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Version modif Fab_Oct 2007_corrVC_FD_BB_FL_16Janv2008

Protective effect of Glutathione S-Transferase T1 gene on melanoma risk in presence of

CDKN2A mutations,MC1R variants and host-related phenotypes.

V. CHAUDRU (1), MT. LO (1), F. LESUEUR (2,3), K. LAUD (4), H. MOHAMDI (1), C.

MARIAN (5), M. BARROIS (2), A. CHOMPRET (2), MF. AVRIL (6), F. DEMENAIS (1), B.

BRESSAC-DE PAILLERETS (2)

(1) INSERM U794, Universit dEvry, Evry, (2) Service de Gntique and FRE2939 CNRS,

Institut Gustave Roussy, Villejuif, (3) Genetic Susceptibility Group, IARC, Lyon, (4) Unit

830 INSERM, Institut Curie, (5) Biochemistry Department, University of Medecine and

Pharmacy, Romania, (6) AP-HP Hpital Cochin, Universit Ren Descartes Paris 5, Paris

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ABSTRACT

UV exposure is the major environmental risk factor of cutaneous melanoma mainly by

generating reactive oxygen species (ROS) causing molecular damages. Glutathione S-

transferases (GSTs) are enzymes playing an important role in detoxifying products of

oxidative stress, but only few case-control studies have investigated the effect of allelic

variants ofGSTgenes on melanoma risk and have led to controversial results. The effect of

these GST genes in melanoma-prone families segregating CDKN2A mutations has not yet

been studied. We examined the effect ofGSTP1, GSTM1 and GSTT1 genotypes on melanoma

risk in 25 melanoma-prone families with CDKN2A mutations, in presence of other risk factors

including MC1R gene variants, sun exposure, pigmentation characteristics and nevus

phenotypes. Logistic regression analyses were applied to 195 subjects genotyped for all three

genes investigated, using a generalized estimating equations (GEE) approach to take into

account correlations among family members. Different models were considered, which

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melanocytes. Ou The observed protective role ofGSTT1 deficiency on the development of

melanoma would need to be interpreted in the context of the other genes, CDKN2A, MC1R

and potentially those underlying dysplastic nevi, that influence melanoma risk and are

involved in multiple interacting pathways.

Key words: Glutathione S-Transferase, CDKN2A mutations, MC1R variants, Melanoma

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INTRODUCTION

Cutaneous malignant melanoma (CMM) is a complex disease resulting from genetic and

other risk factors. Epidemiological studies have shown that exposure to sunlight is the major

environmental risk factor associated with melanoma, while high numbers of melanocytic nevi

(clinically banal and/or atypical (dysplastic)), hair color, eye color, skin color, extent of

freckling and skin reactions to sun exposure are the major host factors [Tucker and Goldstein,

2003 for a review].

Approximately 10% of malignant melanomas are observed in a familial setting. Up-to now,

CDKN2A gene (9p21; MIM# 600160) is the major high-risk melanoma susceptibility gene.

Germline CDKN2A mutations have been observed in approximately 20 - 40 percent of

melanoma-prone families from around the world [Goldstein et al., 2007a]. Although

CDKN2A mutations confer a substantial risk for melanoma, there is a proportion of mutation

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risk factors by case-control studies [Kennedy et al., 2001; Matichard et al., 2004; Palmer et

al., 2000]. Joint analysis of host-related factors, sun exposure and MC1R in French families

with CDKN2A mutations have shown that CDKN2A penetrance is influenced significantly by

independent effects ofMC1R variants and dysplastic nevi [Chaudru et al., 2005].

Besides MC1R, other low-risk genes have been reported to be associated with melanoma

by a few case-control studies, but the results are most often controversial [Fargnoli et al.,

2006; Hayward, 2003]. These genes include the glutathione S-transferase genes (GSTP1

MIM# 134660, GSTM1 MIM# 138350, GSTT1 MIM# 600436) whose products detoxify

electrophilic xenobiotics and inactive endogenous metabolites generated during oxidative

stress, such as the reactive oxygen species (ROS) occurring after excessive ultraviolet (UV)

exposure [Hayes et al., 2005]. Human GSTgenes have been shown to be polymorphic. These

polymorphisms are either single nucleotide polymorphisms (SNPs) in the coding regions

(GSTP1), or gene deletions (GSTT1 and GSTM1). SNPs in exon 5 (p.I105V) and exon 6

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MATERIALS AND METHODS

Ascertainment of families and data collection

The 25 melanoma-prone families available for the present study have been recruited from

the Department of Dermatology at the Institut Gustave Roussy (IGR) and other French

hospitals forming the French Familial Melanoma Study Group. This sample includes five

additional families to our previous sample used to assess the effects of host factors and MC1R

on CDKN2A penetrance [Chaudru et al, 2005] and will be briefly described.

