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基于生物信息学分析鉴定与皮肤烧伤相关的关键基因。

Identification of Key Genes Related to Skin Burns Based on Bioinformatics Analysis.

机构信息

Department of Burns, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.

出版信息

J Burn Care Res. 2024 Sep 6;45(5):1183-1191. doi: 10.1093/jbcr/irac132.

Abstract

To further understand the regulatory network and molecular mechanisms of gene expression after skin burns, we performed bioinformatics analysis of gene expression profiles of skin burn samples and identified key genes associated with skin burns. The GSE8056 and GSE139028 datasets were downloaded from the Gene Expression Omnibus database for analysis and validation. The limma package was used to screen for differentially expressed genes (DEGs). Gene ontology and pathway enrichment analyses (KEGG) were then performed. Subsequently, LASSO regression analysis was performed on DEGs and a regulatory network map of skin burn-related genes was constructed. Finally, the infiltration of immune cells was calculated and coexpression network maps of immune-related key genes and skin regeneration genes were constructed. Analysis of the GSE8056 dataset showed that 432 genes were upregulated and 351 genes were downregulated. The DEGs were mainly focused on immune response and skin regeneration. Meanwhile, these two groups of pivotal genes were significantly associated with abnormal infiltration of nine immune cells. GSE139028 validation revealed that three hub genes associated with skin burn immunity were differentially expressed, except for S100A8, while only the DPT gene was differentially expressed among the seven hub genes associated with skin regeneration. In short, the effect of skin burn on patients is to regulate the expression of immune-related genes UPP1, MMP1, MMP3, and skin regeneration-related gene DPT, which may be the key target for the treatment of skin burn.

摘要

为了进一步了解皮肤烧伤后基因表达的调控网络和分子机制,我们对皮肤烧伤样本的基因表达谱进行了生物信息学分析,鉴定出与皮肤烧伤相关的关键基因。从基因表达综合数据库中下载 GSE8056 和 GSE139028 数据集进行分析和验证。使用 limma 包筛选差异表达基因(DEGs)。然后进行基因本体论和通路富集分析(KEGG)。接着对 DEGs 进行 LASSO 回归分析,并构建皮肤烧伤相关基因的调控网络图谱。最后,计算免疫细胞的浸润度,并构建免疫相关关键基因和皮肤再生基因的共表达网络图谱。对 GSE8056 数据集的分析表明,有 432 个基因上调,351 个基因下调。DEGs 主要集中在免疫反应和皮肤再生。同时,这两组关键基因与 9 种免疫细胞异常浸润显著相关。GSE139028 的验证结果显示,除 S100A8 外,与皮肤烧伤免疫相关的 3 个枢纽基因的表达存在差异,而与皮肤再生相关的 7 个枢纽基因中只有 DPT 基因的表达存在差异。总之,皮肤烧伤对患者的影响是调节免疫相关基因 UPP1、MMP1、MMP3 和皮肤再生相关基因 DPT 的表达,这可能是皮肤烧伤治疗的关键靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19c1/11379151/a0467dbb597d/irac132_fig1.jpg

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