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1.
  • Barrett, Jennifer H., et al. (författare)
  • Fine mapping of genetic susceptibility loci for melanoma reveals a mixture of single variant and multiple variant regions
  • 2015
  • Ingår i: International Journal of Cancer. - : John Wiley and Sons Inc.. - 0020-7136 .- 1097-0215. ; 136:6, s. 1351-1360
  • Tidskriftsartikel (refereegranskat)abstract
    • At least 17 genomic regions are established as harboring melanoma susceptibility variants, in most instances with genome-wide levels of significance and replication in independent samples. Based on genome-wide single nucleotide polymorphism (SNP) data augmented by imputation to the 1,000 Genomes reference panel, we have fine mapped these regions in over 5,000 individuals with melanoma (mainly from the GenoMEL consortium) and over 7,000 ethnically matched controls. A penalized regression approach was used to discover those SNP markers that most parsimoniously explain the observed association in each genomic region. For the majority of the regions, the signal is best explained by a single SNP, which sometimes, as in the tyrosinase region, is a known functional variant. However in five regions the explanation is more complex. At the CDKN2A locus, for example, there is strong evidence that not only multiple SNPs but also multiple genes are involved. Our results illustrate the variability in the biology underlying genome-wide susceptibility loci and make steps toward accounting for some of the missing heritability. What's new? In genome-wide association studies, researchers identify genetic variants that frequently associate with a particular disease, though the variants identified may not contribute to the molecular cause of the disease. This study took a closer look at 17 regions associated with melanoma, fine mapping the regions both in people with melanoma and in healthy controls. Though single SNPs account for the association in some regions, they found that in a few regions, several SNPs - and possibly multiple genes - contributed to the association signal. These findings illustrate the importance of not overlooking the interaction between multiple genetic markers when conducting such studies.
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2.
  • Law, Matthew H, et al. (författare)
  • Genome-wide meta-analysis identifies five new susceptibility loci for cutaneous malignant melanoma.
  • 2015
  • Ingår i: Nature Genetics. - : Nature Publishing Group. - 1546-1718. ; 47:9, s. 987-995
  • Tidskriftsartikel (refereegranskat)abstract
    • Thirteen common susceptibility loci have been reproducibly associated with cutaneous malignant melanoma (CMM). We report the results of an international 2-stage meta-analysis of CMM genome-wide association studies (GWAS). This meta-analysis combines 11 GWAS (5 previously unpublished) and a further three stage 2 data sets, totaling 15,990 CMM cases and 26,409 controls. Five loci not previously associated with CMM risk reached genome-wide significance (P < 5 × 10(-8)), as did 2 previously reported but unreplicated loci and all 13 established loci. Newly associated SNPs fall within putative melanocyte regulatory elements, and bioinformatic and expression quantitative trait locus (eQTL) data highlight candidate genes in the associated regions, including one involved in telomere biology.
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3.
  • Taylor, Nicholas J, et al. (författare)
  • Estimating CDKN2A mutation carrier probability among global familial melanoma cases using GenoMELPREDICT
  • 2019
  • Ingår i: Journal of the American Academy of Dermatology. - : Elsevier. - 0190-9622 .- 1097-6787. ; 81:2, s. 386-394
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Although rare in the general population, highly penetrant germline mutations in CDKN2A are responsible for 5-40% of melanoma cases reported in melanoma-prone families. We sought to determine whether MELPREDICT was generalizable to a global series of melanoma families and whether performance improvements can be achieved.METHODS: 2,116 familial melanoma cases were ascertained by the international GenoMEL Consortium. We recapitulated the MELPREDICT model within our data (GenoMELPREDICT) to assess performance improvements by adding phenotypic risk factors and history of pancreatic cancer. We report areas under the curve (AUC) with 95% confidence intervals (CI) along with net reclassification indices (NRI) as performance metrics.RESULTS: MELPREDICT performed well (AUC=0.752; 95%CI: 0.730, 0.775), and GenoMELPREDICT performance was similar (AUC=0.748; 95% CI: 0.726, 0.771). Adding a reported history of pancreatic cancer yielded discriminatory improvement (p<0.0001) in GenoMELPREDICT (AUC=0.772; 95%CI: 0.750, 0.793; NRI=0.40). Including phenotypic risk factors did not improve performance.CONCLUSION: The MELPREDICT model functioned well in a global dataset of familial melanoma cases. Adding pancreatic cancer history improved model prediction. GenoMELPREDICT is a simple tool for predicting CDKN2A mutational status among melanoma patients from melanoma-prone families and can aid in counselling these patients towards genetic testing or cancer risk counselling.
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