Kong Jiao, Zhou Changcai, Qin Haiyan, Li Caihong, Wu Zhuoxia, Zhang Lianbo
China-Japan Union Hospital of Jilin University, No. 126 of Xiantai Street, Changchun 130033, China.
China-Japan Union Hospital of Jilin University, No. 126 of Xiantai Street, Changchun 130033, China; Beijing Badachu Aesthetic Hospital, No. 54 of Anli Road, Beijing 100020, China.
J Plast Reconstr Aesthet Surg. 2025 Mar;102:313-322. doi: 10.1016/j.bjps.2025.01.070. Epub 2025 Jan 31.
Keloids represent a challenging clinical problem because of their unpredictable and often refractory nature to treatment. This study aimed to identify the key changes in gene expression in the formation of keloid and provide potential biomarker candidates for clinical treatment and drug target discovery. Keloids and normal skin samples were analyzed for gene expression, and datasets from the Gene Expression Omnibus database were also analyzed. Differentially expressed genes (DEGs) were identified and analyzed using bioinformatics techniques, including gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. A protein-protein interaction network of the DEGs was created using the Search Tool for the Retrieval of Interacting Genes database. The gene set enrichment analysis was performed on keloid and normal skin tissue from clinical samples. The enriched functions and pathways identified included collagen-containing extracellular matrix (ECM), ECM, and external encapsulating structure. Ten hub genes were identified, along with one differentially expressed microRNA, miR-22-5p. miRNA target gene prediction was performed using miRPathDB 2.0 and Targetscan database. Among the hub genes, RUNX2, IGF1, EGF, and PPARGC1A were predicted targets of miR-22-5p. Validation at the tissue level highlighted RUNX2 as a crucial DEG in keloid tissue. These findings shed light on the molecular mechanisms of keloid formation and offer candidate therapeutic targets, suggesting that modulation of the miR-22-5p/RUNX2 axis may be a promising avenue for keloid diagnosis and treatment, thus laying a foundation for improved clinical management of keloid disorders.
瘢痕疙瘩是一个具有挑战性的临床问题，因为其性质不可预测且通常对治疗难治。本研究旨在确定瘢痕疙瘩形成过程中基因表达的关键变化，并为临床治疗和药物靶点发现提供潜在的生物标志物候选物。对瘢痕疙瘩和正常皮肤样本进行基因表达分析，并分析来自基因表达综合数据库的数据集。使用生物信息学技术，包括基因本体论和京都基因与基因组百科全书通路富集分析，来鉴定和分析差异表达基因（DEG）。使用检索相互作用基因的搜索工具数据库创建DEG的蛋白质-蛋白质相互作用网络。对临床样本中的瘢痕疙瘩和正常皮肤组织进行基因集富集分析。确定的富集功能和通路包括含胶原蛋白的细胞外基质（ECM）、ECM和外部包裹结构。鉴定出10个枢纽基因，以及1个差异表达的 microRNA，即miR-22-5p。使用miRPathDB 2.0和Targetscan数据库进行miRNA靶基因预测。在枢纽基因中，RUNX2、IGF1、EGF和PPARGC1A被预测为miR-22-5p的靶标。组织水平的验证突出了RUNX2是瘢痕疙瘩组织中的关键DEG。这些发现揭示了瘢痕疙瘩形成的分子机制，并提供了候选治疗靶点，表明调节miR-22-5p/RUNX2轴可能是瘢痕疙瘩诊断和治疗的一个有前景的途径，从而为改善瘢痕疙瘩疾病的临床管理奠定基础。
