2025 Proffered Presentations
S088: IDENTIFYING GENES THAT COULD DETERMINE PROGNOSTICATION IN SINONASAL SQUAMOUS CELL CARCINOMA
Peter Filip, MD1; Tasher A Losenegger, MD1; Rachel Akers, MS1; Glen D Souza, MD1; Jacob Scott1; Sarah Khalife, MD2; Edward C Kuan, MD3; Pete S Batra, MD1; Bobby A Tajudeen, MD1; Peter Papagiannopoulos, MD1; 1Rush University Medical Center; 2McMaster University; 3University of California Irvine
Background: Sinonasal squamous cell carcinoma (SNSCC) is a multifaceted pathology, with several different genetic components and known etiologies. These differences create variable prognoses and pose a unique challenge to skull base surgeons. SNSCC has been studied in several instances, but most literature analyzes specific genes in isolation, which may leave key targets for therapy unidentified. RNA and DNA sequencing can help with identifying prognostic factors as well as in the development of molecular targets in the management of sinonasal squamous cell carcinoma. While individual genes and their role in prognosis have been studied, the effect that a group of genes have on prognosis is unclear.
Objective: To assess the relationship between genetic mutations and overall survival in SNSCC.
Methods: 19 SNSCC samples were analyzed using the Tempus xT panel, a third-party DNA and RNA sequencing service, with accompanying chart review for demographic and survival data. This panel detects single nucleotide variants, indels, and copy number variants in 648 genes and chromosomal rearrangements in a subset of 21 genes. A log-rank test was performed for each gene type to compare overall survival. Logistic regression was also performed to analyze the association between mutation type and demographic characteristics.
Results: 79% of research subjects were male with a mean age of 67 years (range 48-92). At time of diagnosis, 84% of participants were stage T4, and 3 tumors were associated with inverted papillomas. Among patients with documented mortality, mean survival was 23 months, while those without documented mortality had a mean follow-up of 42 months.
The most frequent mutations were P53 (74%), KMT2D (42%), CDKN2A (26%), CDKN2B (21%), EGFR (21%), FAT1 (21%), and MTAP (21%). Gain of function mutations in CUL1 and EZH2 were found to be associated with higher risk of mortality (p = 0.0247). Increased mortality rates were associated with deletion of several genes including ING5, BRAF pseudogene, PRDM11, MAP2K, PSMD2, ELMOD1, LGMN, RMND5B, PNLIPRP1, RAI1, RP11, and TMEM66 (p = 0.0359). Deletions of APOA1, CYP2D6, EMC3, FCRL3, HLA-DBQ1, HOXA11, RBPMS, SEC24A, and TMC4 were also found to be associated with higher mortality (p < 0.001). No specific gene mutations were associated with mortality within 12 months of diagnosis, T4 status at diagnosis, or poorly differentiated tumors. Similarly, overall tumor mutation burden did not correlate with these outcomes.
Conclusion: This study provides a comprehensive genomic analysis of SNSCC and identifies new targets associated with increased mortality risks. Larger studies are required to confirm these findings and help with possible molecular treatment strategies.