Eligible melanoma probands, from whom families were ascertained, were white

subjects living in France for more than ten years who had a newly diagnosed and

histologically confirmed melanoma. Family data were collected by interviewing the probands

on their first-degree, second-degree and third-degree relatives and included demographic

characteristics (gender, date of birth, and if deceased, age at death and cause of death) and the

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no), long stay (>1 year) in a sunny country, skin reactions to sunlight evaluated by the ability

to tan (low, medium, or high) and propensity to sunburn (low, medium or high). Information

on risk factors was obtained in all probands and at least 70% of all living relatives.

Written informed consent was obtained prior to participation under an Institutional

Review Board-approved protocol.

Genotyping

Genomic DNA from participants was extracted from peripheral blood lymphocytes, using the

QIAamp DNA Blood mini kit (QIAGEN, Hilden, Germany). A total of 18 different CDKN2A

mutations and 12 non-synonymous MC1R variants were detected in our 25 families (see

[Chaudru et al, 2004; 2005] for a list of CDKN2A mutations and MC1R variants).The gene

copy number variation for GSTT1 and GSTM1 were determined using an adapted protocol

from the Quantitative Multiplex PCR of Short fluorescent Fragments (QMPSF) method

[Casilli et al., 2002]. In brief, short exonic fragments ofGSTT1 (exon 5) and GSTM1 (exons 4

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Statistical analyses

Comparisons of GSTP1, GSTM1, and GSTT1 genotypes frequencies in affected and

unaffected members of the melanoma-prone families were first carried out by Fisher exact

test. Crude odds-ratios were computed to estimate the effects of these genotypes on melanoma

risk.

We then used logistic regression to assess the effects of each GSTgene on melanoma risk

by examining the following models: (1) GST in presence of CDKN2A mutation status; (2)

GSTin presence ofCDKN2A and number ofMC1R variants (or presence of RHC (Red Hair

Color) variants or NRHC (non-RHC) variants); (3) GST in presence of CDKN2A and by

entering MC1R, sun exposure, pigmentation and nevus phenotypes in the model using a

stepwise procedure. Age and sex were included in all regression models. We used a

generalized estimating equation (GEE) approach to take into account correlations among

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while the at-risk category included heterozygous mutation carriers (there was no homozygous

carriers in our sample). Since the risk of melanoma was found to increase with the number of

MC1R variants across populations [Goldstein et al., 2007b; Demenais, personal

communication], a MC1R variable was created by assigning subjects to one of the three

following categories: MC1R consensus homozygous subjects versus subjects with 1 MC1R

variant versus subjects with at least two MC1R variants. A RHC variable (pooling p.R151C,

p.R160W, p.D84E and p.D294H variants which are associated with red-hair color) and a

NRHC variable (pooling all non-RHC variants) were also considered: the baseline category

included MC1R consensus homozygous subjects while the at-risk category included subjects

with either at least one RHC variant (and no NRHC variant) or at least one NRHC variant

(and no RHC variant). Environmental and host-related covariates were dichotomized with the

baseline and at-risk categories being defined as follows: sun exposure (low or medium versus

high), hair color (dark or dark brown versus light brown, blond or red), skin color (dark

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subjects had melanoma while all other ones were unaffected. The mean age at diagnosis of

melanomapatients (38.56 11.70 years) and mean age at examination of unaffected subjects

(40.93 20.58 years) did not differ significantly (p=0.65). The risk of melanoma was

significantly higher in females than in males (p= 0.03; OR adjusted forCDKN2A = 2.17; 95%

CI, 1.09-4.31). Sex was thus included in all analyses.

