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 < 0.001). We identified 115 genes potentially linked to irAEs, with CXCL8, IL17A, and CD40LG among the top hub genes in the protein-protein interaction network.

CONCLUSIONS

This study provides insights into subtype-specific molecular and immune characteristics of TETs, identifies FGF17 as a potential negative biomarker for immunotherapy response (with lower expression potentially indicating better response), and elucidates mechanisms of irAEs. These findings contribute to the development of targeted immunotherapeutic approaches for managing TETs, particularly in predicting response to immune checkpoint inhibitors.