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

Abstract

BACKGROUND Recurrent and/or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) is generally an incurable disease, with patients experiencing median survival of under 10 months and significant morbidity. While immune checkpoint blockade (ICB) drugs are effective in approximately 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 a modest predictive value in HNSCC. METHODS We analyzed clinical and genomic features, generated using whole-exome sequencing, in 133 ICB-treated patients with R/M HNSCC, of whom 69 had virus-associated and 64 had non-virus-associated tumors. RESULTS Hierarchical clustering of genomic data revealed 6 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 did a model based on TMB alone. Recursive partitioning analysis identified 3 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 responses to ICB and identify a clinical-genomic classifier that outperformed 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. FUNDING Fundación Alfonso Martín Escudero, NIH R01 DE027738, US Department of Defense CA210784, The Geoffrey Beene Cancer Research Center, The MSKCC Population Science Research Program, the Jayme Flowers Fund, the Sebastian Nativo Fund, and the NIH/NCI Cancer Center Support Grant P30 CA008748.

Tumor mutational burden predictability in head and neck squamous cell carcinoma patients treated with immunotherapy: systematic review and meta-analysis

“…See Additional file 1 : Table S3 presents study characteristics, while Additional file 1 : Table S4 provides a summary of the key findings. This meta-analysis included a total of 1200 patients, with each study ranging from 10 to 257 patients, and two studies [ 25 , 27 ] including two different cohorts. Among the 11 included studies, seven studies were conducted in the USA, while single studies were performed in Japan, Italy and China, and another across multiple geographic areas.…”

“…Another study determined the optimal value using the Cox proportional hazards model, setting 10 muts/Mb as a cut-off [ 25 ], while another one employed R language survival package analysis to determine a cut-off value of 2.54 [ 24 ]. In addition, one study determined the optimal cut-point using the Youden Index, setting it at 86.0 muts/exome [ 26 ], in another a threshold for TMB was chosen to attain the best performance in predicting progression free survival (PFS) in a univariable survival model, setting it at 3.34 muts/Mb [ 27 ], whereas in the remaining study the method used to obtain the cut-off value was not specified [ 19 ].…”

“…The pooled ORR for ICI treatment was evaluated across seven studies (eight cohorts) involving 623 patients, using a random-effects model [ 18 – 22 , 26 , 27 ]. The group of patients with high TMB exhibited a superior ORR (OR = 2.62, 95% CI 1.74–3.94, p < 0.0001; Fig.…”

Host-related indexes in head and neck cancer

“…When analyzing the features that contributed to this prediction, we can find multiple host-related factors such as age, sex, BMI, and it also included several parameters from the peripheral blood such as NLR, albumin, hemoglobin and platelets [53 ▪▪ ]. In a study conducted specifically in head and neck cancer patients treated with immunotherapy, similar to the previous study, clinical and genomic factors were included in a model trying to predict response to immunotherapy, and interestingly, the second feature that contributed more to the predictive capacity was SIRI [54 ▪▪ ]. Additionally, a low albumin level has also been shown to predict worse response and survival to immunotherapy in a study conducted in multiple cancer types, including head and neck cancer [55 ▪▪ ].…”

“…Again, to the point of the predictive value, it has started to be used as a predictive tool in models including multiple tumor and host factors in patients treated with immunotherapy [53 ▪▪ ,54 ▪▪ ].…”