The most influential standard prognostic factor for melanoma is Breslow thickness (thickness). Tissue microarrays (TMAs) have identified thickness biomarkers, including RGS1 (Rangel et al., 2008Rangel J. Nosrati M. Leong S.P. Haqq C. Miller III, J.R. Sagebiel R.W. et al.Novel role for RGS1 in melanoma progression.Am J Surg Pathol. 2008; 32: 1207-1212Crossref PubMed Scopus (54) Google Scholar), ING4 (Li et al., 2008Li J. Martinka M. Li G. Role of ING4 in human melanoma cell migration, invasion and patient survival.Carcinogenesis. 2008; 29: 1373-1379Crossref PubMed Scopus (100) Google Scholar), and total/atypical nevi (Geller et al., 2016Geller A.C. Mayer J.E. Sober A.J. Miller D.R. Argenziano G. Johnson T.M. et al.Total nevi, atypical nevi, and melanoma thickness: an analysis of 566 patients at 2 US centers.JAMA Dermatol. 2016; 152: 413-418Crossref PubMed Scopus (14) Google Scholar). In TMA, 23 of 24 DNA repair genes were upregulated with increasing thickness, whereas genes involved in serine-type endopeptidase inhibitor activity, cell adhesion, cell-cell signaling, and transcription factor activity were downregulated (Winnepenninckx et al., 2006Winnepenninckx V. Lazar V. Michiels S. Dessen P. Stas M. Alonso S.R. et al.Gene expression profiling of primary cutaneous melanoma and clinical outcome.J Natl Cancer Inst. 2006; 98: 472-482Crossref PubMed Scopus (419) Google Scholar). Reduced gene dosage across 9p21.3, including CDKN2B, P14ARF, and CDKN2A, was associated with increased thickness (Conway et al., 2010Conway C. Beswick S. Elliott F. Chang Y.M. Randerson-Moor J. Harland M. et al.Deletion at chromosome arm 9p in relation to BRAF/NRAS mutations and prognostic significance for primary melanoma.Genes Chromosomes Cancer. 2010; 49: 425-438Crossref PubMed Scopus (41) Google Scholar). Finally, association has been reported between thickness and vitamin D receptor gene polymorphisms (Santonocito et al., 2007Santonocito C. Capizzi R. Concolino P. Lavieri M.M. Paradisi A. Gentileschi S. et al.Association between cutaneous melanoma, Breslow thickness and vitamin D receptor BsmI polymorphism.Br J Dermatol. 2007; 156: 277-282Crossref PubMed Scopus (62) Google Scholar). To better understand genes involved in determining thickness and evaluate contributions of genetic variation to melanoma disease severity, we performed a genome-wide association study (GWAS) of thickness. Study populations consisted of 1,804 patients with melanoma from MD Anderson Cancer Center (MDACC) (Amos et al., 2011Amos C.I. Wang L.E. Lee J.E. Gershenwald J.E. Chen W.V. Fang S. et al.Genome-wide association study identifies novel loci predisposing to cutaneous melanoma.Hum Mol Genet. 2011; 20: 5012-5023Crossref PubMed Scopus (157) Google Scholar) and 966 patients from the French Melanoma Risk study (MELARISK) (Chaudru et al., 2004Chaudru V. Chompret A. Bressac-De Paillerets B. Spatz A. Avril M.F. Demenais F. Influence of genes, nevi, and sun sensitivity on melanoma risk in a family sample unselected by family history and in melanoma-prone families.J Natl Cancer Inst. 2004; 96: 785-795Crossref PubMed Scopus (86) Google Scholar). Populations and genotyping methods are described in Supplementary Texts S1 and S2 and Supplementary Tables S1 and S2 online. After imputation and quality control, we had 2.65 million single nucleotide polymorphisms (SNPs) in MDACC and 1.05 million SNPs in MELARISK. All individuals provided written, informed consent under an institutional review board-approved protocol. We confirmed that thickness represented an independent risk factor for disease-free survival, overall survival, and melanoma-specific survival after adjustment for sex, age, and disease stage (Supplementary Tables S3 and S4 online). The independent association between thickness and overall survival was replicated in MELARISK (hazard ratio = 1.11, 95% confidence interval = 1.07–1.16, Supplementary Table S4); disease-free survival and melanoma-specific survival were not available in MELARISK. Because the distribution of raw thickness was skewed, we used the logarithm to base 10 of thickness for GWAS (Supplementary Figure S1 online). The Q-Q plot for MDACC is shown in Supplementary Figure S2 online. MDACC GWAS results are shown in Supplementary Figure S3 and Table S5 online (P < 10−5). The 20 SNPs most strongly associated with thickness spanned four loci (1p12, 6q23, 8q22, 11p15, and 19p13; Table 1 and Supplementary Table S5). The most significant loci were close to mucin 2 (MUC2)/mucin 5AC (MUC5AC) and calreticulin (CALR)/RAD23 homolog A (RAD23A). The most significant imputed SNP, rs12365253, was near MUC2/MUC5AC and had a P-value of 5.6 × 10−8, close to the nominal genome-wide significance level of 5.0 × 10−8. The most strongly associated SNP was supported by concordant results for genotyped SNPs in linkage disequilibrium with it (r2 = 0.7817 with genotyped SNP rs64211966, P-value 3.2 × 10−7). The most significant genotyped SNP, rs17859811, had a P-value of 1.2 × 10−7, but was in moderate linkage disequilibrium (r2 = 0.53, D′ = −0.84) with rs12365253 (Supplementary Figure S4 online). The most significant imputed SNP, rs1049481, near CALR/RAD23A, had a P-value of 5.8 × 10−7, followed by a genotyped SNP, rs2974755 (P = 7.6 × 10−7). These two variants were in strong linkage disequilibrium (r2 = 0.96, D′ = 0.99; Supplementary Figure S5 online). We performed joint analysis of the most significant genotyped SNPs rs17859811 in the MUC2/MUC5AC region and rs2974755 in the CALR/RAD23A region, and observed that the P-value decreased to 2.6 × 10−12.Table 1Tumor-thickness-related SNPs in MDACC and MELARISK studies and their association with melanoma outcomeSNPChrPosition1Position in base pair according to the genome build 36.3.Nearby GeneEffect alleleTumor thicknessAssociation with melanoma outcome in MDACCMDACCMELARISKHeterogeneity4The I2 heterogeneity measure is the percentage of variation in study estimates that is due to heterogeneity. Cochran is the P-value of Cochran’s test for heterogeneity.Random-effectsMeta-analysis5βrand and serand are the regression coefficient and standard error of the SNP effect, respectively, in the meta-analysis of MDACC and MELARISK (using a random-effects model). Prand is the P-value associated with the Wald test of the meta-analyzed SNP effect.P-valueEAF2EAF: effect allele frequency.β3β and se are the regression coefficient and standard error of the SNP effect, respectively, estimated by linear regression assuming an additive model.se3β and se are the regression coefficient and standard error of the SNP effect, respectively, estimated by linear regression assuming an additive model.PEAF2EAF: effect allele frequency.β3β and se are the regression coefficient and standard error of the SNP effect, respectively, estimated by linear regression assuming an additive model.se3β and se are the regression coefficient and standard error of the SNP effect, respectively, estimated by linear regression assuming an additive model.PI2 [95% CI]Cochranβ randserandP randStage (III/VI vs. I/II)MSSOS6P-values for those significant SNPs for OS with adjustment for sex, age, and thickness: rs12365253 P = 0.27, rs6421966 P = 0.05, rs7130988 P = 0.02, rs7112954 P = 0.02, rs17859811 P = 0.22.DFS7P-values for those significant SNPs for DFS with adjustment for sex, age, and thickness: rs1049481 P = 0.11, rs2974755 P = 0.09.rs75263891119,616,604WARS2/HAO2A0.50−0.070.013.7 × 10−7––––0.160.791.000.90rs15391881119,630,065WARS2/HAO2C0.49−0.070.018.3 × 10−70.470.050.026.8 × 10−396.3 [89.9–98.7]1.8 × 10−7−0.010.060.840.190.690.890.86rs12365253111,106,034MUC2/MUC5ACC0.790.100.025.6 × 10−8––––0.420.050.020.39rs6421966111,116,979MUC2/MUC5ACG0.19−0.090.023.2 × 10−70.170.000.020.9789.8 [62.3–97.2]1.8 × 10−3−0.050.050.310.651.6 × 10−39 × 10−40.16rs7130988111,119,721MUC2/MUC5ACA0.810.090.024.6 × 10−70.830.000.020.9889.4 [60.7–97.2]2.1 × 10−30.050.050.310.634.4 × 10−34.1 × 10−30.98rs7112954111,127,086MUC2/MUC5ACC0.810.100.024.7 × 10−70.840.000.020.8590.8 [66.9–97.4]1.0 × 10−30.050.050.350.552.7 × 10−32.7 × 10−30.98rs17859811111,140,353MUC2/MUC5ACA0.18−0.100.021.2 × 10−70.160.010.030.7190.8 [67.1–97.4]9.6 × 10−4−0.050.060.390.131 × 10−42 × 10−40.16rs10494811912,915,781CALRG0.390.080.025.8 × 10−70.420.010.020.4484.6 [37–96.2]0.010.050.030.130.040.050.120.03rs29747551912,923,663RAD23AC0.390.070.027.6 × 10−70.410.020.020.3581.9 [23.3–95.7]0.020.050.030.0950.030.070.130.02Note that the single nucleotide polymorphisms (SNPs) rs7526389 and rs12365253 were not present in the HapMap3 imputation panel used for French