Deciphering the Overlapping Immune Mechanism Between Depression and Breast Cancer

Depression and breast cancer (BC) demonstrate significant clinical comorbidity, yet their shared molecular mechanisms remain unclear, particularly regarding immune pathway regulation. This study systematically analyzed Depression-associated gene expression profiles (Gene Expression Omnibus (GEO) database) and BC transcriptomic data (The Cancer Genome Atlas (TCGA) database), identifying overlapping differentially expressed genes (DEGs). Functional enrichment (Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG)) and protein-protein interaction (PPI) network analyses (STRING/Cytoscape) were employed to elucidate biological processes, followed by least absolute shrinkage and selection operator (LASSO) regression and receiver operating characteristic (ROC) curve validation to prioritize key genes. Immune infiltration patterns were assessed via the xCell algorithm, with Spearman correlation linking genes to immune subsets, and single-gene Gene Set Enrichment Analysis (GSEA) evaluating pathway activity. In total, 93 overlapping genes were identified, with predominant involvement in immune-related pathways being revealed by functional enrichment analysis. <i>BHLHE41</i>, <i>EpCAM</i>, and <i>GSTM2</i> were prioritized as mechanism-associated genes through integrated LASSO regression and ROC analyses. Significant correlations were observed between these genes and specific immune cell populations. GSEA further linked these genes to immune response pathways, suggesting their regulatory roles. These findings highlight immune dysregulation as a shared mechanism underlying Depression-BC comorbidity, providing a foundation for developing early diagnostic strategies and therapeutic strategies targeting both conditions.