Literature DB >> 24982914

A large French case-control study emphasizes the role of rare Mc1R variants in melanoma risk.

Hui-Han Hu1, Mériem Benfodda2, Nicolas Dumaz3, Steven Gazal4, Vincent Descamps5, Agnès Bourillon2, Nicole Basset-Seguin6, Angélique Riffault2, Khaled Ezzedine7, Martine Bagot6, Armand Bensussan6, Philippe Saiag8, Bernard Grandchamp2, Nadem Soufir1.   

Abstract

BACKGROUND: The MC1R gene implicated in melanogenesis and skin pigmentation is highly polymorphic. Several alleles are associated with red hair and fair skin phenotypes and contribute to melanoma risk.
OBJECTIVE: This work aims to assess the effect of different classes of MC1R variants, notably rare variants, on melanoma risk. Methods. MC1R coding region was sequenced in 1131 melanoma patients and 869 healthy controls. MC1R variants were classified as RHC (R) and non-RHC (r). Rare variants (frequency < 1%) were subdivided into two subgroups, predicted to be damaging (D) or not (nD).
RESULTS: Both R and r alleles were associated with melanoma (OR = 2.66 [2.20-3.23] and 1.51 [1.32-1.73]) and had similar population attributable risks (15.8% and 16.6%). We also identified 69 rare variants, of which 25 were novel. D variants were strongly associated with melanoma (OR = 2.38 [1.38-4.15]) and clustered in the same MC1R domains as R alleles (intracellular 2, transmembrane 2 and 7).
CONCLUSION: This work confirms the role of R and r alleles in melanoma risk in the French population and proposes a novel class of rare D variants as important melanoma risk factors. These findings may improve the definition of high-risk subjects that could be targeted for melanoma prevention and screening.

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Year:  2014        PMID: 24982914      PMCID: PMC4003837          DOI: 10.1155/2014/925716

Source DB:  PubMed          Journal:  Biomed Res Int            Impact factor:   3.411


1. Introduction

The incidence of cutaneous melanoma, the most lethal type of skin cancer, is increasing in western countries, doubling every ten years [1]. Melanoma is a complex disease that arises through multiple etiological pathways [2]. Ultraviolet radiation exposure is the main environmental cause, and pigmentation characteristics such as light skin, hair and eye colour, and high number of nevi have also been identified as melanoma risk factors [3]. Germline mutations in high-penetrance melanoma predisposing genes CDKN2A and CDK4 have been found in 20% of familial melanoma cases [4]. Recently, a third major gene, BAP1, that predisposes to melanoma (mainly ocular), mesothelioma, and possibly additional cancers has been identified [5-7]. In addition, numerous low penetrant susceptibility variants, which modulate melanoma risk, have also been described. These genes are mainly involved in melanogenesis (MC1R, ASIP, TYR, TYRP1, and SLC45A2) and melanocyte differentiation (MITF, KIT, and EDNRB) [8-12].Recently, variants in other pathways, such as DNA repair, genome maintenance integrity, and immunological pathways (TERT-CLPTM1, CASP8, ATM, and MX2), have also been linked to melanoma predisposition [13-17]. Among pigmentation genes, MC1R, which is the most studied, is associated with human skin pigmentation and melanoma susceptibility. MC1R, the receptor for α-melanocyte stimulating hormone (α-MSH), is a G protein coupled receptor with seven transmembrane domains that regulates the relative concentration of brown-black eumelanin and red-yellow pheomelanin [18]. Eumelanin has been shown to reduce the accumulation of DNA photodamage and to protect melanocytes from UV-induced apoptosis. Pheomelanin is, on the contrary phototoxic, generating oxidative stress by the production of reactive oxygen species [19-21]. MC1R is highly polymorphic within Caucasian populations [21]. A recent review has documented 57 nonsynonymous and 25 synonymous polymorphisms in different populations [22]. RHC (red hair color) variants (also called “R” alleles) lead to nonfunctional or diminished functional receptors [23], preferentially induce pheomelanin production, and are therefore associated with red hair, light skin, poor tanning ability, and heavy freckling [24-27]. Other MC1R variants that impact less strongly on MC1R function are called non-RHC variants and are labelled “r” alleles. Numerous association studies have demonstrated the important role of MC1R R variants in melanoma predisposition [8, 11, 28, 29]. The influence of MC1R r variants on melanoma risk has also been reported but there are several discrepancies in the different published works [4, 29–31]. In addition, to date there is no conclusion on the role of rare MC1R variants in melanoma. In this large French case-control study, we investigated the role of different classes of MC1R variants in melanoma risk, focussing particularly on the role of rare MC1R variants.

