Sun Yuexin, Yu Haoyue, Zhou Ying, Bao Jun, Qian Xiaoping
Department of Dermotology, Nanjing Drum Tower Hospital, Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210000, China.
Department of Oncology, Nanjing Drum Tower Hospital, Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.
Arch Dermatol Res. 2025 Mar 1;317(1):514. doi: 10.1007/s00403-025-03895-8.
To identify genes differentially expressed between resistant and sensitive BRAF V600E melanoma cell lines using bioinformatics tools applied to GEO data. We retrieved and downloaded the target gene set (GSE45558) from the GEO database and used R software to filter differentially expressed genes (DEGs) between BRAF V600E melanoma cell lines resistant. The identified DEGs were subjected to GO functional enrichment analysis (including biological processes, molecular functions, and cellular components) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, utilizing R software. Protein-protein interaction networks for the DEGs were generated using the STRING online database. Top hub genes were cross-referenced with genes related to ferroptosis from the FerrDb database to identify DEGs linked to ferroptosis in resistant melanoma cells. From the GEO database analysis, we identified the top 100 DEGs between BRAF V600E melanoma cell lines, including 50 downregulated and 50 upregulated DEGs. Using STRING and Cytoscape, we identified the top 10 hub genes: IL6, IL1B, CCL2, MMP2, TGFB2, EGFR, POSTN, SERPINE1, COL1A2, and MITF. Cross-referencing with the FerrDb database, we found that IL6 and EGFR are differentially expressed genes related to ferroptosis in resistant melanoma cells. Validation through clinical samples and in vitro experiments confirmed the high expression of the ferroptosis-related gene EGFR as a potential biomarker for resistance to targeted therapy in BRAF melanoma. Bioinformatics analysis identified key resistance genes in BRAF melanoma targeted therapy, demonstrating the impact of ferroptosis-related gene EGFR on the resistance of BRAF melanoma.
使用应用于GEO数据的生物信息学工具,鉴定耐药和敏感的BRAF V600E黑色素瘤细胞系之间差异表达的基因。我们从GEO数据库中检索并下载了目标基因集(GSE45558),并使用R软件筛选BRAF V600E黑色素瘤耐药细胞系之间的差异表达基因(DEGs)。利用R软件,对鉴定出的DEGs进行基因本体(GO)功能富集分析(包括生物学过程、分子功能和细胞成分)和京都基因与基因组百科全书(KEGG)通路分析。使用STRING在线数据库生成DEGs的蛋白质-蛋白质相互作用网络。将顶级枢纽基因与来自FerrDb数据库的铁死亡相关基因进行交叉引用,以鉴定耐药黑色素瘤细胞中与铁死亡相关的DEGs。通过GEO数据库分析,我们鉴定出BRAF V600E黑色素瘤细胞系之间的前100个DEGs,包括50个下调的和50个上调的DEGs。使用STRING和Cytoscape,我们鉴定出前10个枢纽基因:IL6、IL1B、CCL2、MMP2、TGFB2、EGFR、POSTN、SERPINE1、COL1A2和MITF。与FerrDb数据库交叉引用后,我们发现IL6和EGFR是耐药黑色素瘤细胞中与铁死亡相关的差异表达基因。通过临床样本和体外实验验证,证实铁死亡相关基因EGFR的高表达是BRAF黑色素瘤靶向治疗耐药的潜在生物标志物。生物信息学分析鉴定出BRAF黑色素瘤靶向治疗中的关键耐药基因,证明了铁死亡相关基因EGFR对BRAF黑色素瘤耐药性的影响。