Whole exome sequencing of sinonasal cancers.

Authors

null

Priyanka Bhateja

The Ohio State University Wexner Medical Center, Columbus, OH

Priyanka Bhateja , Ayse Selen Yilmaz , Sachin R. Jhawar , Sujith Baliga , Emile Gogineni , Darrion L Mitchell , Riccardo Carrau , Dukagjin Blakaj , Marcelo Raul Bonomi

Organizations

The Ohio State University Wexner Medical Center, Columbus, OH, The Ohio State University, Columbus, OH, The Ohio State University-James Cancer Hospital Solove Research Institute, Columbus, OH, The Ohio State University - James Cancer Hospital and Solove Research Institute, Columbus, OH, James Cancer Hospital and Solove Research Institute, The Ohio State University, Columbus, OH, James Cancer Hospital Solove Research Institute, The Ohio State University, Columbus, OH

Research Funding

Institutional Funding
Ohio State Start up Funds

Background: Sinonasal cancers are a rare group of heterogenous cancers arising in the nasal cavity and sinuses. Understanding the genomics alterations of these tumors can help identify subgroups with additional targets. Methods: Oncology Research Information Exchange Network (ORIEN) is an alliance of cancer centers, powered by M2GEN. ORIEN Avatar samples are extracted, and the libraries are prepared to be sequenced by M2Gen. Somatic Calls for 38 samples (with diagnosis ICD 10 code 30.0 to 31.9) from 36 patients are downloaded from DNA Nexus platform. Annotated somatic calls are first filtered based on 55 OncoKB genes and then aggregated variant level and patient level based on three different levels on stringency: 1. protein changing functional variants 2. pathogenic protein changing including variants of unknown significance (VUS)3. protein changing pathogenic variants. Results: Based on protein changing functional variants: NOTCH1 and TSC1 mutations is prevalent in 95% of the samples, followed by SMARCA4 in 92%, ABL1 and AKT1 both in 71%, CDK12 in 63%, ALK in 61%, EGFR in 50% of the patients. The top frequently mutated gene is NOTCH1 with an 8% of all the protein changing mutations, followed by SMARCA4, BRCA2, ALK, TSC1 each with 5% mutation frequency. On applying the filter of pathogenic protein changing variants including VUS: the top frequently mutated genes are NOTCH1, ATM, BRCA1 and NF1 each with 10% of all the mutations, followed by PIK3CA, BRCA1 each with 7%, PTCH1, RET with 6% and SMARCA4, MET with 5% mutation frequency. When we look at the percentage of patients with specific mutations, PIK3CA mutations are prevalent in 24% of the samples, followed by NOTCH1 in 18% and ATM, BRCA1, BRCA2, NF1, PTCH1 and SMARCA4 in 16% of the total patient population. Applying the most stringent criteria and including known pathogenic variants only: the top frequently mutated gene is PIK3CA with 25%, followed by BRCA2 and CDKN2A with 11% of all the protein changing pathogenic mutations, followed by SF3B1, TSC2 each with 8%, ATM, BRAF, BRCA1 with 6% and EGFR, FGFR3, IDH1, IDH2 and KRAS with 3% mutational frequency. One sample has the greatest number of pathogenic protein changing mutations on genes IDH1, BRAF, BRCA1, BRCA2, SF3B1 and TSC2. 7 out of 36 patients have co-mutations in more than one gene. 5 of 7 of these patients have PIK3CA mutations as one of the co-mutations. The three mutations on PIK3CA that are shared by two or more patients are p.E542K, p.E545K, p.H1047R. IDH1(p.R132C) and IDH2(p.R172S) mutations that have been previously described in case series exist in two different patients in our cohort. Using MSISensor2 software tool, 9 of 38 samples in our cohort have MSI score of 3.5% or higher. Highest MSI score is 9.45%. Conclusions: PIK3CA pathogenic mutation was seen in about one fourth of our patients. Genomic sequencing should be considered for all sinonasal cancers which can lead to better understanding and potentially guide treatment options.

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Abstract Details

Meeting

2023 ASCO Annual Meeting

Session Type

Publication Only

Session Title

Publication Only: Head and Neck Cancer

Track

Head and Neck Cancer

Sub Track

Biologic Correlates

Citation

J Clin Oncol 41, 2023 (suppl 16; abstr e18046)

DOI

10.1200/JCO.2023.41.16_suppl.e18046

Abstract #

e18046

Abstract Disclosures

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