2. Patients and Methods

2.1. Studied Populations

A cohort of 1131 Caucasian melanoma patients was recruited between 2002 and 2008 from the dermatology departments of all university-affiliated hospitals in Paris (the MelanCohort). The main characteristics of the patients have been previously described [32]. Melanoma was sporadic in 784 patients (69%), including 81 patients (7%) who had multiple melanomas and 229 patients (20%) who had familial melanoma (at least 2 cases in first- or second-degree relatives, including the proband). Among the familial and multiple sporadic cases, 8.5% of patients carried mutations in the CDKN2A or CDK4 gene. The control group comprised 869 ethnically matched skin cancer-free blood donors recruited from the EFS (Etablissement Français du Sang) in Bichat and Saint-Louis hospitals over the same period. These subjects have previously been described and used as controls in case-control studies [32-34]. Data from patients and controls regarding sex, age, ethnic origin, date of birth, anatomoclinical data, pigmentation characteristics (hair, eye, and skin colours), skin type (Fitzpatrick classification I to IV), nevus count (<10, 10–50, 51–100, and >100), and heavy freckles (yes/no) were collected in a standard document. Ancestry was investigated through birth location of parents and grandparents, and only those with a Caucasian ancestry were retained for the study. The pigmentation characteristics of patients and controls are summarized in Supplementary Table 1 (see Supplementary Materials available online at http://dx.doi.org/10.1155/2014/925716). All subjects signed an informed consent form and provided a blood sample.

2.2. Sequencing and Mutational Analysis

The coding sequence of MC1R deposited in GenBank (NM_002386.3) was amplified with 2 couples of primer selected by UCSC Genome Browser Gateway (data available upon request) in 1131 melanoma patients and 869 controls. The PCR mix contained 20 ng of genomic DNA, 2.5 mM MgCl2, 50 μM of each dNTP, 400 nM of each primer, and 0.5 U Ampli TaqGold polymerase (Applied Biosystems, Courtaboeuf, France). A 62°C annealing temperature was used for PCR amplification. PCR products were verified on a 2% agarose gel and purified by EXOSAP-IT (USB Corporation, OH, USA). Sequencing reaction was performed on 8900 Fast Thermal Cycler (Applied Biosystems), using 10 ng of purified PCR products and the Big-Dye Terminator Cycle Kit (Applied Biosystems). Sequence analysis was performed with an ABI-Prism 3130 automated sequencer (Applied Biosystems) and read with SeqScape software v2.5 (Applied Biosystems).

2.3. Classification of MC1R Variants

The functional impact of numerous MC1R variants has been assessed in previous studies [47] (Supplementary Table 2). Some variants lead to poor MC1R expression, due to endoplasmic reticulum (ER) retention or aberrant trafficking from ER to Golgi [50]. Other variants result in a diminished functional receptor due to lower affinity for α-MSH, reduced coupling with cAMP, or decreased ability to stimulate cAMP production [47, 50–53]. In order to predict the impact on protein function of MC1R variants, we used in silico prediction tools, SIFT (http://sift.jcvi.org/), SNPs3D (http://www.snps3d.org/), and PolyPhen (http://genetics.bwh.harvard.edu/pph/). Rare variants, which were defined by an allele frequency <1% and predicted to be damaging by at least 1 of 3 prediction tools, were predicted to be damaging (D) variants, while variants without any damaging effect were regarded as nondamaging (nD) variants. Variants that had a clear functional impact (i.e., nonsense or frameshift mutations) were classified as damaging (D) variants.

