Unraveling most abundant mutational signatures in head and neck cancer
Michaela Plath, Johanna Gass, Mario Hlevnjak, Qiaoli Li, Bohai Feng, Xavier Pastor Hostench, Matthias Bieg, Lea Schroeder, Dana Holzinger, Marc Zapatka, Kolja Freier, Wilko Weichert, Jochen Heß, Karim Zaoui
Abstract
Abstract Genomic alterations are a driving force in the multistep process of head and neck cancer (HNC) and result from the interaction of exogenous environmental exposures and endogenous cellular processes. Each of these processes leaves a characteristic pattern of mutations on the tumor genome providing the unique opportunity to decipher specific signatures of mutational processes operative during HNC pathogenesis and to address their prognostic value. Computational analysis of whole exome sequencing data of the HIPO‐HNC (Heidelberg Center for Personalized Oncology‐head and neck cancer) (n = 83) and TCGA‐HNSC (The Cancer Genome Atlas‐Head and Neck Squamous Cell Carcinoma) (n = 506) cohorts revealed five common mutational signatures (Catalogue of Somatic Mutations in Cancer [COSMIC] Signatures 1, 2, 3, 13 and 16) and demonstrated their significant association with etiological risk factors (tobacco, alcohol and HPV16). Unsupervised hierarchical clustering identified four clusters (A, B, C1 and C2) of which Subcluster C2 was enriched for cases with a higher frequency of signature 16 mutations. Tumors of Subcluster C2 had significantly lower p16 INK4A expression accompanied by homozygous CDKN2A deletion in almost one half of cases. Survival analysis revealed an unfavorable prognosis for patients with tumors characterized by a higher mutation burden attributed to signature 16 as well as cases in Subcluster C2. Finally, a LASSO‐Cox regression model was applied to prioritize clinically relevant signatures and to establish a prognostic risk score for head and neck squamous cell carcinoma patients. In conclusion, our study provides a proof of concept that computational analysis of somatic mutational signatures is not only a powerful tool to decipher environmental and intrinsic processes in the pathogenesis of HNC, but could also pave the way to establish reliable prognostic patterns.