Rose Yang

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NCI, DCEG, GEB

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PLCO (Learn more about this study)

2014-0017

Mar 7, 2014

Identify high-risk susceptibility genes for melanoma using population-based samples to follow-up on rare variants in potential melanoma susceptibility genes identified from melanoma-prone families

Approximately 10% of cutaneous malignant melanoma (CMM) cases occur in a familial setting and the known high-risk melanoma genes account for melanoma susceptibility in less than 40% melanoma-prone families. To identify additional high-penetrance susceptibility genes for familial CMM, we performed whole-exome sequencing in 94 CMM cases or obligate carriers (assuming dominant inheritance) in 28 unrelated melanoma-prone families without known mutations recruited from the United States. After rigorous filtering steps to exclude common and non-segregating variants, a large number of potentially interesting variants remain, most of which have been technically validated. To determine which variants are more likely to be disease-related, we propose to evaluate the top variants/genes in population-based melanoma studies including PLCO. In this request, we seek permission to extract and genotype/sequence DNA from all incident CMM cases accrued in PLCO participants of European ancestry (N~1,113) and a similar number of melanoma-free controls matched to cases on age and sex. We plan to genotype the top 100 variants and sequence the entire coding region of the top 25 genes, selected based on co-segregation with disease within families, rarity in the population, predicted damaging effect based on in silico algorithms, and functional relevance. Recurrent variants enriched in CMM cases and genes demonstrating significantly increased genetic burden caused by rare variants will be considered as more important and will be further included in future functional studies. We plan to combine these data with results from other cohort studies including Nurses’ Health Study, Physicians’ Health Study, and Agricultural Health Study (N~1,200 CMM cases) to further increase the power for identifying disease-causing variants/genes. The evaluation of genetic variants in population-based studies will not only provide critical information in prioritizing candidate genes for future follow-up but will also enable estimation of allele frequencies of disease-causing variants in the general population once new genes have been identified.