The GSTP1, GSTM1, and GSTT1 genotypes as well as MC1R genotypes were determined

in all 195 individuals genotyped forCDKN2A. All GSTand MC1R variants were in Hardy-

Weinberg equilibrium (p> 0.05). Regarding MC1R, 85 subjects (43.6 %) carried one MC1R

variant and 69 had at last two variants (35.4 %), these proportions being 28.6% and 49.6% in

affected subjects and 58.9% and 25.9% in unaffecteds (p

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null allele nor by GSTP1 p.I105V or p.A114V variant (table 2). However, carrying at least

one GSTT1 null allele decreased melanoma risk significantly. This protective effect was

higher when MC1R was added to a model including CDKN2A as compared to a model with

CDKN2A alone: OR = 0.24 (95% CI, 0.15-0.58; p=0.001) with CDKN2A and MC1R vs OR =

0.41 (95% CI, 0.18-0.94; p=0.035) with CDKN2A alone. This decrease in melanoma risk

associated with GSTT1 null allele was similar in presence of RHC or NRHC variants,

although being more significant with NRHC variants (p = 0.008 with NRHC variants vs

p=0.046 with RHC variants). To investigate further the higher decrease in melanoma risk

when MC1R was incorporated in the regression model, we tested for interaction between

MC1R and GSTT1 variables but no significant interaction was evidenced. However, when

estimating odds-ratios by stratifying on number of MC1R variants, we observed a lower

melanoma risk associated with GSTT1 null allele in carriers of less than two MC1R variants as

compared to subjects having two or more variants (test of homogeneity between ORs being

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puisquon ne peut rien comparer (diffrente mthode de gnotypage et diffrente population

tudie?) Ceci a t raccourci.

The decrease in odds-ratio associated with the effect ofGSTT1 was enhanced when MC1R

was added to the regression model including CDKN2A as compared to the model with

CDKN2A alone. No significant interaction between MC1R and GSTT1 on melanoma risk

could be detected. However, estimates of ORs associated with GSTT1, which were lower in

subjects with less than two MC1R variants than in those with two variants or more, suggest

such interaction which may become significant in larger samples. The protective effect of

GSTT1 was of the same order of magnitude when considering separately RHC and NRHC

variants. The higher significance level observed in presence of NRHC as compared to RHC

variants may be accounted for by differences in sample size (149 and 115 subjects examined

in presence of NRHC and RHC variants respectively). Moreover, the stepwise analysis

showed that dysplastic nevi increased significantly melanoma risk independently from the

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where a decrease in risk, although not significant, was found in subjects carrying at least one

GSTM1 null allele. As observed forGSTT1, the decrease in OR was higher when MC1R was

included in the model and was similar whether considering number ofMC1R variants, RHC

orNRHCvariants. Pooling the effects of both GSTM1 and GSTT1 gene (having at least one

GSTT1 or GSTM1 null allele) led also to a reduced melanoma risk which remained not

significant (results not shown).

To our knowledge, only one Slovenian case-control study has investigated the role of

GSTP1 gene on melanoma risk [Dolzan et al., 2006] and found that none ofGSTP1 genotypes

influenced significantly melanoma risk as in our study.

The finding of an association between the GSTT1 null allele and a decreased risk of

melanoma was somehow unexpected but has to be interpreted in the context of CDKN2A

mutations and MC1R variants. These three genes are involved in multiple pathways with

complex interactions between these pathways and it has been reported that key genetic factors

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can lead to proliferation, differentiation and stress adaptation but also apoptosis [Wittgen and

Kempen, 2007]. The -melanocyte-stimulating hormone (-MSH), acting through MC1R,

plays a major role in the pigmentation process which involves melanin synthesis that guards

against the photodamaging effects of UV and acts as a scavenger of ROS [Miyamura et al,

2007]. However, melanin can also turn into a prooxidant under oxidative stress as a result of

inflammation or higher metabolic processes [Wittgen and Kempen, 2007]. Besides its effects

on pigmentation, -MSH is involved in antiapoptotic and DNA repair pathways [Kadekaro et

al, 2005; Miyamura et al., 2007] and has also been shown to potentiate the expression of

CDKN2A gene product (p16) after UV exposure [Pavey and Gabrielli, 2002]. MC1R

expression is also regulated by oxidative products [Garcia-Borron et al., 2005]. The positive

and negative feedbacks among these various factors underlie the complexity of the

mechanisms involved.

