Yang Ronghua, Wang Zhengguang, Li Jiehua, Pi Xiaobing, Wang Xiaoxiang, Xu Yang, Shi Yan, Zhou Sitong
Department of Burn Surgery and Skin Regeneration, The First People's Hospital of Foshan, Foshan, China.
Department of Orthopedics, The First Affiliated Hospital of China Medical University, Shenyang, China.
Front Genet. 2022 Jan 3;12:781589. doi: 10.3389/fgene.2021.781589. eCollection 2021.
Burn injury is a life-threatening disease that does not have ideal biomarkers. Therefore, this study first applied weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) screening methods to identify pivotal genes and diagnostic biomarkers associated with the skin burn process. After obtaining transcriptomic datasets of burn patient skin and normal skin from Gene Expression Omnibus (GEO) and performing differential analysis and functional enrichment, WGCNA was used to identify hub gene modules associated with burn skin processes in the burn patient peripheral blood sample dataset and determine the correlation between modules and clinical features. Enrichment analysis was performed to identify the functions and pathways of key module genes. Differential analysis, WGCNA, protein-protein interaction analysis, and enrichment analysis were utilized to screen for hub genes. Hub genes were validated in two other GEO datasets, tested by immunohistochemistry for hub gene expression in burn patients, and receiver operating characteristic curve analysis was performed. Finally, we constructed the specific drug activity, transcription factors, and microRNA regulatory network of the five hub genes. A total of 1,373 DEGs in GSE8056 were obtained, and the top 5 upregulated genes were , , , , and , whereas the top 5 downregulated genes were , , , , and . DEGs were significantly enriched in the immunity, epidermal development, and skin development processes. In WGCNA, the yellow module was identified as the most closely associated module with tissue damage during the burn process, and the five hub genes (, , , , and ) were identified as the key genes for burn injury status, which consistently showed high expression in burn patient blood samples in the GSE37069 and GSE13902 datasets. Furthermore, we verified using immunohistochemistry that these five novel hub genes were also significantly elevated in burn patient skin. In addition, MCEMP1, MMP9, and S100A12 showed perfect diagnostic performance in the receiver operating characteristic analysis. In conclusion, we analyzed the changes in genetic processes in the skin during burns and used them to identify five potential novel diagnostic markers in blood samples from burn patients, which are important for burn patient diagnosis. In particular, MCEMP1, MMP9, and S100A12 are three key blood biomarkers that can be used to identify skin damage in burn patients.
烧伤是一种危及生命的疾病，目前尚无理想的生物标志物。因此，本研究首次应用加权基因共表达网络分析（WGCNA）和差异表达基因（DEG）筛选方法，以鉴定与皮肤烧伤过程相关的关键基因和诊断生物标志物。从基因表达综合数据库（GEO）获取烧伤患者皮肤和正常皮肤的转录组数据集，进行差异分析和功能富集后，利用WGCNA在烧伤患者外周血样本数据集中鉴定与烧伤皮肤过程相关的枢纽基因模块，并确定模块与临床特征之间的相关性。进行富集分析以确定关键模块基因的功能和途径。利用差异分析、WGCNA、蛋白质-蛋白质相互作用分析和富集分析来筛选枢纽基因。在另外两个GEO数据集中对枢纽基因进行验证，通过免疫组织化学检测烧伤患者枢纽基因的表达，并进行受试者工作特征曲线分析。最后，我们构建了五个枢纽基因的特定药物活性、转录因子和微小RNA调控网络。在GSE8056中总共获得了1373个差异表达基因，上调排名前5的基因是 、 、 、 和 ，而下调排名前5的基因是 、 、 、 和 。差异表达基因在免疫、表皮发育和皮肤发育过程中显著富集。在WGCNA中，黄色模块被确定为与烧伤过程中组织损伤最密切相关的模块，五个枢纽基因（ 、 、 、 和 ）被确定为烧伤损伤状态的关键基因，在GSE37069和GSE13902数据集中的烧伤患者血液样本中持续显示高表达。此外，我们通过免疫组织化学验证，这五个新的枢纽基因在烧伤患者皮肤中也显著升高。此外，在受试者工作特征分析中，MCEMP1、MMP9和S100A12表现出完美的诊断性能。总之，我们分析了烧伤期间皮肤遗传过程的变化，并利用这些变化在烧伤患者的血液样本中鉴定出五个潜在的新型诊断标志物，这对烧伤患者的诊断具有重要意义。特别是，MCEMP1、MMP9和S100A12是三个关键的血液生物标志物，可用于识别烧伤患者的皮肤损伤。
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