Integrated bioinformatic analysis identifies ferroptosis-related biomarkers and subtypes in invasive aspergillosis

Invasive aspergillosis (IA) is a severe fungal infection with complex pathogenesis, and the role of ferroptosis, an iron-dependent regulated cell death, in IA remains largely unexplored. This study investigates the association between ferroptosis and IA using a bioinformatics approach. We analyzed the GSE78000 dataset to assess ferroptosis activity and identify differentially expressed genes (DEGs). Ferroptosis-related genes (FRGs) were curated from literature, and protein–protein interaction (PPI) networks and functional enrichment analyses (GO and KEGG) were performed. Three machine learning algorithms (SVM, LASSO, and Random Forest) identified five core FRGs (KIF20A, PEBP1, HMOX1, MTF1, QSOX1), which exhibited excellent diagnostic potential (AUCs: 0.884–0.981). IA patients were categorized into two ferroptosis-related subtypes (C1 and C2), characterized by distinct molecular profiles and pathway enrichments, such as ribosome biogenesis and DNA replication. Immune cell infiltration analysis, using ssGSEA, revealed significant alterations in IA, with increased innate immune cells (macrophages, neutrophils) positively correlating with core FRG expression, while adaptive immune cells (B cells, T cells) were decreased. Our findings indicate that ferroptosis is critically involved in IA pathogenesis, with identified core FRGs serving as promising diagnostic biomarkers. The revealed heterogeneity among IA patients and the interaction between ferroptosis and the immune microenvironment provide new insights into the disease’s molecular mechanisms and potential therapeutic targets for further investigation.