{"http:\/\/dx.doi.org\/10.14288\/1.0406308":{"http:\/\/vivoweb.org\/ontology\/core#departmentOrSchool":[{"value":"Medicine, Faculty of","type":"literal","lang":"en"},{"value":"Non UBC","type":"literal","lang":"en"},{"value":"Dermatology and Skin Science, Department of","type":"literal","lang":"en"}],"http:\/\/www.europeana.eu\/schemas\/edm\/dataProvider":[{"value":"DSpace","type":"literal","lang":"en"}],"https:\/\/open.library.ubc.ca\/terms#identifierCitation":[{"value":"Current Oncology 28 (6): 4756-4771 (2021)","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/contributor":[{"value":"BC Cancer Agency","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/creator":[{"value":"Davari, Danielle R.","type":"literal","lang":"en"},{"value":"Orlow, Irene","type":"literal","lang":"en"},{"value":"Kanetsky, Peter A.","type":"literal","lang":"en"},{"value":"Luo, Li","type":"literal","lang":"en"},{"value":"Busam, Klaus J.","type":"literal","lang":"en"},{"value":"Sharma, Ajay","type":"literal","lang":"en"},{"value":"Kricker, Anne","type":"literal","lang":"en"},{"value":"Cust, Anne E.","type":"literal","lang":"en"},{"value":"Anton-Culver, Hoda","type":"literal","lang":"en"},{"value":"Gruber, Stephen B.","type":"literal","lang":"en"},{"value":"Gallagher, R. P. (Richard P.), 1944-","type":"literal","lang":"en"},{"value":"Zanetti, Roberto","type":"literal","lang":"en"},{"value":"Rosso, Stefano","type":"literal","lang":"en"},{"value":"Sacchetto, Lidia","type":"literal","lang":"en"},{"value":"Dwyer, Terence","type":"literal","lang":"en"},{"value":"Gibbs, David C.","type":"literal","lang":"en"},{"value":"Ollila, David W.","type":"literal","lang":"en"},{"value":"Begg, Colin B.","type":"literal","lang":"en"},{"value":"Berwick, Marianne","type":"literal","lang":"en"},{"value":"Thomas, Nancy E.","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/issued":[{"value":"2022-01-19T17:02:08Z","type":"literal","lang":"en"},{"value":"2021-11-16","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/description":[{"value":"Genome-wide association studies (GWAS) and candidate pathway studies have identified low-penetrant genetic variants associated with cutaneous melanoma. We investigated the association of melanoma-risk variants with primary melanoma tumor prognostic characteristics and melanoma-specific survival. The Genes, Environment, and Melanoma Study enrolled 3285 European origin participants with incident invasive primary melanoma. For each of 47 melanoma-risk single nucleotide polymorphisms (SNPs), we used linear and logistic regression modeling to estimate, respectively, the per allele mean changes in log of Breslow thickness and odds ratios for presence of ulceration, mitoses, and tumor-infiltrating lymphocytes (TILs). We also used Cox proportional hazards regression modeling to estimate the per allele hazard ratios for melanoma-specific survival. Passing the false discovery threshold (p = 0.0026) were associations of IRF4 rs12203592 and CCND1 rs1485993 with log of Breslow thickness, and association of TERT rs2242652 with presence of mitoses. IRF4 rs12203592 also had nominal associations (p < 0.05) with presence of mitoses and melanoma-specific survival, as well as a borderline association (p = 0.07) with ulceration. CCND1 rs1485993 also had a borderline association with presence of mitoses (p = 0.06). MX2 rs45430 had nominal associations with log of Breslow thickness, presence of mitoses, and melanoma-specific survival. Our study indicates that further research investigating the associations of these genetic variants with underlying