Abstract C068: HPV+ and HPV- Head and Neck Cancer Patient-derived Models in the NCI Patient-Derived Models Repository
Abstract Head and neck (HN) cancers are a rare set of cancers defined by their anatomical point of origin including mouth, sinus, throat, or nose. Human papilloma virus (HPV) infection plays a pathogenic role in HN cancers resulting in distinct clinical and molecular characteristics from those that are HPV-. The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), organoids (PDOrg), tumor cell cultures (PDCs) and cancer associated fibroblasts (CAFs). These models are clinically annotated with molecular information available in a public database for the extramural community. To date, 361 patient HN tumor specimens have been received from 351 unique patients across a range of histologies including lip/oral, pharyngeal, laryngeal, salivary and sinonasal with an overall PDX take rate of 48% (322 assessable specimens). The NCI PDMR currently has 200 public HN PDX, PDOrg, and PDC models from 124 unique patients. Thirty-three models (PDX, PDOrg, PDC) from 20 unique patients are positive for HPV16 or 18 (one double positive) as detected by PCR and one sinonasal PDOrg model is positive for HPV33 identified in NextGenSeq data. As has been reported in the clinical literature TP53 and CDKN2A mutations are found predominantly in PDX models that are HPV- (84% and 65%, respectively) but not HPV+ (0%; 0%) and PIK3CA is more commonly mutated in HPV+ PDX models (47% vs 25%). No significant difference in loss of heterozygosity is observed in the models. However, significant differences in chromosome arm copy number changes (copy gains in 7p, 11p and 12p and copy losses in 3p, 9p and 18q [P-value<0.05; Wilcoxon Rank-Sum test]) are observed in HPV- compared to HPV+ models. Gene set enrichment analysis (GSEA) suggest the E2F_TARGETS, G2M_CHECKPOINT, and DNA_REPAIR gene sets are significantly up-regulated in HPV+ while the APOPTOSIS gene set is significantly down-regulated using MSigDB Hallmark dataset (P-value<0.05). In all analyses, differences are consistent whether examining in vivo PDX models or in vitro PDC/PDOrg models indicating the fidelity of the models. These preclinical models recapitulate the molecular differences reported in HPV+ versus HPV- clinical cases providing an important tool for the development of novel therapeutics for HN cancers. Funded by NCI Contract No. HHSN261200800001E Citation Format: Yvonne A. Evrard, Ting-Chia Chang, Jasmine B'Lanton, Gareth Bliss, Alice Chen, Li Chen, Kevin Cooper, Kristin Cox, Natalie Czarra, Isabella Czernia, Biswajit Das, Kelly Dougherty, Aarin Dreyer, Lindsay Dutko, Katie Frey, Marion Gibson, Tara Grinnage-Pulley, Shahanawaz Jiwani, Poorva Juneja, Keegan Kalmbach, Tamikia Lamb, Eva Loewenstein, Candace Mallow, Chelsea McGlynn, Justine Mills, Michael Mullendore, Matthew Murphy, Sandra Navas-Reyes, Michelle Norris, Jessica Park, Kaci Paulus, Kevin Plater, Tia Shearer, Jessica Steed, Luke H. Stockwin, Howard Stotler, Ruth Thornton, Cindy R. Timme, Shannon Uzelac, Dianne L. Newton, Chris A. Karlovich, P Mickey. Williams, Melinda G. Hollingshead, James H. Doroshow. HPV+ and HPV- Head and Neck Cancer Patient-derived Models in the NCI Patient-Derived Models Repository [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2025 Oct 22-26; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2025;24(10 Suppl):Abstract nr C068.
Authors
- Ting-Chia Chang (ORCID: https://orcid.org/0000-0001-6296-5797)
- Cindy R. Timme
- Katie Frey (ORCID: https://orcid.org/0000-0001-9891-4465)
- Dianne L. Newton
- J. Lewis Blanton
- Jessica Park
- Chris Karlovich (ORCID: https://orcid.org/0000-0002-4617-2161)
- Shannon Uzelac
- Matthew Murphy
- Ruth Thornton (ORCID: https://orcid.org/0009-0006-4041-0233)
- E. Loëwenstein
- Kristin E. Cox (ORCID: https://orcid.org/0000-0001-8621-1869)
- Kelly Dougherty
- James H. Doroshow (ORCID: https://orcid.org/0000-0002-4463-1790)
- Yvonne A. Evrard (ORCID: https://orcid.org/0000-0002-3475-4850)
- Justine Mills
- Keegan Kalmbach
- Gareth Bliss
- Tia Shearer
- Kevin Cooper
- Shahanawaz Jiwani (ORCID: https://orcid.org/0000-0002-4717-8637)
- Michelle Norris
- Lindsay Dutko
- Tammy Lamb
- Candace Mallow
- Chelsea McGlynn
- Marion Gibson
- Howard Stotler
- Andries Dreyer
- Sandra Navas-Reyes
- Kevin Plater
- Tara Grinnage‐Pulley (ORCID: https://orcid.org/0000-0002-7797-4642)
- Biswajit Das (ORCID: https://orcid.org/0000-0002-1929-3646)
- Melinda G. Hollingshead (ORCID: https://orcid.org/0000-0002-1207-1397)
- Jessica Steed
- Poorva Juneja
- Luke H. Stockwin
- Natalie Czarra
- Isabella Czernia
- Li Chen (ORCID: https://orcid.org/0000-0001-7922-0599)
- Paul M. Williams
- Michael E. Mullendore
- Alice Chen (ORCID: https://orcid.org/0000-0002-4987-2665)
- Katharina Paulus
Institutions
- Frederick National Laboratory for Cancer Research (US)
- National Cancer Institute (US)
Publication Details
- Journal
- Molecular Cancer Therapeutics
- Published
- 2025-10-22
- DOI
- https://doi.org/10.1158/1535-7163.targ-25-c068
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00