Zhang Weiqiang, Wang Fujun, Zhang Yixun, Xu Lusheng, Mao Lujia, Wang Xiaoxiang, Yang Ronghua
The First Clinical School of Medicine, Guangdong Medical University, Zhanjiang, Guangdong, China.
School of Basic Medicine, Qiqihar Medical University, Qiqihar, Heilongjiang, China.
Front Cell Dev Biol. 2025 Nov 19;13:1718189. doi: 10.3389/fcell.2025.1718189. eCollection 2025.
Keloid formation is a prevalent dermatological condition characterized by abnormal dermal connective tissue proliferation. Despite ongoing research, the underlying mechanisms of keloid formation remain insufficiently understood. The aim of this research is to identify and verify molecular biomarkers associated with keloid and to explore potential therapeutic targets.
Transcriptomic data from keloid tissue specimens and normal skin controls were retrieved from the Gene Expression Omnibus (GEO) database. We performed differential expression and functional enrichment analyses after batch effect correction. We performed differential gene analysis, weighted Gene Co-expression Network Analysis (WGCNA), and protein-protein interaction (PPI) analyses to verify hub genes, explore their functions, and evaluate their connection to keloid formation, therapeutic potential, and immune-related characteristics. Key genes were validated through experimental assays.
679 differentially expressed genes (DEGs) were identified. Through WGCNA and Venn diagram analysis, 41 DEGs most closely associated with keloid were identified. These 41 overlapping DEGs were confirmed to be markedly involved in metabolic pathways, nucleotide excision repair, and amino acid biosynthesis by functional enrichment analysis. PPI analysis identified CDK7 and DDB2 as hub genes, each demonstrating strong diagnostic performance in ROC curve analysis (AUC = 0.80), with comparable results in validation datasets (AUC = 0.86). Basic experiments confirmed higher expression of CDK7 and DDB2 in keloid tissue compared to normal skin.
Our findings demonstrate that CDK7 and DDB2 are promising biomarkers for diagnostic and potential therapeutic targets in keloid, providing novel insights into its pathogenesis and offering promising druggable targets.
瘢痕疙瘩形成是一种常见的皮肤病学病症,其特征为真皮结缔组织异常增殖。尽管研究不断,但瘢痕疙瘩形成的潜在机制仍未得到充分理解。本研究的目的是识别和验证与瘢痕疙瘩相关的分子生物标志物,并探索潜在的治疗靶点。
从基因表达综合数据库(GEO)中检索瘢痕疙瘩组织标本和正常皮肤对照的转录组数据。我们在批次效应校正后进行差异表达和功能富集分析。我们进行差异基因分析、加权基因共表达网络分析(WGCNA)和蛋白质-蛋白质相互作用(PPI)分析,以验证核心基因、探索其功能,并评估它们与瘢痕疙瘩形成、治疗潜力和免疫相关特征的联系。关键基因通过实验分析进行验证。
共鉴定出679个差异表达基因(DEG)。通过WGCNA和维恩图分析,确定了41个与瘢痕疙瘩最密切相关的DEG。通过功能富集分析证实,这41个重叠的DEG显著参与代谢途径、核苷酸切除修复和氨基酸生物合成。PPI分析确定CDK7和DDB2为核心基因,二者在ROC曲线分析中均显示出较强的诊断性能(AUC = 0.80),在验证数据集中结果相当(AUC = 0.86)。基础实验证实,与正常皮肤相比,瘢痕疙瘩组织中CDK7和DDB2的表达更高。
我们的研究结果表明,CDK7和DDB2是瘢痕疙瘩诊断和潜在治疗靶点的有前景的生物标志物,为其发病机制提供了新见解,并提供了有前景的可成药靶点。