biologic pathways related to tumor progression is warranted.","type":"literal","lang":"en"}],"http:\/\/www.europeana.eu\/schemas\/edm\/aggregatedCHO":[{"value":"https:\/\/circle.library.ubc.ca\/rest\/handle\/2429\/80683?expand=metadata","type":"literal","lang":"en"}],"http:\/\/www.w3.org\/2009\/08\/skos-reference\/skos.html#note":[{"value":"CommunicationAssociation of Melanoma-Risk Variants with PrimaryMelanoma Tumor Prognostic Characteristics andMelanoma-Specific Survival in the GEM StudyDanielle R. Davari 1 , Irene Orlow 2 , Peter A. Kanetsky 3 , Li Luo 4 , Klaus J. Busam 5, Ajay Sharma 2,Anne Kricker 6 , Anne E. Cust 7,8 , Hoda Anton-Culver 9, Stephen B. Gruber 10, Richard P. Gallagher 11,Roberto Zanetti 12 , Stefano Rosso 12 , Lidia Sacchetto 12, Terence Dwyer 13,14,15,16 , David C. Gibbs 17,David W. Ollila 18,19, Colin B. Begg 2, Marianne Berwick 4 and Nancy E. Thomas 1,19,*,\u2020on behalf of the GEM Study Group\u0001\u0002\u0003\u0001\u0004\u0005\u0006\u0007\b\u0001\u0001\u0002\u0003\u0004\u0005\u0006\u0007Citation: Davari, D.R.; Orlow, I.;Kanetsky, P.A.; Luo, L.; Busam, K.J.;Sharma, A.; Kricker, A.; Cust, A.E.;Anton-Culver, H.; Gruber, S.B.; et al.Association of Melanoma-RiskVariants with Primary MelanomaTumor Prognostic Characteristics andMelanoma-Specific Survival in theGEM Study. Curr. Oncol. 2021, 28,4756\u20134771. https:\/\/doi.org\/10.3390\/curroncol28060401Received: 11 August 2021Accepted: 10 November 2021Published: 16 November 2021Publisher\u2019s Note: MDPI stays neutralwith regard to jurisdictional claims inpublished maps and institutional affil-iations.Copyright: \u00a9 2021 by the authors.Licensee MDPI, Basel, Switzerland.This article is an open access articledistributed under the terms andconditions of the Creative CommonsAttribution (CC BY) license (https:\/\/creativecommons.org\/licenses\/by\/4.0\/).1 Department of Dermatology, University of North Carolina, Chapel Hill, NC 27599, USA;danielle_davari@med.unc.edu2 Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center,New York, NY 10065, USA; orlowi@mskcc.org (I.O.); Ajay.sharma2@perkinelmer.com (A.S.);beggc@mskcc.org (C.B.B.)3 Department of Cancer Epidemiology, Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA;peter.kanetsky@moffitt.org4 Department of Internal Medicine, University of New Mexico Cancer Center, University of New Mexico,Albuquerque, NM 87102, USA; lluo@salud.unm.edu (L.L.); mberwick@salud.unm.edu (M.B.)5 Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;busamk@mskcc.org6 Sydney School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia;anne.kricker@sydney.edu.au7 Daffodil Centre, The University of Sydney, a Joint Venture with Cancer Council NSW,Sydney, NSW 2006, Australia; anne.cust@sydney.edu.au8 Melanoma Institute Australia, The University of Sydney, Sydney, NSW 2065, Australia9 Department of Medicine, University of California, Irvine, CA 92697, USA; hantoncu@uci.edu10 City of Hope National Medical Center, Duarte, CA 91010, USA; sgruber@coh.org11 BC Cancer and Department of Dermatology and Skin Science, University of British Columbia,Vancouver, BC V5Z 1L3, Canada; rgallagher@bccrc.ca12 Piedmont Cancer Registry, Centre for Epidemiology and Prevention in Oncology in Piedmont,10156 Turin, Italy; roberto.zanetti@cpo.it (R.Z.); stefano.rosso@cpo.it (S.R.); lidia.sacchetto@cpo.it (L.S.)13 Murdoch Children\u2019s Research Institute, Melbourne, VIC 3052, Australia; terence.dwyer@wrh.ox.ac.uk14 The Nuffield Department of Women\u2019s & Reproductive Health, University of Oxford, Oxford OX3 9DU, UK15 Department of