2.4. Statistical Analysis

Statistical analysis was performed by using PASW software version 18. The level of significance for all tests corresponded to an alpha error rate of 5%. All odds ratios (OR) were calculated with 95% confidence intervals. To assess the association of R and r variants with melanoma, we used Fisher's exact test, the number of haplotypes without any variants alleles (wild-type and synonymous variants) being considered as reference. Rare r variants were thereafter classified into two subgroups according to functional prediction (predicted to be damaging (D) or nondamaging (nD)), and their effects on melanoma risk were also tested. A multivariate analysis adjusted for hair and eye colours, skin type, and nevus count was carried out to investigate the independent effect of R and r alleles on melanoma risk. P values and their corresponding OR were calculated with logistic regression. Due to the interdependency of all our tests and the magnitude of our results, no correction for multiple testing was performed. In order to quantify the impact of MC1R R, r, and D variants on melanoma risk, their population attributable fractions (PAF) were calculated as follows: PAF = (p × (OR − 1)/(p × (OR − 1) + 1), where p is the proportion of controls carrying the risk alleles [34]. Finally, in order to investigate the respective role of MC1R protein domains in melanoma, the number of D and nD variants in different domains was compared between patients and controls. Each protein domain was determined by ExPASy Bioinformatics Resource Portal (http://expasy.org/) using UniProtKB Q01726.2 as query.

3. Results

3.1. Characterization of MC1R Variants

By sequencing the entire MC1R coding sequence, we found 79 MC1R variants: 2 nonsense, 3 frameshift, 53 missense, and 21 silent variants (Table 1), 9% of which were localized in the extracellular portion of the receptor, 65% in the transmembrane domains, and 25% in the cytoplasmic domains (Figure 1).
Table 1

All variants found in the study.

Nucleotide change Amino acid changeNumber of chromosome Predicted to be damaging (D) varianta  Rare variantb  Novel variantc  Reference
Patients (chr = 2262)Controls (chr = 1738)
Nonsynonymous
 c.100C > Tp.R34W1NoYes Yes
 c.104G > Ap.C35Y1YesYesNo [35]
 c.112G > A p.V38M23NoYesNo [35]
 c.122C > G p.S41C2YesYes Yes
 c.133T > C (rs61996344)p.F45L2YesYesNo [36]
c.178G > T (rs1805005) p.V60L 359254YesNoNo [25]
 c.199C > Tp.R67W2YesYesNo [37]
 c.200G > A (rs34090186)p.R67Q11NoYesNo [38]
 c.205C > Gp.L69V1YesYes Yes
 c.241G > Cp.A81P1YesYesNo[24]
 c.247T > C (rs34474212)p.S83P51YesYesNo [39]
 c.252C > A (rs1805006)p.D84E2313RHCNoNo[27]
c.274G > A p.V92M 188113YesNoNo[27]
 c.284C > T (rs34158934)p.T95M62YesYesNo[27]
 c.296T > Cp.L99P1YesYes Yes
 c.310G > A (rs2229617)p.G104S1YesYesNo[24]
 c.350A > Tp.D117V1YesYes Yes
 c.359T > C (rs33932559)p.I120T1YesYesNo [35]
 c.364G > A p.V122M14NoYesNo [40]
 c.373T > Cp.C125R1YesYesNo [41]
 c.389C > Tp.S130F1YesYes Yes
 c.415G > Ap.A139T1YesYesNo[31]
 c.417G > Ap.V140M1NoYes Yes
 c.419T > G p.V140G1YesYes Yes
 c.424C > Tp.R142C1YesYesNo[42]
 c.425G > A (rs11547464)p.R142H2913RHCNoNo[25]
 c.451C > T (rs1805007)p.R151C21176RHCNoNo[25]
 c.456C > Ap.Y152X1YesYesNo [43]
c.464T > C (rs1110400) p.I155T 3514YesNoNo[25]
 c.467T > Cp.V156A1YesYesNo[31]
 c.478C > T (rs1805008)p.R160W15259RHCNoNo[25]
 c.479G > Ap.R160Q2YesYesNo [36]
c.488G > A (rs885479) p.R163Q 7557YesNoNo[25]
 c.512C > A p.A171D1YesYesNo [43]
 c.613G > Cp.V205L1YesYes Yes
 c.637C > T (rs144239448)p.R213W34YesYesNo [36]
 c.652G > Ap.A218T1YesYesNo[29]
 c.664G > Tp.A222S1NoYes Yes
 c.667C > Tp.R223W1YesYes Yes
 c.707G < Ap.G236D1YesYes Yes
 c.766C > Tp.P256S11YesYesNo [43]
 c.801C > Ap.C267X1YesYes Yes
 c.820G > Ap.G274S1NoYesNo [44]
 c.832A > Gp.K278E31YesYesNo[24]
 c.842A > G (rs141177570)p.N281S1YesYesNo [45]
 c.853G > Ap.A285T1NoYes Yes
 c.854C > Gp.A285G1YesYes Yes
 c.861C > Gp.I287M2YesYesNo [46]
 c.865T > Cp.C289R1YesYesNo[47]
 c.880G > C (rs1805009)p.D294H8535RHCNoNo[27]
 c.892T > Cp.Y298H1YesYesNo[42]
 c.895G > Ap.A299T1YesYesNo[25]
 c.917G > Ap.R306H1YesYesNo [45]
 c.928A > Cp.K310Q1NoYes Yes
 c.951G > Tp.W317C1YesYes Yes
Insertion/deletion
 c.86_87 insA4YesYesNo [46]
 c.481_482 insG1YesYes Yes
 c.524_525 insT1YesYes Yes
Synonymous
 c.366G > Ap.V122V1NoYesNo[29]
 c.414C > T p.I138I1NoYesNo [38]
 c.426C > A p.R142R2NoYes Yes
 c.471C > T p.T157T1NoYes Yes
 c.477G > Cp.P159P1NoYes Yes
 c.478C > A p.R160R1NoYesNo [48]
 c.483G > A p.A161A1NoYesNo[29]
 c.504C > T (rs34612847)p.I168I1NoYesNo [38]
 c.531G > A (rs145781072)p.T177T11NoYesNo
 c.537C > Tp.F179F1NoYes Yes
 c.621C > Tp.Y207Y1NoYesNo[31]
 c.690G > C p.P230P3NoYesNo[24]
 c.699G > A (rs146544450)p.Q233Q610NoYesNo [46]
 c.792C > T p.I264I4NoYesNo [49]
 c.828C > T p.I276I1NoYesNo[31]
 c.873C > Tp.A291A1NoYes Yes
 c.894C > T (rs143395134)p.Y298Y2NoYesNo
 c.900C > T (rs3212367)p.F300F14NoYesNo [38]
 c.927C < Gp.L309L1NoYes Yes
c.942A > G (rs2228478) p.T314T 249170NoNoNo[25]
 c.948C > T (rs151318945)p.S316S55NoYesNodbSNP

