Evaluation of computational tools to determine prognostic significance of TP53 mutation in head and neck squamous cell carcinoma (HNSCC).

6035 Background: TP53 is the most commonly mutated gene in HNSCC. The specific mutations in TP53 can be prognostic of patient survival. Thus, a framework to predict patient survival from previously uncharacterized mutation in TP53 is valuable. There are many computational tools for predicting the phenotypic impact of genetic variation, but the overall clinical value of these algorithms remains unclear. Methods: Sixteen different models to predict HNSCC patient survival based on TP53 mutations were assessed using the TP53 mutation and clinical data from ECOG 4393 [Poeta, M. L., et al. NEJM (2007) 357(25) 2552-2561]. These models include: server-based computational tools SIFT, PolyPhen-2, and Align-GVGD; our in-house POSE and VEST algorithms; the rules devised in Poeta et al.1 with and without considerations for splice-site mutations; location of mutation in the DNA-bound TP53 protein structure; and a functional assay measuring WAF1 transactivation in TP53-mutated yeast. Results: We assessed model performan...