Pediatrics, University of Melbourne, Melbourne, VIC 3010, Australia16 Oxford Martin School, University of Oxford, Oxford OX1 3BD, UK17 School of Medicine, Emory University, Atlanta, GA 30322, USA; david.corley.gibbs@emory.edu18 Department of Surgery, University of North Carolina, Chapel Hill, NC 27599, USA;david_ollila@med.unc.edu19 Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA* Correspondence: nancy_thomas@med.unc.edu; Tel.: +1-919-966-0785; Fax: +1-919-966-6460\u2020 GEM Study Group members are listed in acknowledgments.Abstract: Genome-wide association studies (GWAS) and candidate pathway studies have identifiedlow-penetrant genetic variants associated with cutaneous melanoma. We investigated the asso-ciation of melanoma-risk variants with primary melanoma tumor prognostic characteristics andmelanoma-specific survival. The Genes, Environment, and Melanoma Study enrolled 3285 Europeanorigin participants with incident invasive primary melanoma. For each of 47 melanoma-risk singlenucleotide polymorphisms (SNPs), we used linear and logistic regression modeling to estimate,respectively, the per allele mean changes in log of Breslow thickness and odds ratios for presenceof ulceration, mitoses, and tumor-infiltrating lymphocytes (TILs). We also used Cox proportionalhazards regression modeling to estimate the per allele hazard ratios for melanoma-specific survival.Passing the false discovery threshold (p = 0.0026) were associations of IRF4 rs12203592 and CCND1rs1485993 with log of Breslow thickness, and association of TERT rs2242652 with presence of mitoses.Curr. Oncol. 2021, 28, 4756\u20134771. https:\/\/doi.org\/10.3390\/curroncol28060401 https:\/\/www.mdpi.com\/journal\/curroncolCurr. Oncol. 2021, 28 4757IRF4 rs12203592 also had nominal associations (p < 0.05) with presence of mitoses and melanoma-specific survival, as well as a borderline association (p = 0.07) with ulceration. CCND1 rs1485993also had a borderline association with presence of mitoses (p = 0.06). MX2 rs45430 had nominalassociations with log of Breslow thickness, presence of mitoses, and melanoma-specific survival. Ourstudy indicates that further research investigating the associations of these genetic variants withunderlying biologic pathways related to tumor progression is warranted.Keywords: melanoma; single nucleotide polymorphism; Breslow thickness; ulceration; mitoses;tumor-infiltrating lymphocytes; survival1. IntroductionGenome-wide association studies (GWAS) and candidate pathway studies have iden-tified low-penetrant genetic variants associated with cutaneous melanoma [1,2]. Previouslywe investigated the association of 47 single nucleotide polymorphisms (SNPs) in putativemelanoma-risk loci identified through GWAS or candidate studies with multiple primarymelanoma occurrence and found that several of these susceptibility loci are generalizable tothe risk of subsequent melanomas [3]. Many of these variants are in gene regions associatedwith pigmentation, such as SLC45A2, TYRP1, TYR, and ASIP [4\u201311]; nevi, such as NID1,MTAP, and PLA2G6 [4,6,12\u201318]; or both, such as IRF4 and HERC2\/OCA2 [4,7,13,14,19\u201323].Others are in gene regions, including ATM and MX2, not associated with melanoma-riskphenotypes [5]. Variants related to pigmentation and\/or nevus count variation likelymodify melanoma risk via these mechanisms, while others may modify risk via alternativemechanisms, such as cell proliferation [5,24].To explore whether genetic variants associated with melanoma risk could influencetumor aggressivity, we examined the associations of