MC1R variants as melanoma risk factors independent of at-risk phenotypic characteristics: a pooled analysis from the M-SKIP project

• Published in: Cancer management and research Vol. 10; pp. 1143 - 1154
• Main Authors: Tagliabue, Elena, Gandini, Sara, Bellocco, Rino, Maisonneuve, Patrick, Newton-Bishop, Julia, Polsky, David, Lazovich, DeAnn, Kanetsky, Peter A, Ghiorzo, Paola, Gruis, Nelleke A, Landi, Maria Teresa, Menin, Chiara, Fargnoli, Maria Concetta, García-Borrón, Jose Carlos, Han, Jiali, Little, Julian, Sera, Francesco, Raimondi, Sara
• Format: Journal Article
• Language: English
• Published: New Zealand Dove Medical Press Limited 01.01.2018; Taylor & Francis Ltd; Dove Medical Press
• Subjects: Analysis; cutaneous melanoma; Dermatology; Epidemiology; Family medical history; Genes; genetic epidemiology; Genomes; Health care; Mediation; Medicin och hälsovetenskap; Melanocortin-1 Receptor; Melanoma; Oncology; Original Research; pigmentation; Pooled-analysis; Population; Prevention; Prognosis; Public health; Risk factors; Skin; Skin cancer; Studies; Task forces; Australia; New York; Italy; United Kingdom > UK; United States > US; cutaneous melanoma; melanocortin 1 receptor; pigmentation; pooled analysis; genetic epidemiology
• ISSN: 1179-1322; 1179-1322
• DOI: 10.2147/cmar.s155283

Melanoma represents an important public health problem, due to its high case-fatality rate. Identification of individuals at high risk would be of major interest to improve early diagnosis and ultimately survival. The aim of this study was to evaluate whether variants predicted melanoma risk independently of at-risk phenotypic characteristics. Data were collected within an international collaboration - the M-SKIP project. The present pooled analysis included data on 3,830 single, primary, sporadic, cutaneous melanoma cases and 2,619 controls from seven previously published case-control studies. All the studies had information on gene variants by sequencing analysis and on hair color, skin phototype, and freckles, ie, the phenotypic characteristics used to define the red hair phenotype. The presence of any variant was associated with melanoma risk independently of phenotypic characteristics (OR 1.60; 95% CI 1.36-1.88). Inclusion of variants in a risk prediction model increased melanoma predictive accuracy (area under the receiver-operating characteristic curve) by 0.7% over a base clinical model ( =0.002), and 24% of participants were better assessed (net reclassification index 95% CI 20%-30%). Subgroup analysis suggested a possibly stronger role of in melanoma prediction for participants without the red hair phenotype (net reclassification index: 28%) compared to paler skinned participants (15%). The authors suggest that measuring the genotype might result in a benefit for melanoma prediction. The results could be a valid starting point to guide the development of scientific protocols assessing melanoma risk prediction tools incorporating the genotype.