AUTHOR=Mao Jing , Lan Jianping , Zhuang Zheyu , Chen Ying , Ou Yushan , Su Xinhong , Zeng Xueting , Huang Fuchen , Tong Zequn , Lv Xiaoqing , Ke Hui , Wu Zhenlan , Zou Ying , Cheng Bo , Ji Chao , Gong Ting 

TITLE=Exploring the role of ferroptosis in pemphigus: identification of diagnostic markers and regulatory mechanisms

JOURNAL=Frontiers in Medicine

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1615865

DOI=10.3389/fmed.2025.1615865

ISSN=2296-858X

ABSTRACT=BackgroundPemphigus is an autoimmune blistering disorder characterized by the loss of cell adhesion in the epidermis. Recent studies have suggested a potential link between ferroptosis, a form of regulated cell death dependent on iron, and various diseases. However, the role of ferroptosis-related genes in pemphigus remains largely unexplored. This study aims to investigate the expression patterns and potential biological functions of ferroptosis-related genes in pemphigus, as well as their regulatory mechanisms.MethodsTo achieve this, skin samples from five pemphigus patients and five healthy controls were collected from Fujian Medical University Union Hospital. Additionally, we processed the GSE53873 microarray dataset, which includes 19 pemphigus samples and 5 controls. Differentially expressed genes (DEGs) were identified using the limma R package, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Weighted Gene Co-expression Network Analysis (WGCNA) was employed to identify co-expressed gene modules related to pemphigus. Machine learning algorithms such as Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) were used to select key ferroptosis-related genes. Immune cell infiltration was assessed using CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA). Finally, experimental validation was conducted through real-time quantitative PCR, transmission electron microscopy, and drug prediction.ResultsOur results identified 1,840 DEGs in pemphigus patients compared to controls, with significant enrichment in pathways such as PI3K-Akt signaling and fatty acid metabolism. Eleven co-expression modules were identified via WGCNA, with the module highlighted in lightcyan color showing the strongest correlation with pemphigus. Machine learning highlighted ACSL4, SAT2, and XBP1 as potential hub genes with high diagnostic value. Immune analysis revealed increased proportions of activated CD8+ T cells and natural killer cells in pemphigus patients. Experimental validation confirmed the presence of ferroptosis morphological features in patient samples.ConclusionIn conclusion, this study elucidates the involvement of ferroptosis-related genes in pemphigus pathogenesis and identifies potential biomarkers for diagnosis. Further research is warranted to explore therapeutic strategies targeting these pathways.