melanoma-risk SNPs with primarymelanoma tumor prognostic characteristics. Prognostic characteristics in melanoma in-clude Breslow thickness, ulceration, mitoses, and tumor-infiltrating lymphocytes (TILs).Breslow thickness and ulceration are the primary melanoma tumor characteristics includedin the eighth edition of the American Joint Committee on Cancer staging system [25]. Thepresence of mitoses and a lower TIL grade are associated with worse melanoma-specificsurvival [26\u201330]. We assessed the association of melanoma-risk SNPs with log of Breslowthickness, presence of ulceration, presence of mitoses, and presence of TILs in the large,international, population-based Genes, Environment, and Melanoma (GEM) Study. Toinvestigate whether genetic variants associated with melanoma risk could influence out-comes, we also examined the associations of these SNPs with melanoma-specific survival.2. Materials and Methods2.1. Study PopulationThe GEM Study enrolled 3579 participants with incident first- or higher-order pri-mary cutaneous melanoma diagnosed between 1998 and 2003 in Australia, Canada, Italy,and the United States; recruitment and data collection details have been published pre-viously [31]. Each recruitment site\u2019s institutional review board approved the study. Par-ticipants provided written informed consent. Of the 3579 patients, we limited analysesto the 3285 participants of self-reported European origin with invasive first- or higher-order primary melanoma. Twelve participants of non-European origin were excluded. Anadditional 282 patients with incident in situ melanoma were also excluded, as Breslowthickness, ulceration, mitoses, and TIL presence are not relevant for in situ melanomas.Thus, the final dataset for these analyses is 3285 subjects (1827 males and 1458 females)between ages 7 to 96 years old.Curr. Oncol. 2021, 28 47582.2. Pathology ReviewAge at diagnosis, sex, and anatomic site of the melanoma were extracted from pathol-ogy reports and confirmed during patient interview. Histologic subtype and Breslowthickness were also extracted from pathology reports. The diagnostic slides underwentcentralized pathology slide review for histopathologic characteristics [30,32\u201334], accordingto established criteria [35,36]. The pathology slide review included evaluation of histologicsubtype, Breslow thickness, ulceration, mitoses, and TIL grade. The histologic subtypefrom the centralized review was chosen unless missing, in which case the subtype fromthe pathology report was utilized. Breslow thickness was obtained from both sources, andthe measure corresponding to the deepest reading was chosen to represent the value ofmost biological relevance. Ulceration, mitoses, and TIL grade were only obtained fromthe centralized review, as these characteristics are less reliably documented in pathologyreports. Ulceration and mitoses were recorded as present or absent [37]. TIL grade wasscored as brisk, nonbrisk, or absent using a previously defined grading system [38\u201340].Missing data resulted from a lack of access to the diagnostic slide or transection of themelanoma. Breslow thickness has less missing data than ulceration, mitoses, and TIL gradebecause these latter characteristics were only obtained from centralized review, whereasBreslow thickness was obtained from both the centralized review and the pathology report.The pathologists conducting the centralized review were blinded to genotype and survival.2.3. GenotypingSNPs were selected, as described [3], based on their association with melanoma inother studies and