Abstract A03: Predictors of HPV-related head and neck cancer progression identified through patient-derived models

Purpose/Objectives: Therapeutic innovation for human papilloma virus-related (HPV+) head and neck squamous cell carcinomas (HNSCCs) is hindered by both inadequate biomarkers and a paucity of experimental models. To address these limitations, this study aimed to establish the first well-characterized panel of patient-derived xenografts (PDXs) and organoids from HPV+ HNSCCs, which typically grow poorly outside humans. The models were hypothesized to retain molecular hallmarks of HPV+ HNSCC that are lost in cell lines. In addition, genotype-phenotype correlations in the models were hypothesized to offer prognostic utility for patients. Materials/Methods: Whole-exome sequencing was performed on 20 HNSCC PDXs, including nine new HPV+ PDXs. Results were compared against the known genetic profiles of human HPV+ HNSCCs and their derivative cell lines. Genetic traits of the PDXs were subsequently evaluated relative to their growth properties and the outcomes of their patients of origin. Genotype-phenotype associations in the models were then tested for prognostic utility across multiple published patient cohorts. Results: Despite low engraftment rates, HPV+ PDXs retained multiple molecular features of HPV+ HNSCC lost in cell lines, including PIK3CA mutations, TRAF3 deletion, and absence of EGFR amplifications. Selective engraftment notably enriched for NOTCH1 mutants, thus providing new models for this negatively prognostic feature in HPV+ HNSCC. Observation of high tumor mutational burden (TMB) in faster-growing models facilitated detection of a novel association between TMB and local progression in both HPV+ and HPV- patients. Whereas TMB’s prognostic utility was limited to early stage HPV- tumors, outcomes prediction for HPV+ cases was served by features of an HPV+ PDX from an outlier case with lethal outcome. Reduced E7 and p16INK4A levels found in this PDX led to detection of similar profiles among recurrent HPV+ HNSCCs in two patient cohorts. Further analysis of the same cohorts revealed lower E2F target gene expression downstream of reduced E7 levels to be predictive of recurrence and mortality. Conclusions: Our PDXs are the first models systematically shown to retain the distinguishing genetic hallmarks of HPV+ HNSCC lost in cancer cell lines. Beyond bridging the critical gap in experimental models, these materials revealed novel applications for quantifying TMB and viral oncogene effects in biomarker development. Our findings suggest that E2F target transcript levels allow discrimination of HPV+ HNSCC patients at risk of treatment failure. Emerging evidence that low E2F target expression in poor-prognosis cases is part of a wider decrease in the viral imprint upon host gene expression holds promise for development of molecular risk stratifiers with clinical utility. Citation Format: Nicole D. Facompre, Pavithra Rajagopalan, Varun Sahu, Frederico O. Gleber-Netto, Joseph A. Califano, Curtis R. Pickering, Phyllis A. Gimotty, Devraj Basu. Predictors of HPV-related head and neck cancer progression identified through patient-derived models [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr A03.