Xia Yijun, Wang Youbin, Xiao Yingjie, Shan Mengjie, Hao Yan, Zhang Lingyun
Department of Plastic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Department of Plastic Surgery, Peking Union Medical College Hospital, Beijing, China.
Front Mol Biosci. 2022 May 20;9:879461. doi: 10.3389/fmolb.2022.879461. eCollection 2022.
Keloid disorder is a recurrent fibroproliferative cutaneous tumor. Due to the lack of early identification of keloid patients before the formation of keloids, it is impossible to carry out pre-traumatic intervention and prevention for these patients. This led us to identify and determine signatures with diagnostic significance for keloids. Public series of matrix files were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were calculated from expression profiling data, and the diagnostic signature was identified by constructing a protein-protein interaction (PPI) network. The diagnostic efficacy of the screened signature was assessed by employing receiver operating characteristic (ROC) curves. Furthermore, we calculated the proportion of different immune cells in the gene expression matrix microenvironment by the "ssGSEA" algorithm, and assessed the difference in immune cell abundance between keloids and control groups and the relationship between the signature and immune cell infiltration. Clinical keloid and normal skin tissues were collected, and the expression of the screened diagnostic signature was validated by RT-qPCR and immunohistochemical assay. By screening the key genes in PPI, TGM2 was recognized and validated as a diagnostic signature and the infiltrating abundance of 10 immune cells was significantly correlated with TGM2 expression. Gene ontology enrichment analysis demonstrated that TGM2 and molecules interacting with it were mainly enriched in processes involving wound healing and collagen fiber organization. TGM2 correlated positively with HIF-1A (R = 0.82, -value = 1.4e-05), IL6 (R = 0.62, -value = 0.0053), and FN1 (R = 0.66, -value = 0.0019). Besides, TGM2 was significantly upregulated in clinical keloid samples compared to normal skin tissues. TGM2 may serve as an auxiliary diagnostic indicator for keloids. However, the role of TGM2 in keloids has not been adequately reported in the current literature, which may provide a new direction for molecular studies of keloids.
瘢痕疙瘩是一种复发性纤维增生性皮肤肿瘤。由于在瘢痕疙瘩形成之前缺乏对瘢痕疙瘩患者的早期识别，因此无法对这些患者进行创伤前干预和预防。这促使我们识别并确定对瘢痕疙瘩具有诊断意义的特征。从基因表达综合数据库下载公共系列的矩阵文件。根据表达谱数据计算差异表达基因（DEG），并通过构建蛋白质-蛋白质相互作用（PPI）网络来识别诊断特征。采用受试者工作特征（ROC）曲线评估筛选出的特征的诊断效能。此外，我们通过“ssGSEA”算法计算基因表达矩阵微环境中不同免疫细胞的比例，并评估瘢痕疙瘩与对照组之间免疫细胞丰度的差异以及该特征与免疫细胞浸润的关系。收集临床瘢痕疙瘩和正常皮肤组织，并通过RT-qPCR和免疫组织化学分析验证筛选出的诊断特征的表达。通过筛选PPI中的关键基因，发现并验证TGM2作为诊断特征，并且10种免疫细胞的浸润丰度与TGM2表达显著相关。基因本体富集分析表明，TGM2及其相互作用分子主要富集在涉及伤口愈合和胶原纤维组织的过程中。TGM2与HIF-1A（R = 0.82，P值 = 1.4e-05）、IL6（R = 0.62，P值 = 0.0053）和FN1（R = 0.66，P值 = 0.0019）呈正相关。此外，与正常皮肤组织相比，临床瘢痕疙瘩样本中TGM2显著上调。TGM2可能作为瘢痕疙瘩的辅助诊断指标。然而，目前文献中尚未充分报道TGM2在瘢痕疙瘩中的作用，这可能为瘢痕疙瘩的分子研究提供新的方向。