genotyped from buccal swab DNA using the MassArray iPLEX assay(Agena Bioscience, San Diego, CA, USA; previously known as Sequenom) with reportedquality control measures [41]. The staff running assays were blinded to outcomes.2.4. SurvivalInformation about deaths from melanoma or other causes was obtained for all par-ticipants from National Death Indexes, cancer registries, and municipal records. Patientfollow-up for vital status was complete through 2008 for British Columbia, Canada, andTurin, Italy, and to the end of 2007 for all other centers.2.5. Statistical AnalysisBreslow thickness was normalized using a log transformation. Linear regression mod-els estimated the per allele mean changes in log of Breslow thickness and 95% confidenceintervals (CIs) for each SNP. TIL grade was dichotomized as present (brisk or nonbrisk)or absent. Logistic regression models estimated the per allele odds ratios (ORs) and 95%CIs for presence versus absence of ulceration, mitoses, or TILs for each SNP. These mod-els were all adjusted for baseline features (age at diagnosis, sex, and study center) andlesion status as first- or higher-order primary. We performed a principal component analy-sis of the 47 SNPs to detect potential population structure within our data, as describedpreviously [42].We next explored melanoma-specific survival. For these analyses, we limited thedataset to 2458 patients of self-reported European origin who entered the study with inva-sive first-order primary melanoma during the ascertainment period. Patients that enteredthe study with second- or higher-order primary melanoma during the ascertainment periodwere not included. For these patients, it would have been necessary to account for previousmelanomas that occurred prior to the ascertainment period, which was not included in thisinvestigation. Survival time was accumulated from the diagnosis date until the date ofdeath due to melanoma, date of death due to any cause other than melanoma, or the end offollow-up (censored patients). The median follow-up time was 7.7 years. Cox proportionalhazards regression analyses estimated the hazard ratios (HRs) and 95% CIs for the per alleleassociation of each SNP with melanoma-specific survival adjusted for baseline features. InCurr. Oncol. 2021, 28 4759this analysis, for cases who developed a second primary melanoma, the occurrence of thesecond primary was included as a time-dependent covariate.The false discovery threshold adjusted for multiple comparisons was computed usinga resampling method that considers the linkage disequilibrium information among SNPsevaluated and is less conservative than the classical Bonferroni procedure [43,44]. All testswere two-sided. Data were analyzed using Stata\/SE 16.1 (College Station, TX, USA).3. ResultsThe demographic and tumor characteristics of the 3285 GEM participants of Europeanorigin with incident invasive primary melanoma included in these analyses are in Table 1.The median age was 58 years and 55.6% were male. Most melanomas (43.7%) wereon the trunk with smaller proportions on the head or neck (17.2%), upper extremities(18.1%), and lower extremities (20.9%). The predominant subtype was superficial spreadingmelanoma (65.3%). The melanomas had a median thickness of 0.70 mm (interquartilerange = 0.44\u20131.26 mm); 6.8% had ulceration present, 32.9% had mitoses present, and 62.2%had TILs (brisk or nonbrisk TIL grade) present. The locations, minor alleles, minor allelefrequencies in GEM, and literature references for the 47 SNPs are in Table S1. The numbersof samples genotyped are