O ibl l ti th t ld b t f d i th t th ti GSTT1 ti

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_________________________________________________________________________

Previous version / biology

Biological hypotheses can be put forward in an attempt to explain the significant protective

effect ofGSTT1 null allele on melanoma risk as evidenced in the present genetic context of

CDKN2A mutations and MC1R variants. Increased UV exposure is regarded as the major

environmental factor contributing to melanoma. Pleiotropic effects of UV irradiation on skin

cells include direct DNA damage and formation of ROS. ROS can directly attack DNA or can

cause DNA damage following reaction with membrane lipids [Hayes et al., 2005].

Accordingly, genetic variations of enzymes involved in the detoxification of oxidative stress

products have been postulated to influence the risk of melanoma and other skin cancers

related to UV exposure [Afaq et al., 2001]. GSTs are a family of isoenzymes that catalyze the

detoxification of substrates of ROS and theconjugation of the tripeptide glutathione (GSH) to

minimize injurious events that results from toxic chemicals and normal oxidative products of

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shown that -MSH, acting through MC1R, potentiates the expression of CDKN2A gene

product (p16) after UV exposure (Pavey and Gabrielli, 2002). The -MSH protein, besides its

effect on pigmentation, plays a role in apoptotic/antiapoptotic and DNA repair pathways

(Kadekaro et al, 2005; Miyamura et al., 2006). Reactive oxygen species are involved in the

regulation of many signaling pathways which can lead to proliferation, differentiation and

stress adaptation but also apoptosis (Wittgen and Kempen, 2007).

A first hypothesis would be that the absence of GSTT1 protein induces an increase of cell

death when the number of deleterious genetic events (such as UV-induced DNA damages) in

melanocytes is accumulating, thus preventing the transformation to cancerous state. UV-

induced DNA damage could be BRAF oncogenic somatic mutations as it has been shown

recently that BRAF mutations are a characteristic feature of non-CSD melanoma in

individuals carriers of two variant MC1R alleles, such mutation could be the result of A>T

i d i d f ROS [L di l 2006] Th f h i

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that GSH depletion is involved in apoptosis, and that this process is independent of ROS

formation [Franco et al., 2007].

Because unrepaired DNA damages appear to play a central role in carcinogenesis, the

effect of GST genes had been widely studied in different types of cancer (such as breast,

colon, lung, and brain cancers). Although homozygous deletion forGSTM1 slightly increased

lung cancer risk and homozygous deletion forGSTM1 and GSTT1 slightly increased head and

neck cancer risk, controversial results were found for other cancers by epidemiological studies

[Hayes et al., 2005; Parl, 2005 for reviews]. Interestingly, one study [Roodi, 2004] has

suggested a protective effect of the GSTM1 deletion on breast cancer. Subjects carrying two

active GSTM1 alleles had increased risk of breast cancer, compared to subjects carrying the

GSTM1 null genotype: the relative risk adjusted for age was 2.83 (95% CI 1.45-5.59) in

Caucasian women while the increased risk was not significant in African-American women

(the relative risk adjusted for age was 1.66, 95% CI 0.66-4.20).

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phenotype relationships in U.S. melanoma-prone families with CDKN2A and CDK4

mutations. J Natl Cancer Inst 92:1006-10.

Goldstein AM, Landi MT, Tsang S, Fraser MC, Munroe DJ, Tucker MA. 2005. Association of

MC1R variants and risk of melanoma in melanoma-prone families with CDKN2A

mutations. Cancer Epidemiol Biomarkers Prev 14(9):2208-12.

Goldstein AM, Chan M, Harland M, Hayward NK, Demenais F, Bishop DT, Azizi E,

Bergman W, Bianchi-Scarra G, Bruno W Calista D, Albright LA, Chaudru V, Chompret A,

Cuellar F, Elder DE, Ghiorzo P, Gillanders EM, Gruis NA, Hansson J, Hogg D, Holland

EA, Kanetsky PA, Kefford RF, Landi MT, Lang J, Leachman SA, MacKie RM,

Magnusson V, Mann GJ, Bishop JN, Palmer JM, Puig S, Puig-Butille JA, Stark M, Tsao H,

Tucker MA, Whitaker L, Yakobson E; Lund Melanoma Study Group; Melanoma Genetics

Consortium (GenoMEL). 2007a. Features associated with germline CDKN2A mutations: a

GenoMEL study of melanoma-prone families from three continents. J Med Genet

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Heagerty AH, Fitzgerald D, Smith A, Bowers B, Jones P, Fryer AA, Zhao L, Alldersea J,

Strange RC. 1994. Glutathione S-transferase GSTM1 phenotypes and protection against

cutaneous tumours. Lancet 343(8892):266-8.