aDamaging variants were those predicted as deleterious or intolerated by SIFT, SNPs3D, and PolyPhen in silico prediction tools.

bRare variants were defined as allele frequency less than 1%.

cVariants were absent in dbSNP by using NM_002386.3 as contig transcript and works of Gerstenblith et al. [22] and García-Borrón et al. [23].

RHC, red hair colour variant.

Frequent non-RHC variants are shown in bold.

Figure 1

Structure of human melanocortin-1 receptor. Putative structure is drawn according to the two-dimensional model of Ringholm et al., 2004 [54]. The amino acid sequence corresponds to the wildtype consensus (UniProtKB Q01726.2). Each protein domain is framed by residues marked in blue. Residues with R, frequent r, and predicted-to-be-damaging (D) alleles are shown in red, pink, and yellow, respectively. Ec: extracellular domain; Ic: intracellular domain; TM: transmembrane domain; R: RHC alleles; r: frequent non-RHC alleles; D: predicted damaging variants.

Five R alleles (D84E, R142H, R151C, R160W, and D294H) and 5 frequent r alleles (V60L, V92M, I155T, R163Q, and T314T) were found in our cohorts. In addition, we found 69 rare r alleles, consisting of 44 missense, 2 nonsense, 3 frameshift, and 20 silent variants. Interestingly, 25 were novel MC1R variants, 15 of which (52%) were predicted to have a functional impact (D variants). Amongst the 69 rare r alleles, 40 (58%) were predicted to be D variants, including 35 missense, 2 nonsense, and 3 frameshift variants (Table 1).

3.2. Association of Different MC1R Variant Subgroups with Melanoma Risk

The association of different subgroups of MC1R variants with melanoma risk was assessed as described in Section 2. Collectively, R alleles were strongly associated with melanoma (OR = 2.66 [2.20–3.23]; P = 2.69E − 25) (Table 2). In addition, association of individual R alleles with melanoma was significant (ORs = from 2.33 to 2.9) for all R variants except for D84E (P = 0.092). We calculated an estimated PAF due to R variants of 15.8%. By decreasing order, the PAFs were, respectively, 7.4 (R151C), 5.7 (R160W), 2.9 (D294H), 1 (R142H), and 0.8 (D84E) (Table 2).
Table 2

Association of different variant subgroups with melanoma risk.