in Table S2.Table 1. Characteristics of patients with incident invasive cutaneous melanoma in the GEM study(n = 3285) 1.Characteristic No. (%)Median age at most recent diagnosis (IQR),years 58 (46\u201370)SexMale 1827 (55.6)Female 1458 (44.4)Lesion statusFirst-order primary melanoma 2458 (74.8)Higher-order primary melanoma 827 (25.2)Anatomic siteHead\/neck 565 (17.2)Trunk 1437 (43.7)Upper extremities 595 (18.1)Lower extremities 688 (20.9)Histologic subtypeSuperficial spreading 2144 (65.3)Nodular 275 (8.4)Lentigo maligna 377 (11.5)Unclassified\/other 2 489 (14.9)Breslow thickness, mmMedian (IQR) 0.70 (0.44\u20131.26)0.01\u20131.00 2195 (66.8)1.01\u20132.00 592 (18.0)2.01\u20134.00 276 (8.4)>4.00 144 (4.4)Missing 78 (2.4)UlcerationAbsent 2392 (72.8)Present 225 (6.8)Missing 668 (20.3)MitosesAbsent 1544 (47.0)Present 1081 (32.9)Missing 660 (20.1)Curr. Oncol. 2021, 28 4760Table 1. Cont.Characteristic No. (%)Tumor-infiltrating lymphocyte (TIL) gradeAbsent 567 (17.3)Nonbrisk 1658 (50.5)Brisk 385 (11.7)Missing 675 (20.5)Abbreviations: GEM, Genes, Environment and Melanoma; No., number; IQR, interquartile range. 1 Limited toindividuals of European origin with incident invasive first- or higher-order primary melanoma. Percentages maynot sum to 100 because of rounding of decimals. 2 Other includes acral lentiginous, spindle cell, nevoid, andSpitzoid melanomas.Passing the false discovery threshold (p = 0.0026) were associations of IRF4 rs12203592and CCND1 rs1485993 with log of Breslow thickness, and association of TERT rs2242652with presence of mitoses (Table 2). Adjusting for the top two principal components from ourprincipal component analysis did not affect these associations (OR change 0\u20131%, results notshown). No SNPs passed false discovery for their association with presence of ulcerationor TILs or melanoma-specific survival. Nominal associations (p < 0.05) with prognosticcharacteristics and melanoma-specific survival are in Tables 2 and 3, respectively.In addition to IRF4 rs12203592*T passing false discovery for its association withincreased log of Breslow thickness, IRF4 rs12203592*T had nominal associations (p < 0.05)with presence of mitoses and worse melanoma-specific survival, as well as a borderlineassociation (p = 0.07) with presence of ulceration.In addition to CCND1 rs1485993*T passing false discovery for its association withdecreased log of Breslow thickness, CCND1 rs1485993*T was borderline associated withabsence of mitoses (p = 0.06). Also, CCND1 rs11604821*G and rs11263498*T were eachnominally associated with both decreased log of Breslow thickness and absence of mitoses.While TERT rs2242652 did not have any additional nominal associations, TERT rs2853676*Awas nominally associated with absence of mitoses, and TERT; CLPTM1L rs401681*T wasnominally associated with decreased log of Breslow thickness and absence of mitoses. MX2rs45430*G had nominal associations with decreased log of Breslow thickness and absenceof mitoses, as well as better melanoma-specific survival.We have previously reported, in separate and combined analyses of GEM and theWestern Australia Melanoma Health Study (WAMHS), the associations of IRF4 rs12203592,CCND1 rs11263498, and MX2 rs45430 with Breslow thickness [45] and IRF4 rs12203592with melanoma-specific survival among first-order primary melanoma patients [46].Curr. Oncol. 