Kadekaro AL, Kavanagh R, Kanto H, Terzieva S, Hauser J, Kobayashi N, Schwemberger S,

Cornelius J, Babcock G, Shertzer HG, Scott G, Abdel-Malek ZA. 2005. alpha-

Melanocortin and endothelin-1 activate antiapoptotic pathways and reduce DNA damage in

human melanocytes. Cancer Res 65(10):4292-9.

Kanetsky PA, Holmes R, Walker A, Najarian D, Swoyer J, Guerry D, Halpern A, Rebbeck

TR. 2001. Interaction of glutathione S-transferase M1 and T1 genotypes and malignant

melanoma. Cancer Epidemiol Biomarkers Prev 10(5):509-13.

Kennedy C, ter Huurne J, Berkhout M, Gruis N, Bastiaens M, Bergman W, Willemze R, JN B.

2001. Melanocortin 1 receptor (MC1R) gene variants are associated with an increased risk

for cutaneous melanoma which is largely independent of skin type and hair color. J Invest

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Miyamura Y, Coelho SG, Wolber R, Miller SA, Wakamatsu K, Zmudzka BZ, Ito S, Smuda C,

Passeron T, Choi W, Batzer J, Yamaguchi Y, Beer JZ, Hearing VJ. 2007. Regulation of

human skin pigmentation and responses to ultraviolet radiation. Pigment Cell Res

20(1):2-13. Review.

Mossner R, Anders N, Konig IR, Kruger U, Schmidt D, Berking C, Ziegler A, Brockmoller J,

Kaiser R, Volkenandt M, Westphal GA, Reich K. 2007. Variations of the melanocortin-1

receptor and the glutathione-S transferase T1 and M1 genes in cutaneous malignant

melanoma. Arch Dermatol Res 298(8):371-9.

Palmer JS, Duffy DL, Box NF, Aitken JF, O'Gorman LE, Green AC, Hayward NK, Martin

NG, RA S. 2000. Melanocortin-1 receptor polymorphisms and risk of melanoma: is the

association explained solely by pigmentation phenotype? Am J Hum Genet 66:176-86.

Parl FF. 2005. "Glutathione S-transferase genotypes and cancer risk." Cancer Lett 221(2):

123-9.

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carcinoma syndrome or sporadic melanoma. Carcinogenesis 16(8):2003-4.

Soufir N, Avril MF, Chompret A, Demenais F, Bombled J, Spatz A, Stoppa-Lyonnet D,

Benard J, Bressac-de Paillerets B. 1998. Prevalence of p16 and CDK4 germline mutations

in 48 melanoma-prone families in France. The French Familial Melanoma Study Group.

Hum Mol Genet 7:209-16.

Sturm RA, Teasdale RD, NF B. 2001. Human pigmentation genes: identification, structure

and consequences of polymorphisms variations. Gene 277:49-62.

Tucker MA and Goldstein AM. 2003. " Melanoma etiology: where are we?" Oncogene 22:

3042-52.

van der Velden PA, Sandkuijl LA, Bergman W, Pavel S, van Mourik L, Frants RR, NA G.

2001. Melanocortin-1 receptor variant Arg151Cys modifies melanoma risk in Dutch

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Table 1

Distribution of GST genotyped by melanoma affection status and crude odds-ratio associated to the GSTgenes in the total sample and in

the subset ofCDKN2A mutation carriers

Carriers and non carriers ofCDKN2A mutations

(N=195)

carriers ofCDKN2A mutations

(N=96)

No. of

GST genotypes genotyped

subject (%)

Cases/Controls Odds-Ratio 95% CI

No. of

genotyped

subject (%)

Cases/Controls Odds-Ratio 95% CI

GSTM1b

+/+

+/-

-/-

24 (12.9)

93 (47.3)

78 (39.8)

9/15

28/65

19/59

1.00

0.72

0.54

-

0.28-

1.83

0.20-

1.42

15 (15.6)

47 (48.9)

34 (35.4)

8/7

27/20

18/16

1.00

1.18

0.98

-

0.37-

3.80

0.29-

3.33pa =0.43 pa =0.96

GSTT1b

+/+

+/-

-/-

54 (27.7)

