Unraveling the complexities of immunotherapy for thymic epithelial tumors via bioinformatics and experimental analyses

Introduction: Thymic epithelial tumors (TETs) are rare neoplasms typically located in the anterior mediastinum. While immune checkpoint inhibitors (ICIs) show promise for advanced or refractory TETs, their clinical application is hindered by heterogeneous responses across TET subtypes, lack of reliable predictive markers, and the risk of immune-related adverse events (irAEs). Methods: We analyzed TCGA, GEO, and GTEx databases to identify differentially expressed genes (DEGs) among three TET subtypes. Comprehensive enrichment analysis determined gene functions and pathways. CIBERSORT analysis revealed subtype-specific immune infiltration profiles. We assessed immune-related genes using immune/stromal scores, TIDE scores, and immune checkpoint gene correlation analysis. Immunohistochemistry was performed to evaluate FGF17 and PD-L1 protein expression levels and their correlation in TET samples. Results: Our findings revealed distinctive molecular and immune infiltration patterns across TET subtypes. Pathway analysis showed upregulation of immune-related pathways in type C. CIBERSORT analysis revealed higher fractions of plasma cells and activated CD4 T cells in type C and increased resting dendritic cells in type A or B3. Furthermore, we identified 1,100 DEGs between responders and non-responders to pembrolizumab. FGF17 emerged as a potential predictive marker for immunotherapy response, showing significantly lower expression in type C and a strong negative correlation with PD-L1 expression (P © 2024