The genetic risk architecture of mucosal melanoma.
Authors: Amouzegar Afsaneh , Wu Xiaogang , Long James Patrick , Wong Justin W , Prabhakaran Sabitha , Little Latasha , Gumbs Curtis , Malke Jared , Simon Julie , Zhang Jianhua , Wargo Jennifer Ann , Nagarajan Priyadharsini , Scheet Paul A. , McQuade Jennifer Leigh , Futreal Andrew 
Published: June 2024

10595

Background: Mucosal melanoma (MM) is a rare and aggressive subtype of melanoma. Outcomes for MM are significantly worse than for cutaneous melanoma (CM). While somatic mutations induced by UV radiation are known to cause CM, less is known about environmental and genetic alterations associated with MM. High penetrance alleles have been identified in familial cases of CM but the contribution of germline mutations to development of MM is not understood. Further, whilst population-based risk has been elaborated in CM, little is known for MM. The aim of this study is to characterize the germline genetic architecture of MM from high penetrance alleles to patient population genetics. Methods: A large retrospective cohort of MM patients (n=247) seen at MD Anderson Cancer Center were identified. Demographics, primary tumor sites, and presence of somatic mutations in BRAF, NRAS and KIT were extracted. Germline sequencing was performed on PBMC derived genomic DNA from the cohort using a gene panel of 322 major cancer genes. Frequency of identified germline alleles were compared to expected population control rate based on TOPMED using Fisher’s exact test. For genome wide association analysis (GWAS), genotyping will be performed on the MM cohort and the control group using the Infinium Global Screening Array. Cancer-free controls matched 3:1 based on MM cohort demographics have been assembled from existing case-control studies at MD Anderson. Following standard quality control procedures, we will impute variants from TOPMed using the Michigan Imputation Server. SNPtest v2.5.268 software will be utilized to perform association tests, using a multivariate logistic regression model incorporating gender and principal components. In addition to variants that may surpass a genome-wide significance score, we will inspect results for an enrichment of cancer genes. Results: Median age of MM cohort is 63, female predominant (60%), primarily White (84.6%), with gastrointestinal (36%), genitourinary (34%) and head & neck (30%) being the most common MM subtypes. Characteristics of the cohort were representative of the US MM population. Somatic mutations in KIT (26%) were most common. Germline mutations were found in 10.9% of the cohort, with most common detected variations in MITF (c.G952A:p.E318K) (2.4%) at OR of 13.9 (95%CI 5.0, 30.9), and CHEK2 (c.1100delC:p.T367fs) (1.6%) at OR of 16.4 (4.4, 42.9) compared to population control rate. Conclusions: Our study is the first to demonstrate the distribution of germline mutations in the largest cohort of MM patients. The MITF E318K allele is a known risk factor for CM, while CHEK2 1100delC allele has mixed evidence for conferring CM risk. GWAS data are currently being analyzed and these updated results will be presented in the context of the comprehensive analyses of germline risk alleles in MM patients.