Patientsc (chr = 2262)Controlsc (chr = 1738)OR [95% CI] P valuePAF (%)
Reference sequencea 936976Ref.Ref.
All R variantsb 500/0.22196/0.11 2.66 [2.20–3.23] 2.69E − 25 15.8
Individual RHC variant
 D84E23/0.0113/0.0071.85 [0.89–3.87]0.0920.8
 R142H29/0.0113/0.007 2.33 [1.16–4.75] 0.012 1
 R151C211/0.0976/0.04 2.90 [2.18–3.86] 7.95E − 15 7.4
 R160W152/0.0759/0.03 2.69 [1.94–3.72] 1.60E − 10 5.7
 D294H85/0.0435/0.02 2.53 [1.66–3.87] 3.10E − 06 2.9
All r variants980/0.43678/0.39 1.51 [1.32–1.73] 1.40E − 09 16.6
Frequent r variants
 V60L359/0.16254/0.15 1.47 [1.22–1.78] 3.50E − 05 6.5
 V92M188/0.08113/0.07 1.73 [1.34–2.25] 1.30E − 05 4.5
 I155T35/0.0214/0.008 2.61 [1.35–5.12] 0.002 1.3
 R163Q75/0.0357/0.031.37 [0.95–1.98]0.0871.2
Rare r variants57/0.02531/0.017 1.92 [1.20–3.07] 0.004 1.6
D variants48/0.0221/0.01 2.38 [1.38–4.15] 0.001 1.6
nD variants9/0.00410/0.0060.94 [0.35–2.51]1

aNumber of alleles containing wild-type sequence or synonymous variants and used as reference.

bAll R variants including D84E, R142H, R151C, R160W, and D294H.

cNumber of alleles/MAF (minor allelic frequency).

R: red hair colour variant; r: nonred hair colour variant; D: predicted to be damaging; nD: predicted to be nondamaging; OR: odds ratio; CI: confidence interval; PAF: population attributable fraction.

Statistically significant results are shown in bold. Ref, used as reference.

Interestingly, r alleles were also associated, although less strongly, with melanoma (OR = 1.51 [1.32–1.73]; P = 1.40E − 09) (Table 2). In addition, three frequent r alleles (V60L, V92M, and I155T) were associated individually with melanoma, but the association for the R163Q variant did not reach significance (P = 0.087). Of note, the I155T variant associated almost as strongly as R alleles with melanoma (OR = 2.61 [1.35–5.12]) and the other frequent r alleles conferred risks equal to roughly half the risk of R alleles (ORs = from 1.47 to 1.73). The PAF of r variants was very similar to that of R variants (16.6%). By decreasing order, the PAFs were, respectively, 6.5 (V60L), 4.5 (V92M), 1.3 (I155T), and 1.2 (R163Q) (Table 2). Furthermore, rare r variants were also strongly associated with melanoma (OR = 1.92 [1.20–3.07]; P = 0.004) (Table 2). We divided rare r alleles into D and nD subgroups according to in silico functional predictions. Interestingly, D variants were associated with melanoma susceptibility as strongly as R alleles (OR = 2.38 [1.38–4.15]; P = 0.001). Of note, the estimated PAF of D variants was 1.6% and contributed almost completely to the PAF of rare r variants (Table 2). On the contrary, nD variants had no impact on melanoma susceptibility (P = 1). Moreover, the average age at melanoma diagnosis of patients carrying D variants was younger than that of patients without D variants (45 and 54, resp.; P = 0.04). Finally, D variants, like R variants, were also associated with familial melanoma (OR = 4.78). To investigate whether the effect of the two main MC1R variant categories on melanoma susceptibility was independent of pigmentation traits, we conducted a multivariate analysis including the main clinical melanoma risk factors using logistic regression (Tables 3(a) and 3(b)). This showed a persistent role of R and r alleles on melanoma risk (respective ORs = 2.22 [1.66–2.97] and 1.26 [1.04–1.52]).

