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  • Title: Identifying predictors of HPV-related head and neck squamous cell carcinoma progression and survival through patient-derived models.
    Author: Facompre ND, Rajagopalan P, Sahu V, Pearson AT, Montone KT, James CD, Gleber-Netto FO, Weinstein GS, Jalaly J, Lin A, Rustgi AK, Nakagawa H, Califano JA, Pickering CR, White EA, Windle BE, Morgan IM, Cohen RB, Gimotty PA, Basu D.
    Journal: Int J Cancer; 2020 Dec 01; 147(11):3236-3249. PubMed ID: 32478869.
    Abstract:
    Therapeutic innovation for human papilloma virus-related (HPV+) head and neck squamous cell carcinomas (HNSCCs) is impaired by inadequate preclinical models and the absence of accurate biomarkers. Our study establishes the first well-characterized panel of patient-derived xenografts (PDXs) and organoids from HPV+ HNSCCs while determining fidelity of the models to the distinguishing genetic features of this cancer type. Despite low engraftment rates, whole exome sequencing showed that PDXs retain multiple distinguishing features of HPV+ HNSCC lost in existing cell lines, including PIK3CA mutations, TRAF3 deletion and the absence of EGFR amplifications. Engrafted HPV+ tumors frequently contained NOTCH1 mutations, thus providing new models for a negatively prognostic alteration in this disease. Genotype-phenotype associations in the models were then tested for prediction of tumor progression and survival in published clinical cohorts. Observation of high tumor mutational burdens (TMBs) in the faster-growing models facilitated identification of a novel association between TMB and local progression in both HPV+ and HPV- patients that was prognostic in HPV- cases. In addition, reduced E7 and p16INK4A levels found in a PDX from an outlier case with lethal outcome led to detection of similar profiles among recurrent HPV+ HNSCCs. Transcriptional data from the Cancer Genome Atlas was used to demonstrate that the lower E2F target gene expression predicted by reduced E7 levels has potential as a biomarker of disease recurrence risk. Our findings bridge a critical gap in preclinical models for HPV+ HNSCCs and simultaneously reveal novel potential applications of quantifying mutational burden and viral oncogene functions for biomarker development.
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