105 (53.8)

36 (18.5)

21/33

27/78

8/28

1.00

0.54

0.45

-

0.27-

1.10

0.17-

1.17

29 (30.2)

49 (51.0)

18 (18.7)

20/9

25/24

8/10

1.00

0.47

0.36

-

0.18-

1.23

0.11-1.22

pa=0.14 pa =0.18

GSTP1

p.I105V (A>G): A/A

A/G

G/G

91 (46.7)

92 (47.2)

12 (6.1)

24/67

27/65

5/7

1.00

1.16

1.99

-

0.61-

2.22

0.58-

6.88

44 (45.8)

43 (44.8)

9 (9.4)

23/21

25/18

5/4

1.00

1.27

1.14

-

0.54-

2.96

0.27-

4.83

pa =0.49 pa =0.91

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p.A114V (C>T): C/C

C/T

T/T

170 (87.2)

25 (12.8)

0 (0)

50/120

6/19

-

1.00

0.76

-

-

0.29-

2.01

-

86 (89.6)

10 (10.4)

0 (0)

47/39

6/4

-

1.00

1.25

-

-

0.33-

4.73

-

pa =0.64 pa =1.00a

: p = p-value associated to the Fisher exact test in order to compare GST allele frequencies in affected and non affected members of melanoma-prone familiesb: + = active allele, - = null allele

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Table 2

Effect of GST genes on melanoma risk by taking into account successively age, sex, CDKN2A, andMC1R in the total sample of carriers

and non carriers ofCDKN2A mutations.

Adjustment model

Age, sex, CDKN2A Age, sex, CDKN2A,

MC1RaAge, sex, CDKN2A,

RHC

Age, sex, CDKN2A,

NRHC

Gene testedOR (95% CI)

p-value

OR (95% CI)

p-value

OR (95% CI)

p-value

OR (95% CI)

p-value

N=195 N=195 N=115b N=149b

GSTT1 c

+/- or -/-0.41 [0.18-0.94]

0.035

0.24 [0.15-0.58]0.001

0.29 [0.09-0.98]0.046

0.33 [0.14-0.75]0.008

GSTM1 c

+/- or -/-0.84 [0.35-2.01]

0.699

0.42 [0.15-1.11]0.081

0.46 [0.09-2.25]0.338

0.45 [0.12-1.67]0.230

GSTP1p. I105VC/T or T/T

1.22 [0.63-2.35]0.550

1.28 [0.57-2.89]0.545

1.36 [0.42-4.46]0.607

1.55 [0.72-3.32]0.264

GSTP1 p.A114VA/G or G/G

0.99 [0.42-2.33]0.987

1.29 [0.41-4.09]0.661

4.02 [0.49-33.20]0.196

0.82 [0.21-3.20]0.771

a: the MC1R variable includes two dummy variables : a variable were the baseline category included MC1R consensus compared to subject with

1 MC1R variant and a second variable were the baseline category included MC1R consensus compared to subject with at least 2 MC1R variants.

b: When the RHC and NRHC variables were considered, some subjects were excluded from the analyse since the baseline category included

MC1R consensus homozygous subjects while the at-risk category included subjects with either at least one RHC variant (and no NRHC variant)

or at least one NRHC variant (and no RHC variant) .

c: + = active allele, - = null allele

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Table 3

Outcomes of the unconditional logistic regression analyses selecting the effects ofMC1R gene, GSTT1 gene, and host factors (nevi

phenotypes) by a stepwise procedure in the total sample of carriers and non carriers ofCDKN2A mutations.

Effect of the following variable on melanoma risk

1 MC1R variant 2 MC1R variants GSTT1 b

+/- or -/-

Presence of

Dysplastic nevi

(DN)

High number

of nevi

(HNN)

Model ORa (95% CI)

p-value

ORa (95% CI)

p-value

ORa (95% CI)

p-value

ORa (95% CI)

p-value

ORa (95% CI)

p-value

1. MC1R 1.42 [0.46-4.42]0.546

6.24 [1.68-23.21]0.006

- - -

2. GSTT1 added to model 1 1.33 [0.42-4.21]0.627

7.68 [2.16-27.33]0.002

0.24 [0.10-0.58]0.001

- -

3. DN added to model 2 1.34 [0.42-4.23]0.623

10.17 [2.88-35.91]

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