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

M-SKIP Study Group

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Purpose: 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 MC1R variants predicted melanoma risk independently of at-risk phenotypic characteristics. Materials and methods: 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 MC1R gene variants by sequencing analysis and on hair color, skin phototype, and freckles, ie, the phenotypic characteristics used to define the red hair phenotype. Results: The presence of any MC1R variant was associated with melanoma risk independently of phenotypic characteristics (OR 1.60; 95% CI 1.36–1.88). Inclusion of MC1R 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 (P=0.002), and 24% of participants were better assessed (net reclassification index 95% CI 20%–30%). Subgroup analysis suggested a possibly stronger role of MC1R in melanoma prediction for participants without the red hair phenotype (net reclassification index: 28%) compared to paler skinned participants (15%). Conclusion: The authors suggest that measuring the MC1R 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 MC1R genotype.

Original languageEnglish (US)
Pages (from-to)1143-1154
Number of pages12
JournalCancer Management and Research
Volume10
DOIs
StatePublished - May 14 2018

Fingerprint

Melanoma
Hair
Genotype
Hair Color
Phenotype
Melanosis
Skin
ROC Curve
Early Diagnosis
Public Health
Mortality
Genes

Keywords

  • Cutaneous melanoma
  • Genetic epidemiology
  • Melanocortin 1 receptor
  • Pigmentation
  • Pooled analysis

ASJC Scopus subject areas

  • Oncology

Cite this

MC1R variants as melanoma risk factors independent of at-risk phenotypic characteristics : A pooled analysis from the M-SKIP project. / M-SKIP Study Group.

In: Cancer Management and Research, Vol. 10, 14.05.2018, p. 1143-1154.

Research output: Contribution to journalArticle

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title = "MC1R variants as melanoma risk factors independent of at-risk phenotypic characteristics: A pooled analysis from the M-SKIP project",
abstract = "Purpose: 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 MC1R variants predicted melanoma risk independently of at-risk phenotypic characteristics. Materials and methods: 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 MC1R gene variants by sequencing analysis and on hair color, skin phototype, and freckles, ie, the phenotypic characteristics used to define the red hair phenotype. Results: The presence of any MC1R variant was associated with melanoma risk independently of phenotypic characteristics (OR 1.60; 95{\%} CI 1.36–1.88). Inclusion of MC1R 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 (P=0.002), and 24{\%} of participants were better assessed (net reclassification index 95{\%} CI 20{\%}–30{\%}). Subgroup analysis suggested a possibly stronger role of MC1R in melanoma prediction for participants without the red hair phenotype (net reclassification index: 28{\%}) compared to paler skinned participants (15{\%}). Conclusion: The authors suggest that measuring the MC1R 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 MC1R genotype.",
keywords = "Cutaneous melanoma, Genetic epidemiology, Melanocortin 1 receptor, Pigmentation, Pooled analysis",
author = "{M-SKIP Study Group} and Elena Tagliabue and Sara Gandini and Rino Bellocco and Patrick Maisonneuve and Julia Newton-Bishop and David Polsky and Deann Lazovich and Kanetsky, {Peter A.} and Paola Ghiorzo and Gruis, {Nelleke A.} and Landi, {Maria Teresa} and Chiara Menin and Fargnoli, {Maria Concetta} and Garc{\'i}a-Borr{\'o}n, {Jose Carlos} and Jiali Han and Julian Little and Francesco Sera and Sara Raimondi",
year = "2018",
month = "5",
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doi = "10.2147/CMAR.S155283",
language = "English (US)",
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pages = "1143--1154",
journal = "Cancer Management and Research",
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T1 - MC1R variants as melanoma risk factors independent of at-risk phenotypic characteristics

T2 - A pooled analysis from the M-SKIP project

AU - M-SKIP Study Group

AU - Tagliabue, Elena

AU - Gandini, Sara

AU - Bellocco, Rino

AU - Maisonneuve, Patrick

AU - Newton-Bishop, Julia

AU - Polsky, David

AU - Lazovich, Deann

AU - Kanetsky, Peter A.

AU - Ghiorzo, Paola

AU - Gruis, Nelleke A.

AU - Landi, Maria Teresa

AU - Menin, Chiara

AU - Fargnoli, Maria Concetta

AU - García-Borrón, Jose Carlos

AU - Han, Jiali

AU - Little, Julian

AU - Sera, Francesco

AU - Raimondi, Sara

PY - 2018/5/14

Y1 - 2018/5/14

N2 - Purpose: 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 MC1R variants predicted melanoma risk independently of at-risk phenotypic characteristics. Materials and methods: 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 MC1R gene variants by sequencing analysis and on hair color, skin phototype, and freckles, ie, the phenotypic characteristics used to define the red hair phenotype. Results: The presence of any MC1R variant was associated with melanoma risk independently of phenotypic characteristics (OR 1.60; 95% CI 1.36–1.88). Inclusion of MC1R 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 (P=0.002), and 24% of participants were better assessed (net reclassification index 95% CI 20%–30%). Subgroup analysis suggested a possibly stronger role of MC1R in melanoma prediction for participants without the red hair phenotype (net reclassification index: 28%) compared to paler skinned participants (15%). Conclusion: The authors suggest that measuring the MC1R 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 MC1R genotype.

AB - Purpose: 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 MC1R variants predicted melanoma risk independently of at-risk phenotypic characteristics. Materials and methods: 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 MC1R gene variants by sequencing analysis and on hair color, skin phototype, and freckles, ie, the phenotypic characteristics used to define the red hair phenotype. Results: The presence of any MC1R variant was associated with melanoma risk independently of phenotypic characteristics (OR 1.60; 95% CI 1.36–1.88). Inclusion of MC1R 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 (P=0.002), and 24% of participants were better assessed (net reclassification index 95% CI 20%–30%). Subgroup analysis suggested a possibly stronger role of MC1R in melanoma prediction for participants without the red hair phenotype (net reclassification index: 28%) compared to paler skinned participants (15%). Conclusion: The authors suggest that measuring the MC1R 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 MC1R genotype.

KW - Cutaneous melanoma

KW - Genetic epidemiology

KW - Melanocortin 1 receptor

KW - Pigmentation

KW - Pooled analysis

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