MELRISK study.Abbreviations: Chr, chromosome; CI, confidence interval; DFS, disease-free survival; MDACC, MD Anderson Cancer Center; MELARISK, the French Melanoma Risk study; MSS, melanoma-specific survival; OS, overall survival; SNP, single nucleotide polymorphisms.1 Position in base pair according to the genome build 36.3.2 EAF: effect allele frequency.3 β and se are the regression coefficient and standard error of the SNP effect, respectively, estimated by linear regression assuming an additive model.4 The I2 heterogeneity measure is the percentage of variation in study estimates that is due to heterogeneity. Cochran is the P-value of Cochran’s test for heterogeneity.5 βrand and serand are the regression coefficient and standard error of the SNP effect, respectively, in the meta-analysis of MDACC and MELARISK (using a random-effects model). Prand is the P-value associated with the Wald test of the meta-analyzed SNP effect.6 P-values for those significant SNPs for OS with adjustment for sex, age, and thickness: rs12365253 P = 0.27, rs6421966 P = 0.05, rs7130988 P = 0.02, rs7112954 P = 0.02, rs17859811 P = 0.22.7 P-values for those significant SNPs for DFS with adjustment for sex, age, and thickness: rs1049481 P = 0.11, rs2974755 P = 0.09. Open table in a new tab Note that the single nucleotide polymorphisms (SNPs) rs7526389 and rs12365253 were not present in the HapMap3 imputation panel used for French MELRISK study. Abbreviations: Chr, chromosome; CI, confidence interval; DFS, disease-free survival; MDACC, MD Anderson Cancer Center; MELARISK, the French Melanoma Risk study; MSS, melanoma-specific survival; OS, overall survival; SNP, single nucleotide polymorphisms. All five SNPs in the MUC2/MUC5AC gene regions were in strong linkage disequilibrium (r2 ≥ 0.70 with the most significant SNP rs12365253) and were nominally associated with overall survival and melanoma-specific survival in MDACC (all P-values < 0.05, Table 1, Supplementary Table S6 online). Two SNPs in the CALR/RAD23A region had borderline significance for melanoma-specific survival but were associated with disease-free survival (P-value < 0.05, Table 1). After adjustment for thickness these associations were less significant, suggesting that any effect of these loci on melanoma recurrence or survival is at least partially mediated through tumor thickness. Top-associated SNPs were selected for attempted replication (Table 1). Neither of our two most strongly associated loci (MUC2/MUC5AC and CALR/RAD23A) were replicated in MELARISK, and another SNP (rs1539188) in the WARS2/HAO2 region was not replicated (MDACC P = 8.3 × 10−7, MELARISK P = 6.8 × 10−3, with opposite direction of effects in the two studies. Furthermore, the joint effect of the two most significant MDACC SNPs, rs17859811 (MUC2/MUC5AC) and rs2974755 (CALR/RAD23A), was not replicated (P = 0.60). We performed gene-based testing using Versatile Gene-based Association Study (VEGAS) (Liu et al., 2010Liu J.Z. Mcrae A.F. Nyholt D.R. Medland S.E. Wray N.R. Brown K.M. et al.A versatile gene-based test for genome-wide association studies.Am J Hum Genet. 2010; 87: 139-145Abstract Full Text Full Text PDF PubMed Scopus (632) Google Scholar) and found that MUC2 and MUC5AC were significantly associated with tumor thickness in MDACC (both P-values reached the multiple testing corrected threshold of 2.8 × 10−6, Supplementary Table S7 online). Results also suggested the association of CALR and RAD23A with thickness in MDACC (P ≤ 10−5, Supplementary Table S7). However, none of these genes was replicated in MELARISK (Supplementary Table S7). Notably, previous pathway analysis for melanoma risk in MDACC and MELARISK identified five pathways (Brossard et al., 2015Brossard M. Fang S. Vaysse A. Wei Q. Chen W.V. Mohamdi H. et al.Integrated pathway and epistasis analysis reveals interactive effect of genetic variants at TERF1 and AFAP1L2 loci on melanoma risk.Int J Cancer. 