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North American Skull Base Society

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2025 Proffered Presentations

2025 Proffered Presentations

 

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S321: CHARACTERIZING COMMON MUTATIONS IN NASOPHARYNGEAL CARCINOMAS: PATHWAYS TO TARGETED THERAPY DEVELOPMENT
Beau Hsia, BS1; Gabriel Bitar, BS1; Saif Alshaka, BS1; Mariko Sato, MD, PhD2; John Crawford, MD2; Michael L Levy, MD, PhD3; Danielle Levy, MD3; Bastien A Valencia, MD4; Jeeho Kim, MD5; Farhoud Faraji, MD, PhD6; Vijay A Patel, MD6; Sean Polster, MD7; 1Creighton University School of Medicine; 2Pediatrics, University of California Irvine; 3Department of Neurosurgery, University of California San Diego, Rady Children's Hospital - San Diego; 4Department of Otolaryngology - Head and Neck Surgery, Mayo Clinic, Jacksonville, Florida; 5Naval Medical Center San Diego; 6Division of Pediatric Otolaryngology, Rady Children's Hospital - San Diego; 7Department of Neurosurgery, University of Chicago

Purpose: Nasopharyngeal carcinomas (NPC) are malignant neoplasms arising from the epithelial cells of the nasopharyngeal mucosa. They are typically associated with Epstein-Barr virus infection and characterized by unique histopathological features and epidemiological distribution but have limited information on their somatic mutational landscape. Current treatment options for NPC include first-line chemoradiation or salvage surgery for refractory tumors. There are also ongoing clinical trials evaluating the efficacy of  PD-1/PDL-1 checkpoint inhibitors in NPC, such as Tislelizumab, Pembrolizumab, and Camrelizumab. This work aims to identify common mutations and genetic alterations to understand the genetic basis of NPC in support of the development of targeted therapies. 

Methods: The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE)® database was accessed from cBioPortal (v16.1-public) on July 22, 2024 to identify all patients with nasopharyngeal carcinoma. The most common gene mutations, gene correlations, and mutual exclusivities were assessed using a two-sided T-test and non-parametric tests, with Benjamini-Hochberg False Discovery Rate (FDR) correction.

Results: Of the 2595 sequenced samples of head and neck cancers, 125 (4.8%) were of nasopharyngeal carcinoma, collected from 119 unique patients. In this cohort, there were 48 (40.3%) Asian, 30 (25.2%) White, and 15 (12.6%) Black patients. 79 (66.4%) patients were male and 40 (33.6%) were female. 4 (3.4%) patients were pediatric and the rest were adults (n=121; 96.6%). The top mutations in the cohort were: KMT2D (n=25; 20.0%), TP53 (n=20; 17%), CYLD (n=12; 9.6%), FAT1 (n=8; 6.4%), NFKBIA (n=8; 6.4%), PIK3CA (n=7; 5.6%), and SPEN (n=7; 5.6%).  There were no significant clinical differences between Asian and non-Asian patients, but the TP53 mutation was enriched in non-Asian patients (p=0.0361). There were no specific mutation types (missense, nonsense, etc.) associated with the top three mutations KMT2D, TP53, or CYLD. In this cohort, KMT2D mutations tended to co-occur with PIK3CA (n=3; 12.0%; p=0.020) and FAT1 (n=2; 8.0%; p=0.025), while TP53 tended to co-occur with SPEN (n=3; 15.0%; p=0.020), suggesting that KMT2D mutations are associated with alterations in genes important in cell growth and survival (PIK3CA) and cell adhesion and signaling pathways (FAT1), while TP53 mutations are linked with genes involved in transcriptional regulation and Notch signaling (SPEN). KMT2D, TP53, or CYLD were relatively mutually exclusive, with the majority of cases (n=123; 98.0%) holding no more than one of these top three mutation types.

Conclusions: KMT2D, TP53, and CYLD mutations account for approximately half of somatic mutations in nasopharyngeal carcinoma. Currently, there are clinical trials for PD-1/PDL-1 checkpoint inhibitors that might be more effective in tumors with TP53 mutations due to increased immunogenicity. However, there are limited clinical trials evaluating direct targeted therapies against these three most common mutations. Understanding these mutational landscapes may accelerate the development of novel NPC preclinical models for targeted therapy testing.

 

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