGG分析显示DE-FRGs主要涉及癌症中的MicroRNAs和转录失调、铁死亡等方面。通过CytoHubba插件最终确定四个核心基因：CD44、AR、ZEB1和SLC11A2。结论 本研究通过生物信息学分析初步鉴定出四个DE-FRGs,它们可能作为基底细胞癌的诊断标志物和治疗靶点,为未来进一步研究基底细胞癌的诊断与治疗提供新的方向。 |
| 关键词: 基底细胞癌 铁死亡 铁死亡相关基因 生物信息学分析；差异表达基因 |
| DOI： |
| 分类号: |
| 基金项目:茂名市科技计划立项项目(240525234551147) |
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| Exploration of ferroptosis-related genes in basal cell carcinoma via bioinformatics analysis |
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HUANG Fangchang1, ZHU Xin2, YAN Jun3, LIANG Xinglong3
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1.Department of Dermatology,Maoming People’s Hospital,Guangdong Medicine University,Guangdong,China;2.Graduate School of Guangdong Medical University;3.Maoming Clinical Medical College of Guangdong Medical University
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| Abstract: |
| Objective This study aims to explore differentially expressed ferroptosis- related genes(DE-FRGs)in basal cell carcinoma(BCC)through bioinformatics analysis, providing novel insights for the diagnosis and treatment of future diseases. Materials and Methods The target gene chip GSE7553 was selected from the GEO database, and the ferroptosis-related genes (FRGs) was downloaded from the FerrDb database. Differential expression genes (DEGs) in the GSE7553 dataset were identified using GEO2R. DE-FRGs were determined through Venn diagram analysis. GO and KEGG enrichment analyses of DE-FRGs were conducted, and the protein interactions of the genes were analyzed using STRING. Protein-protein interaction network was constructed by Cytoscape software, followed by identification of core genes using the CytoHubba plugin. Results A total of 51 FRGs involved in the occurrence and progression of BCC were identified. These genes were significantly enriched in cellular responses to chemical stress, oxidative stress, and metal ion responses. KEGG analysis indicated that DE-FRGs are mainly associated with MicroRNAs, transcriptional dysregulation in cancer, and ferroptosis. Using the CytoHubba plugin, four core genes were ultimately identified: CD44, AR, ZEB1, and SLC11A2. Conclusion This study preliminarily identified four DE-FRGs through bioinformatics analysis, suggesting their potential as diagnostic biomarkers and therapeutic targets for BCC, thereby paving the way for future research directions in its diagnosis and treatment. |
| Key words: Basal cell carcinoma Ferroptosis Ferroptosis-related genes Bioinformatics analysis Differentially expressed genes |