3.3. Impact of the Different MC1R Protein Domains

In order to study the impact of MC1R protein domains on melanoma predisposition, the different classes of MC1R variants (R, r, D, and nD) were positioned on the different protein domains (Figure 1). Most MC1R variants were localized in six receptor domains: transmembrane 1, 2, 3, and 7, intracellular 2, and C terminal domains. Very few variants were located in the extracellular portion. Among these domains, variants located in the intracellular domain 2 and in the transmembrane domain 7 had the highest impact on melanoma risk (OR = 2.75 [2.22–3.40] and OR = 2.48 [1.67–3.69]). The repartition of R, r, D, and nD variants in each protein domain indicated in Table 4 showed that 63% of D variants were located in four domains (intracellular 2 and transmembrane 2, 5, and 7) whereas only 18% of nD variants were located in these domains (P < 0.0001). Importantly, three of these four domains also contain at least one R variant, suggesting an important role of these domains in MC1R function and pathogenicity.
Table 4

Localisation of MC1R variants according to their classification and to their demonstrated or predicted functional impact.

Protein region RHC variant (R) Non-RHC variant (r)
Frequent non-RHC (r) Rare r
Predicted to be damaging (D)a Predicted to be nondamaging (nD)a
N-terminusM1-E3711
Transmembrane 1V38-I63x45
Intracellular 1A64-P7232
Transmembrane 2 M73-L100xx162
Extracellular 1L101-Q11501
Transmembrane 3L116-Y143x76
Intracellular 2 I144-R162xx40
Transmembrane 4R163-Y183x10
Extracellular 2D184-L19200
Transmembrane 5 V193-A21890
Intracellular 3Q219-G23621
Transmembrane 6L237-V26520
Extracellular 3L266-I27611
Transmembrane 7 F277-A299x112
C-terminusF300-W31721

aNumber of alleles found in each protein domain.

The crosses indicate localisation of RHC variants or frequent non-RHC variants.

4. Discussion

MC1R variants are usually classified into two main categories, RHC (R) and non-RHC (r), according to their association or not with the red hair colour phenotype [21, 24, 27, 55]. For the past ten years several association studies have demonstrated the importance of R alleles on melanoma predisposition [28, 29, 42, 56, 57]. However, the influence of rare MC1R variants on melanoma predisposition has been poorly investigated which prompted us to study in detail the role of these variants in the French population. In this study, we confirmed the association of most R alleles and melanoma risk with strengths that were close to those observed in previous studies [28, 29, 42, 56, 57]. We also showed a clear association of frequent MC1R r alleles, especially V60L, V92M, and I155T, with melanoma. In an early meta-analysis neither of them was found to be associated with melanoma [55], whereas, in a more recent and larger meta-analysis, both were associated with melanoma [57]. V60L is a loss of function variant with reduced coupling to the cAMP signalling [50, 53] and V92M has a lower affinity for α-MSH than wild-type MC1R and a decreased ability to stimulate the production of cAMP [23]. These functional data argue for an association of theses variants with melanoma risk. Even though the OR of R alleles was much higher than that of r alleles, their PAFs were very close (15.8% for R and 16.6% for r) suggesting that the impact of r alleles on melanoma seems to be important in the French population. Notably, in our work, the individual PAFs of V60L and V92M (6.5% and 4.5%) were very close to that of R alleles R151C and R160W (7.4% and 5.7%). Our results are different from that published by Williams et al., in which the PAF of r variants is only 7.4. This may be due at least, in part, to the high allelic frequency of r variants observed in French melanoma patients (0.43) (versus 0.33 in Williams meta-analysis) [57]. This further emphasises the role r alleles in melanoma risk according to the ethnical background of the population studied. In addition, both R and r alleles remained associated with melanoma risk in multivariate analyses, suggesting that they exert a role in melanoma risk independently of their effect on pigmentation, as previously suggested. In this work we identified 25 variants that have not been reported before [22, 23, 31, 47], further underscoring the highly polymorphic character of MC1R. According to Gerstenblith's work, the proportion of rare MC1R variants varies across populations and within Caucasian populations [23]. In our study, the proportion of rare variants (87%) was close to that described in Scherer's work (74% in Germany and 78% in Spain) [31]. Interestingly, rare variants predicted to be damaging (D variants) were associated with melanoma as strongly as R alleles (OR = 2.38 [1.38–4.15]) whereas variants not predicted to be damaging (nD) had no effect on melanoma. In addition, PAF of D variants (1.6%) was higher than two R variants (R142H and D84E), which seems to indicate that the contribution of this subgroup in melanoma predisposition should be taken into consideration, at least in the French population. Yet, there is a limitation in our work: the absence of functional studies concerning the potential effects of these novel MC1R variants, notably on α-MSH binding, receptor cellular localisation, and cAMP signalling. Finally, the majority of D variants were located in the same domains as the R alleles (intracellular 2 and transmembrane 2, 5, and 7, Table 4 and Figure 1). It had been shown before that there was a similar localization of D variants in the German, Spanish, and Italian populations [29, 31] suggesting an important role of these domains in the receptor's function.

