Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
Front Immunol. 2023 Jun 20;14:1207522. doi: 10.3389/fimmu.2023.1207522. eCollection 2023.
Hypertrophic scar (HS) is a chronic inflammatory skin disease characterized by excessive deposition of extracellular matrix, but the exact mechanisms related to its formation remain unclear, making it difficult to treat. This study aimed to investigate the potential role of cuproptosis in the information of HS. To this end, we used single-cell sequencing and bulk transcriptome data, and screened for cuproptosis-related genes (CRGs) using differential gene analysis and machine learning algorithms (random forest and support vector machine). Through this process, we identified a group of genes, including ATP7A, ULK1, and MTF1, as novel therapeutic targets for HS. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to confirm the mRNA expression of ATP7A, ULK1, and MTF1 in both HS and normal skin (NS) tissues. We also constructed a diagnostic model for HS and analyzed the immune infiltration characteristics. Additionally, we used the expression profiles of CRGs to perform subgroup analysis of HS. We focused mainly on fibroblasts in the transcriptional profile at single-cell resolution. By calculating the cuproptosis activity of each fibroblast, we found that cuproptosis activity of normal skin fibroblasts increased, providing further insights into the pathogenesis of HS. We also analyzed the cell communication network and transcription factor regulatory network activity, and found the existence of a fibroblast-centered communication regulation network in HS, where cuproptosis activity in fibroblasts affects intercellular communication. Using transcription factor regulatory activity network analysis, we obtained highly active transcription factors, and correlation analysis with CRGs suggested that CRGs may serve as potential target genes for transcription factors. Overall, our study provides new insights into the pathophysiological mechanisms of HS, which may inspire new ideas for the diagnosis and treatment.
增生性瘢痕(HS)是一种慢性炎症性皮肤病,其特征是细胞外基质过度沉积,但与形成相关的确切机制尚不清楚,因此难以治疗。本研究旨在探讨铜死亡在 HS 信息中的潜在作用。为此,我们使用单细胞测序和批量转录组数据,通过差异基因分析和机器学习算法(随机森林和支持向量机)筛选铜死亡相关基因(CRGs)。通过这个过程,我们确定了一组基因,包括 ATP7A、ULK1 和 MTF1,作为 HS 的新治疗靶点。此外,我们还进行了定量实时聚合酶链反应(qRT-PCR),以验证 ATP7A、ULK1 和 MTF1 在 HS 和正常皮肤(NS)组织中的 mRNA 表达。我们还构建了 HS 的诊断模型,并分析了免疫浸润特征。此外,我们还使用 CRGs 的表达谱对 HS 进行亚组分析。我们主要关注转录组中单细胞分辨率的成纤维细胞。通过计算每个成纤维细胞的铜死亡活性,我们发现正常皮肤成纤维细胞的铜死亡活性增加,为 HS 的发病机制提供了进一步的见解。我们还分析了细胞通讯网络和转录因子调控网络的活性,发现 HS 中存在以成纤维细胞为中心的通讯调节网络,其中成纤维细胞的铜死亡活性影响细胞间通讯。通过转录因子调控活性网络分析,我们获得了高活性转录因子,与 CRGs 的相关性分析表明,CRGs 可能是转录因子的潜在靶基因。总的来说,我们的研究为 HS 的病理生理机制提供了新的见解,这可能为诊断和治疗提供新的思路。