2015; 137: 1901-1909Crossref PubMed Scopus (10) Google Scholar), among which was the induction of the programmed cell death pathway that includes MUC2 and MUC5AC. Furthermore, MUC2 and MUC5AC were associated with melanoma risk in both datasets (Supplementary Table S8 online; P-values for the best SNP in each gene <0.05), indicating those genes may also contribute to melanoma development. We investigated expression of MUC2/MUC5AC and CALR/RAD23A in melanomas and nevi (Supplementary Text S1). We also investigated MUC2 expression in tumors from 84 patients not included in MDACC. Using immunohistochemistry (IHC), we stained slides from 60 primary and 24 metastatic melanoma tumors (none from the same patient). We also stained TMAs containing 40 benign nevi and 12 primary melanoma tumors. The GWAS, IHC, and TMA cohorts had similar demographic distributions (mean age: GWAS 52.1, IHC 53.9, TMA 52.5; male percentage: GWAS 58.7, IHC 59.3, TMA 62.7; P-values > 0.05). Although MUC2 was commonly expressed in primary melanomas and metastases, we identified no significant difference in MUC2 expression across thickness groups (Figure 1; P = 0.824, Supplementary Figure S6 online), or between primary tumors and metastases (P = 0.484, Supplementary Figure S6). In TMA, primary tumors demonstrated higher expression of MUC2 than nevi (P = 0.025, Supplementary Figure S7 online). mRNA analysis of 17 metastatic tumors (12 regional, 5 distant) (Supplementary Figure S8 online) identified MUC2 mRNA in the majority of melanoma tumors but no correlation between mRNA expression and thickness (Pearson correlation coefficient = 0.267, P = 0.487; data not shown). Finally, we confirmed MUC2 protein by western blot of regional metastases from two patients with melanoma with high MUC2 expression by IHC (Supplementary Figure S9 online). In summary, top polymorphisms associated with melanoma tumor thickness from MDACC GWAS were not replicated in external validation, possibly due to population-based differences (Supplementary Text S2). However, MUC2 conferred risk for development of melanoma in both datasets, and MUC2 was commonly expressed in both primary melanomas and metastases. No association was identified between the level of MUC2 expression and thickness. These studies provide preliminary evidence suggesting that MUC2 may confer risk for melanoma susceptibility, tumor thickness, and/or disease severity. The authors state no conflict of interest. This work was supported by the National Institutes of Health/National Cancer Institute [5R03 CA173792, Specialized Program of Research Excellence grant P50 CA093459]; the University of Texas MD Anderson Cancer Center Various Donors Melanoma and Skin Cancers Priority Program Fund; the Miriam and Jim Mulva Research Fund; the McCarthy Skin Cancer Research Fund and the Marit Peterson Fund for Melanoma Research. This work was also supported by Programme Hospitalier de Recherche Clinique (PHRC) [AOM-07-195], the Institut National du Cancer (INCa) [INCa_5982], the Ligue Nationale Contre le Cancer [PRE 09/FD and doctoral fellowship n° 2010.239], the Fondation pour la Recherche Médicale (FRM) [FDT20130928343], the European Commission under the 6th Framework Programme [LSH-CT-2006-018702]. We thank the John Hopkins University Center for Inherited Disease Research for conducting high-throughput genotyping and the University of Washington for the performance of quality control of the high-density SNP data of the MD Anderson Cancer Center cohort. We also thank the French Familial Study Group for their contribution to the MELARISK collection (M.F. Avril, P. Andry-Benzaquen, B. Bachollet, F. Bérard, P. Berthet, F. Boitier, V. Bonadona, B. Bressac-de Paillerets, J.L. Bonafé, J.M. Bonnetblanc, F. Cambazard, O. Caron, F. Caux, J. Chevrant-Breton, A. Chompret (deceased), S. Dalle, L. Demange, O. Dereure, M.X. Doré, M.S. Doutre, C. Dugast, L. Faivre, F. Grange, Ph. Humbert, P. Joly, D. Kerob, C. Lasset, M.T. Leccia, G. Lenoir, D. Leroux, J. Levang, D. Lipsker, S. Mansard, L. Martin, T. Martin-Denavit, C. Mateus, E. Maubec, J.L. Michel, P. Morel, L. Olivier-Faivre, J.L. Perrot, C. Robert, S. Ronger-Savle, B. Sassolas, P. Souteyrand, D. Stoppa-Lyonnet, L. Thomas, P. Vabres, E. Wierzbicka). We acknowledge that the biological specimens of the French MELARISK study were obtained from the Institut Gustave Roussy and Fondation Jean Dausset–CEPH Biobanks. We thank the Centre National de Génotypage (CNG-CEA, Evry, France) and Service XS (Leiden, the Netherlands) for performing genome-wide genotyping in the MELARISK study. Download .pdf (.92 MB) Help with pdf files Supplementary Data