Research Article | Open Access
Hui-Han Hu, Mériem Benfodda, Nicolas Dumaz, Steven Gazal, Vincent Descamps, Agnès Bourillon, Nicole Basset-Seguin, Angélique Riffault, Khaled Ezzedine, Martine Bagot, Armand Bensussan, Philippe Saiag, Bernard Grandchamp, Nadem Soufir, "A Large French Case-Control Study Emphasizes the Role of Rare Mc1R Variants in Melanoma Risk", BioMed Research International, vol. 2014, Article ID 925716, 10 pages, 2014. https://doi.org/10.1155/2014/925716
A Large French Case-Control Study Emphasizes the Role of Rare Mc1R Variants in Melanoma Risk
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.
The incidence of cutaneous melanoma, the most lethal type of skin cancer, is increasing in western countries, doubling every ten years . Melanoma is a complex disease that arises through multiple etiological pathways . 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 .
Germline mutations in high-penetrance melanoma predisposing genes CDKN2A and CDK4 have been found in 20% of familial melanoma cases . 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 . 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 . A recent review has documented 57 nonsynonymous and 25 synonymous polymorphisms in different populations . RHC (red hair color) variants (also called “” alleles) lead to nonfunctional or diminished functional receptors , 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 “” alleles.
Numerous association studies have demonstrated the important role of MC1R variants in melanoma predisposition [8, 11, 28, 29]. The influence of MC1R 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 . 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  (Supplementary Table 2). Some variants lead to poor MC1R expression, due to endoplasmic reticulum (ER) retention or aberrant trafficking from ER to Golgi . 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 () variants, while variants without any damaging effect were regarded as nondamaging () variants. Variants that had a clear functional impact (i.e., nonsense or frameshift mutations) were classified as damaging () 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 and 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 variants were thereafter classified into two subgroups according to functional prediction (predicted to be damaging () or nondamaging ()), 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 and alleles on melanoma risk. 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 , , and variants on melanoma risk, their population attributable fractions (PAF) were calculated as follows: , where is the proportion of controls carrying the risk alleles .
Finally, in order to investigate the respective role of MC1R protein domains in melanoma, the number of and 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.
3.1. 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).
|Damaging 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.  and García-Borrón et al. .
RHC, red hair colour variant.
Frequent non-RHC variants are shown in bold.
Five alleles (D84E, R142H, R151C, R160W, and D294H) and 5 frequent alleles (V60L, V92M, I155T, R163Q, and T314T) were found in our cohorts. In addition, we found 69 rare 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 ( variants). Amongst the 69 rare alleles, 40 (58%) were predicted to be 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, alleles were strongly associated with melanoma (OR = 2.66 [2.20–3.23]; ) (Table 2). In addition, association of individual alleles with melanoma was significant (ORs = from 2.33 to 2.9) for all variants except for D84E (). We calculated an estimated PAF due to 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).
|Number 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, alleles were also associated, although less strongly, with melanoma (OR = 1.51 [1.32–1.73]; ) (Table 2). In addition, three frequent alleles (V60L, V92M, and I155T) were associated individually with melanoma, but the association for the R163Q variant did not reach significance (). Of note, the I155T variant associated almost as strongly as alleles with melanoma (OR = 2.61 [1.35–5.12]) and the other frequent alleles conferred risks equal to roughly half the risk of alleles (ORs = from 1.47 to 1.73). The PAF of variants was very similar to that of 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 variants were also strongly associated with melanoma (OR = 1.92 [1.20–3.07]; ) (Table 2). We divided rare alleles into and subgroups according to in silico functional predictions. Interestingly, variants were associated with melanoma susceptibility as strongly as alleles (OR = 2.38 [1.38–4.15]; ). Of note, the estimated PAF of variants was 1.6% and contributed almost completely to the PAF of rare variants (Table 2). On the contrary, variants had no impact on melanoma susceptibility (). Moreover, the average age at melanoma diagnosis of patients carrying variants was younger than that of patients without variants (45 and 54, resp.; ). Finally, variants, like 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 and alleles on melanoma risk (respective ORs = 2.22 [1.66–2.97] and 1.26 [1.04–1.52]).
|(a) R variants|
|(b) r variants|
|P value was calculated by logistic regression.|
R: red hair colour variant; r: nonred hair colour variant.
Statistically significant results are shown in bold.
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 (, , , and ) 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 , , , and variants in each protein domain indicated in Table 4 showed that 63% of variants were located in four domains (intracellular 2 and transmembrane 2, 5, and 7) whereas only 18% of variants were located in these domains (). Importantly, three of these four domains also contain at least one variant, suggesting an important role of these domains in MC1R function and pathogenicity.
|Number of alleles found in each protein domain.|
The crosses indicate localisation of RHC variants or frequent non-RHC variants.
MC1R variants are usually classified into two main categories, RHC () and non-RHC (), 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 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.
We also showed a clear association of frequent MC1R alleles, especially V60L, V92M, and I155T, with melanoma. In an early meta-analysis neither of them was found to be associated with melanoma , whereas, in a more recent and larger meta-analysis, both were associated with melanoma . 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 . These functional data argue for an association of theses variants with melanoma risk.
Even though the OR of alleles was much higher than that of alleles, their PAFs were very close (15.8% for and 16.6% for ) suggesting that the impact of 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 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 variants is only 7.4. This may be due at least, in part, to the high allelic frequency of variants observed in French melanoma patients (0.43) (versus 0.33 in Williams meta-analysis) . This further emphasises the role alleles in melanoma risk according to the ethnical background of the population studied. In addition, both and 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 . 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) . Interestingly, rare variants predicted to be damaging ( variants) were associated with melanoma as strongly as alleles (OR = 2.38 [1.38–4.15]) whereas variants not predicted to be damaging () had no effect on melanoma. In addition, PAF of variants (1.6%) was higher than two 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 variants were located in the same domains as the 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 variants in the German, Spanish, and Italian populations [29, 31] suggesting an important role of these domains in the receptor’s function.
In this large study we confirmed the role of MC1R alleles in melanoma susceptibility and clearly showed that MC1R alleles also significantly increase the risk of melanoma. In addition, we defined the role of rare MC1R variants and proposed a novel class of 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.
Conflict of Interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
The authors would like to thank the Société Française de Dermatologie for supporting their research. They also thank the dermatological departments of Ambroise Paré, Bichat, Cochin, Henri Mondor, and Saint Louis hospitals for participating in the MelanCohort project and the Etablissement Français du Sang for providing control blood samples. They thank the Centre de Recherche Biologique of Bichat Hospital for sample preparation. Importantly, they would like to thank the patients and control subjects who participated in this study.
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.
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