Exploration of shared biomarkers and mechanisms in systemic lupus erythematous and lung cancer via bioinformatics analysis.

Systemic lupus erythematosus (SLE) patients exhibit a heightened risk of developing lung cancer, yet the underlying molecular mechanisms remain poorly understood. This study aimed to identify shared genetic factors linking SLE and LC using publicly available transcriptomic data from the Gene Expression Omnibus (GEO). Through integrated differentially expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA), we identified five genes consistently upregulated in both SLE and lung cancer. Gene set enrichment analysis (GSEA) revealed that these shared genes were enriched in inflammatory pathways, particularly those involving interferon-alpha, interferon-gamma, and general inflammatory responses. We applied least absolute shrinkage and selection operator (LASSO) regression to pinpoint potential diagnostic biomarkers and identified two key candidates: AIM2 and SLC26A8. These biomarkers demonstrated robust diagnostic performance with area under the ROC curve (AUC) values exceeding 0.75 in both training and validation cohorts. Immune infiltration and survival analyses using The Cancer Genome Atlas (TCGA) further supported their clinical relevance. Notably, high AIM2 expression was significantly associated with poorer overall survival in female lung adenocarcinoma patients (P = 0.03), and SLC26A8 expression was significantly linked to survival outcomes only in patients with a history of smoking (P = 0.01). These findings are particularly meaningful in SLE, where most patients are female and smoking is a known risk factor. Our study enhances the understanding of autoimmune-driven carcinogenesis and opens new avenues for precision medicine strategies in managing patients with SLE at risk for lung cancer.