5. Conclusion

In this large study we confirmed the role of MC1R R alleles in melanoma susceptibility and clearly showed that MC1R r alleles also significantly increase the risk of melanoma. In addition, we defined the role of rare MC1R variants and proposed a novel class of D variants that are strong melanoma risk factors. These findings might help in the definition of high-risk melanoma subgroups that could be targeted for melanoma prevention. Supplementary Table 1: Pigmentation characteristics, which include hair, eye, and skin color, skin type, nevus count, and heavy freckles, were collected from patients and controls studied in this work. Supplementary table 2: Functional impact of all MC1R variants, which have been investigated to date, was collected from many different studies and summarized in this table. Click here for additional data file.

(a) R variants

OR [95% CI] P valuea
Hair colour0.88 [0.69–1.12]0.292
Eye colour 2.30 [1.63–3.26] 2.64E − 06
Skin type 1.64 [1.17–2.3] 0.004
Nevus count1.39 [0.97–1.98]0.07
R variants 2.22 [1.66–2.97] 6.00E − 08

(b) r variants

OR [95% CI] P valuea
Hair colour0.98 [0.74–1.29]0.88
Eye colour 1.93 [1.45–2.57] 1.20E − 06
Skin type 1.96 [1.49–2.57] 7.33E − 06
Nevus count 1.6 [1.18–2.15] 0.002
r variants 1.26 [1.04–1.52] 0.018

a P value was calculated by logistic regression.

R: red hair colour variant; r: nonred hair colour variant.

Statistically significant results are shown in bold.

  57 in total

1.  MC1R, SLC45A2 and TYR genetic variants involved in melanoma susceptibility in southern European populations: results from a meta-analysis.

Authors:  Maider Ibarrola-Villava; Hui-Han Hu; Mickaël Guedj; Lara P Fernandez; Vincent Descamps; Nicole Basset-Seguin; Martine Bagot; Armand Benssussan; Philippe Saiag; Maria Concetta Fargnoli; Ketty Peris; Jose A Aviles; Ana Lluch; Gloria Ribas; Nadem Soufir
Journal:  Eur J Cancer       Date:  2012-03-28       Impact factor: 9.162

Review 2.  High- and low-penetrance cutaneous melanoma susceptibility genes.

Authors:  Maria Concetta Fargnoli; Giuseppe Argenziano; Iris Zalaudek; Ketty Peris
Journal:  Expert Rev Anticancer Ther       Date:  2006-05       Impact factor: 4.512

3.  Comprehensive evaluation of allele frequency differences of MC1R variants across populations.

Authors:  Meg R Gerstenblith; Alisa M Goldstein; Maria Concetta Fargnoli; Ketty Peris; Maria Teresa Landi
Journal:  Hum Mutat       Date:  2007-05       Impact factor: 4.878

4.  MC1R and PTCH gene polymorphism in French patients with basal cell carcinomas.

Authors:  Muriel Liboutet; Marc Portela; Gisèle Delestaing; Catherine Vilmer; Nicolas Dupin; Isabelle Gorin; Philippe Saiag; Céleste Lebbé; Delphine Kerob; Louis Dubertret; Bernard Grandchamp; Nicole Basset-Seguin; Nadem Soufir
Journal:  J Invest Dermatol       Date:  2006-04-27       Impact factor: 8.551

5.  Association between endothelin receptor B nonsynonymous variants and melanoma risk.

Authors:  Nadem Soufir; Roubila Meziani; Jean-Jacques Lacapère; Guylene Bertrand; Frederic Fumeron; Agnes Bourillon; Bénédicte Gérard; Vincent Descamps; Béatrice Crickx; Laurence Ollivaud; Alain Archimbaud; Céleste Lebbe; Nicole Basset-Seguin; Philippe Saiag; Bernard Grandchamp
Journal:  J Natl Cancer Inst       Date:  2005-09-07       Impact factor: 13.506

Review 6.  Melanocortin-1 receptor structure and functional regulation.

