Interference of tumour mutational burden with outcome of patients with head and neck cancer treated with definitive chemoradiation: a multicentre retrospective study of the German Cancer Consortium Radiation Oncology Group

Background: Tumour mutational burden (TMB) estimated from whole exome sequencing or comprehensive gene panels has previously been established as predictive factor of response to immune checkpoint inhibitors (ICIs). Its predictive value for the efficacy of concurrent chemoradiation (cCRTX), a potential combination partner of ICI, remains unknown. Methods: The accuracy of TMB estimation by an in-house 327-gene panel was established in the Cancer Genome Atlas (TCGA) head and neck squamous cell carcinoma (HNSCC) data set. Interference of TMB with outcome after cCRTX was determined in a multicentre cohort of patients with locally advanced HNSCC uniformly treated with cCRTX. Targeted next-generation sequencing was successfully applied in 101 formalin-fixed, paraffin-embedded pretreatment tumour samples. In a subset of cases (n = 40), tumour RNA was used for immune-related gene expression profiling by the nanoString platform. TMB was correlated with TP53 genotype, human papilloma virus (HPV) status, immune expression signatures and survival parameters. Results were validated in the TCGA HNSCC cohort. Results: A high accuracy of TMB estimation by the 327-gene panel was established. High TMB was significantly associated with an increased prevalence of TP53 mutations and immune gene expression patterns unrelated to T cell-inflamed gene expression profiles. Kaplan-Meier analysis revealed significantly reduced overall survival in the patient group with high TMB (hazard ratio for death: 1.79, 95% confidence interval: 1.02-3.14; P = 0.042) which remained significant after correcting for confounding factors in the multivariate model. The prognostic value of TMB was confirmed in the TCGA HNSCC cohort. Conclusion: High TMB identifies HNSCC patients with poor outcome after cCRTX who might preferentially benefit from CRTX-ICI combinations. (C) 2019 Elsevier Ltd. All rights reserved.