Peng Shixiong, Chen Mengjiao, Yin Ming, Feng Hao
Department of Dermatology, The First Affiliated Hospital of Hunan Normal University/Hunan Provincial People's Hospital, Changsha, People's Republic of China.
Clin Cosmet Investig Dermatol. 2021 May 7;14:437-453. doi: 10.2147/CCID.S310426. eCollection 2021.
This study was meant to analyze immune infiltration and construct a ceRNA network to explore the new therapeutic targets for atopic dermatitis (AD) through bioinformatics way.
We downloaded the AD patients' RNA expression profile datasets (GSE63741, GSE124700) from the Gene Expression Omnibus (GEO) database, which were analyzed through the GEO2R. We explored the hub genes by the enrichment analysis and the protein-protein interaction (PPI) analysis. Moreover, we estimated immune cell types and their proportions by ImmucellAI. GSE121212 dataset validation was performed to verify the robustness of the hub genes. Then, a ceRNA network was constructed by the miRWalk, miRNet, miRDB, DIANA, TargetScan, and starbase database. Finally, gene expression analysis was performed by using RT-qPCR.
In total, we detected 22 differentially expressed genes (DEGs), which contained 8 downregulated genes and 14 upregulated genes. There were 5 hub genes confirmed as key genes through PPI network analysis and the ROC curves. KEGG pathway analysis revealed that they were significantly enriched in the IL-17 signaling pathway and GO analysis showed mainly in the immune cell chemotaxis. The immune infiltration profiles were different between normal controls and AD, and each of the key genes (S100A7, S100A8, S100A9, and LCE3D) was significantly correlated with the main infiltration cell of AD. A lncRNA-miRNA-mRNA ceRNA network containing the key genes was constructed, and NEAT1 and XIST, the core of ceRNA network, were significantly overexpressing verified by RT-qPCR in AD patients.
Altogether, the key genes and their ceRNA network provided a novel perspective to the immunomodulation of AD, which may be potential and new therapeutic targets for AD.
本研究旨在通过生物信息学方法分析免疫浸润并构建ceRNA网络，以探索特应性皮炎（AD）的新治疗靶点。
我们从基因表达综合数据库（GEO）下载了AD患者的RNA表达谱数据集（GSE63741、GSE124700），并通过GEO2R进行分析。我们通过富集分析和蛋白质-蛋白质相互作用（PPI）分析探索枢纽基因。此外，我们使用ImmucellAI估计免疫细胞类型及其比例。对GSE121212数据集进行验证以检验枢纽基因的稳健性。然后，通过miRWalk、miRNet、miRDB、DIANA、TargetScan和starbase数据库构建ceRNA网络。最后，使用RT-qPCR进行基因表达分析。
我们总共检测到22个差异表达基因（DEG），其中包括8个下调基因和14个上调基因。通过PPI网络分析和ROC曲线确定了5个枢纽基因作为关键基因。KEGG通路分析显示它们在IL-17信号通路中显著富集，GO分析表明主要集中在免疫细胞趋化性方面。正常对照和AD之间的免疫浸润谱不同，每个关键基因（S100A7、S100A8、S100A9和LCE3D）都与AD的主要浸润细胞显著相关。构建了一个包含关键基因的lncRNA-miRNA-mRNA ceRNA网络，通过RT-qPCR验证，ceRNA网络的核心NEAT1和XIST在AD患者中显著过表达。
总之，关键基因及其ceRNA网络为AD的免疫调节提供了新的视角，可能是AD潜在的新治疗靶点。