2021, 28 4761Table 2. Associations of melanoma-risk SNPs with primary melanoma tumor prognostic characteristics among patients in the GEM study 1.Tumor Prognostic CharacteristicsBreslow Thickness (n = 3207) Present vs. AbsentUlceration (n = 2617)Present vs. AbsentMitoses (n = 2625)Nonbrisk\/Brisk vs.Absent TIL grade(n = 2610)GeneNeighborhood SNP a\/APer allele mean change inlog of Breslow thickness(95% CI) 2Per allele changein Breslowthickness, % 3p Per allele OR(95% CI) 4 pPer allele OR(95% CI) 4 pPer allele OR(95% CI) 4 pARNT rs7412746 C\/T 0.02 (\u22120.02\u20130.06) 2.15 0.30 1.11 (0.91\u20131.35) 0.32 1.12 (1.00\u20131.25) 0.04 0.90 (0.79\u20131.03) 0.12PARP1 rs3219090 A\/G 0.004 (\u22120.04\u20130.05) 0.44 0.85 0.96 (0.77\u20131.19) 0.70 0.96 (0.85\u20131.08) 0.48 1.07 (0.93\u20131.25) 0.34PARP1 rs2695238 C\/G 0.01 (\u22120.03\u20130.06) 1.11 0.62 0.96 (0.78\u20131.19) 0.73 0.97 (0.86\u20131.09) 0.60 1.03 (0.89\u20131.19) 0.69NID1 rs3768080 G\/A \u22120.03 (\u22120.07\u20130.006) \u22123.35 0.10 0.83 (0.68\u20131.01) 0.06 0.91 (0.81\u20131.02) 0.10 0.95 (0.83\u20131.08) 0.42NID1 rs10754833 C\/T \u22120.03 (\u22120.07\u20130.006) \u22123.33 0.10 0.83 (0.68\u20131.01) 0.06 0.90 (0.81\u20131.01) 0.08 0.94 (0.83\u20131.08) 0.40CASP8 rs6735656 a G\/T \u22120.02 (\u22120.06\u20130.03) \u22121.69 0.47 0.95 (0.76\u20131.19) 0.65 0.96 (0.85\u20131.09) 0.53 0.97 (0.83\u20131.13) 0.67CASP8 rs13016963 A\/G \u22120.01 (\u22120.05\u20130.03) \u22121.03 0.62 1.02 (0.84\u20131.25) 0.81 0.91 (0.81\u20131.02) 0.10 1.01 (0.88\u20131.16) 0.90TERT rs2242652 T\/C \u22120.04 (\u22120.09\u20130.02) \u22123.56 0.17 0.99 (0.77\u20131.27) 0.92 0.80 (0.69\u20130.92) 0.002 1.05 (0.89\u20131.25) 0.55TERT rs2853676 A\/G \u22120.02 (\u22120.06\u20130.03) \u22121.69 0.45 0.96 (0.77\u20131.19) 0.69 0.87 (0.77\u20130.98) 0.02 0.95 (0.82\u20131.10) 0.48TERT rs13356727 G\/A \u22120.03 (\u22120.07\u20130.007) \u22123.29 0.11 0.92 (0.76\u20131.12) 0.41 0.91 (0.82\u20131.02) 0.10 0.92 (0.81\u20131.06) 0.24TERT; CLPTM1L rs4975616 G\/A \u22120.03 (\u22120.07\u20130.01) \u22122.96 0.16 1.03 (0.84\u20131.27) 0.79 0.93 (0.83\u20131.04) 0.22 0.93 (0.81\u20131.07) 0.33TERT; CLPTM1L rs401681 T\/C \u22120.05 (\u22120.09 to\u22120.007) \u22124.64 0.02 0.94 (0.77\u20131.14) 0.51 0.88 (0.79\u20130.99) 0.03 0.98 (0.86\u20131.12) 0.80SLC45A2 rs16891982 C\/G 0.03 (\u22120.13\u20130.19) 2.93 0.72 1.12 (0.55\u20132.30) 0.76 0.73 (0.47\u20131.14) 0.16 0.63 (0.40\u20130.99) 0.05SLC45A2 rs35391 T\/C 0.08 (\u22120.12\u20130.28) 8.57 0.41 1.52 (0.66\u20133.52) 0.33 0.91 (0.53\u20131.57) 0.73 0.71 (0.39\u20131.29) 0.26SLC45A2 rs26722 T\/C 0.04 (\u22120.17\u20130.25) 3.76 0.73 1.28 (0.49\u20133.32) 0.61 0.86 (0.48\u20141.52) 0.60 0.84 (0.44\u20131.62) 0.61SLC45A2 rs13289 G\/C 0.03 (\u22120.01\u20130.07) 2.87 0.19 1.11 (0.90\u20131.35) 0.33 1.09 (0.97\u20131.22) 0.14 0.82 (0.72\u20130.94) 0.005IRF4 rs12203592 T\/C 0.08 (0.03\u20130.13) 8.14 0.002 1.23 (0.99\u20131.54) 0.07 1.17 (1.02\u20131.33) 0.02 0.92 (0.79\u20131.08) 0.31IRF4 rs872071 A\/G 0.008 (\u22120.03\u20130.05) 0.76 0.71 0.94 (0.77\u20131.14) 0.54 1.05 (0.94\u20131.17) 0.42 1.00 (0.87\u20131.14) 0.97Curr. Oncol. 2021, 28 4762Table 2. Cont.Tumor Prognostic CharacteristicsBreslow Thickness (n = 3207) Present vs. AbsentUlceration (n = 2617)Present vs. AbsentMitoses (n = 2625)Nonbrisk\/Brisk vs.Absent TIL grade(n = 2610)GeneNeighborhood SNP a\/APer allele mean change inlog of Breslow thickness(95% CI) 2Per allele changein Breslowthickness, % 3p Per allele OR(95% CI) 4 pPer allele OR(95% CI) 4 pPer allele OR(95% CI) 4 pTYRP1 rs1408799 T\/C 0.008 (\u22120.04\u20130.05) 0.85 0.71 1.19 (0.97\u20131.47) 0.09 1.09 (0.97\u20131.23) 0.15 1.05 (0.90\u20131.21) 0.54TYRP1 rs2733832 C\/T 0.02 (\u22120.02\u20130.06) 1.77 0.41 1.05 (0.86\u20131.28) 