Authors:  José C García-Borrón; Berta L Sánchez-Laorden; Celia Jiménez-Cervantes
Journal:  Pigment Cell Res       Date:  2005-12

7.  Population-based study of natural variation in the melanocortin-1 receptor gene and melanoma.

Authors:  Peter A Kanetsky; Timothy R Rebbeck; Amanda J Hummer; Saarene Panossian; Bruce K Armstrong; Anne Kricker; Loraine D Marrett; Robert C Millikan; Stephen B Gruber; Hoda Anton Culver; Roberto Zanetti; Richard P Gallagher; Terence Dwyer; Klaus Busam; Lynn From; Urvi Mujumdar; Homer Wilcox; Colin B Begg; Marianne Berwick
Journal:  Cancer Res       Date:  2006-09-15       Impact factor: 12.701

8.  Determination of phenotype associated SNPs in the MC1R gene.

Authors:  Wojciech Branicki; Urszula Brudnik; Tomasz Kupiec; Paulina Wolañska-Nowak; Anna Wojas-Pelc
Journal:  J Forensic Sci       Date:  2007-03       Impact factor: 1.832

9.  MC1R variants associated susceptibility to basal cell carcinoma of skin: interaction with host factors and XRCC3 polymorphism.

Authors:  Dominique Scherer; Justo Lorenzo Bermejo; Peter Rudnai; Eugene Gurzau; Kvetoslava Koppova; Kari Hemminki; Rajiv Kumar
Journal:  Int J Cancer       Date:  2008-04-15       Impact factor: 7.396

10.  Identification of novel functional variants of the melanocortin 1 receptor gene originated from Asians.

Authors:  Kazuhiro Nakayama; Augustinus Soemantri; Feng Jin; Bumbein Dashnyam; Ryutaro Ohtsuka; Phaibool Duanchang; Mohd Nizam Isa; Wannapa Settheetham-Ishida; Shinji Harihara; Takafumi Ishida
Journal:  Hum Genet       Date:  2006-02-04       Impact factor: 4.132

View more
  3 in total

1.  A new POT1 germline mutation-expanding the spectrum of POT1-associated cancers.

Authors:  Tremika Le-Shan Wilson; Namita Hattangady; Antonio Marcondes Lerario; Carmen Williams; Erika Koeppe; Shane Quinonez; Jenae Osborne; Kelly B Cha; Tobias Else
Journal:  Fam Cancer       Date:  2017-10       Impact factor: 2.375

2.  Molecular characterization of melanoma cases in Denmark suspected of genetic predisposition.

Authors:  Karin A W Wadt; Lauren G Aoude; Lotte Krogh; Lone Sunde; Anders Bojesen; Karen Grønskov; Nine Wartacz; Jakob Ek; Morten Tolstrup-Andersen; Mette Klarskov-Andersen; Åke Borg; Steffen Heegaard; Jens F Kiilgaard; Thomas V O Hansen; Kerenaftali Klein; Göran Jönsson; Krzysztof T Drzewiecki; Morten Dunø; Nicholas K Hayward; Anne-Marie Gerdes
Journal:  PLoS One       Date:  2015-03-24       Impact factor: 3.240

3.  Family-based whole-exome sequencing identifies rare variants potentially related to cutaneous melanoma predisposition in Brazilian melanoma-prone families.

Authors:  Felipe Fidalgo; Giovana Tardin Torrezan; Bianca Costa Soares de Sá; Bruna Durães de Figueiredo Barros; Luciana Facure Moredo; Renan Valieris; Sandro J de Souza; João Pereira Duprat; Ana Cristina Victorino Krepischi; Dirce Maria Carraro
Journal:  PLoS One       Date:  2022-01-27       Impact factor: 3.240

  3 in total

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