Clinical-genomic determinants of immune checkpoint blockade response in head and neck squamous cell carcinoma

BACKGROUND Recurrent and/or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) is often an incurable disease, with patients experiencing median survival of under ten months and significant morbidity. While immune checkpoint blockade (ICB) drugs are effective in ~20% of patients, the remaining experience limited clinical benefit and are exposed to potential adverse effects and financial costs. Clinically approved biomarkers, such as tumor mutational burden (TMB), have modest predictive value in HNSCC. METHODS We analyze clinical and genomic features, generated using whole-exome sequencing, in 133 ICB-treated R/M HNSCC patients, of whom 69 had virus-associated and 64 had non-virus-associated tumors. RESULTS Hierarchical clustering of genomic data revealed six molecular subtypes characterized by a wide range of objective response rates and survival after ICB therapy. The prognostic importance of these 6 subtypes was validated in an external cohort. A random forest-based predictive model, using several clinical and genomic features, predicted progression-free survival (PFS), overall survival (OS), and response with greater accuracy than a model based on TMB alone. Recursive partitioning analysis identified three features (systemic inflammatory response index, TMB, and smoking signature) that classified patients into risk groups with accurate discrimination of PFS and OS. CONCLUSION These findings shed light on the immunogenomic characteristics of HNSCC tumors that drive differential response to ICB and identify a clinical-genomic classifier that outperforms the current clinically approved biomarker of TMB. This validated predictive tool may help with clinical risk stratification in patients with R/M HNSCC for whom ICB is being considered.