0.65 1.08 (0.97\u20131.22) 0.17 1.05 (0.91\u20131.20) 0.53MTAP rs2218220 T\/C 0.005 (\u22120.04\u20130.04) 0.48 0.82 0.97 (0.80\u20131.18) 0.79 1.01 (0.90\u20131.12) 0.92 1.15 (1.00\u20131.31) 0.04MTAP rs1335510 G\/T 0.003 (\u22120.04\u20130.04) 0.26 0.90 0.89 (0.73\u20131.09) 0.28 1.00 (0.89\u20131.12) 0.95 1.18 (1.03\u20131.35) 0.02MTAP rs7023329 G\/A 0.01 (\u22120.03\u20130.05) 1.22 0.55 0.98 (0.80\u20131.19) 0.82 0.98 (0.88\u20131.10) 0.74 1.10 (0.96\u20131.26) 0.16MTAP rs10811629 G\/A 0.006 (\u22120.03\u20130.05) 0.61 0.77 0.97 (0.80\u20131.19) 0.79 1.03 (0.92\u20131.15) 0.60 1.12 (0.98\u20131.28) 0.10CCND1 rs11604821 G\/A \u22120.06 (\u22120.11 to\u22120.02) \u22126.06 0.004 0.98 (0.79\u20131.21) 0.84 0.88 (0.78\u20130.99) 0.03 0.98 (0.85\u20131.12) 0.73CCND1 rs1485993 T\/C \u22120.07 (\u22120.11 to\u22120.03) \u22126.77 0.001 1.01 (0.83\u20131.24) 0.89 0.89 (0.79\u20131.00) 0.06 1.03 (0.89\u20131.18) 0.70CCND1 rs11263498 T\/C \u22120.06 (\u22120.10 to\u22120.02) \u22125.78 0.006 0.96 (0.78\u20131.19) 0.73 0.89 (0.79\u20131.00) 0.04 1.01 (0.88\u20131.16) 0.89TYR rs1042602 A\/C 0.008 (\u22120.03\u20130.05) 0.75 0.73 1.07 (0.87\u20131.32) 0.50 0.94 (0.84\u20131.06) 0.31 1.08 (0.94\u20131.25) 0.27TYR rs10765198 C\/T 0.01 (\u22120.03\u20130.06) 1.40 0.52 0.95 (0.77\u20131.17) 0.62 1.12 (1.00\u20131.26) 0.05 0.98 (0.85\u20131.12) 0.72TYR rs1847142 A\/G 0.01 (\u22120.03\u20130.05) 1.30 0.54 1.02 (0.84\u20131.25) 0.82 1.08 (0.97\u20131.21) 0.17 0.94 (0.82\u20131.08) 0.41TYR rs10830253 G\/T 0.01 (\u22120.03\u20130.05) 0.98 0.65 1.01 (0.82\u20131.24) 0.92 1.08 (0.96\u20131.21) 0.19 0.93 (0.81\u20131.07) 0.29ATM rs12278954 b A\/C 0.02 (\u22120.04\u20130.07) 1.59 0.59 1.04 (0.79\u20131.37) 0.76 0.92 (0.79\u20131.08) 0.31 0.99 (0.82\u20131.20) 0.94OCA2 rs1800407 A\/G 0.004 (\u22120.07\u20130.07) 0.41 0.91 0.99 (0.71\u20131.40) 0.97 0.92 (0.76\u20131.12) 0.42 0.88 (0.71\u20131.11) 0.28OCA2 rs1800401 T\/C \u22120.02 (\u22120.12\u20130.07) \u22122.37 0.61 1.06 (0.68\u20131.67) 0.80 1.08 (0.83\u20131.40) 0.56 1.23 (0.89\u20131.70) 0.22HERC2 rs1129038 G\/A 0.02 (\u22120.03\u20130.07) 2.29 0.37 1.15 (0.91\u20131.45) 0.26 0.97 (0.85\u20131.12) 0.72 0.93 (0.79\u20131.10) 0.39HERC2 rs12913832 A\/G 0.02 (\u22120.03\u20130.07) 2.03 0.42 1.12 (0.89\u20131.42) 0.34 0.96 (0.84\u20131.10) 0.60 0.95 (0.80\u20131.11) 0.51ASIP rs17305657 C\/T \u22120.03 (\u22120.10\u20130.03) \u22123.36 0.31 0.77 (0.54\u20131.10) 0.15 0.87 (0.72\u20131.05) 0.14 1.11 (0.89\u20131.39) 0.35Curr. Oncol. 2021, 28 4763Table 2. Cont.Tumor Prognostic CharacteristicsBreslow Thickness (n = 3207) Present vs. AbsentUlceration (n = 2617)Present vs. AbsentMitoses (n = 2625)Nonbrisk\/Brisk vs.Absent TIL grade(n = 2610)GeneNeighborhood SNP a\/APer allele mean change inlog of Breslow thickness(95% CI) 2Per allele changein Breslowthickness, % 3p Per allele OR(95% CI) 4 pPer allele OR(95% CI) 4 pPer allele OR(95% CI) 4 pASIP rs4911414 T\/G \u22120.02 (\u22120.06\u20130.02) \u22122.07 0.33 1.02 (0.83\u20131.25) 0.88 0.89 (0.80\u20131.01) 0.06 1.05 (0.92\u20131.21) 0.47PIGU rs910873 A\/G \u22120.02 (\u22120.09\u20130.04) \u22122.42 0.44 0.77 (0.56\u20131.07) 0.12 0.86 (0.72\u20131.03) 0.09 1.10 (0.89\u20131.36) 0.37PIGU rs17305573 C\/T \u22120.01 (\u22120.08\u20130.05) \u22121.26 0.71 0.74 (0.51\u20131.06) 0.10 0.86 (0.71\u20131.04) 0.11 1.05 (0.84\u20131.32) 0.65NCOA6 rs4911442 G\/A \u22120.01 (\u22120.07\u20130.04) \u22121.28 0.65 0.83 (0.62\u20131.11) 0.22 0.88 (0.75\u20131.03) 0.10 1.11 (0.92\u20131.35) 0.27MYH7B rs1885120 C\/G \u22120.04 (\u22120.11\u20130.02) \u22124.31 0.18 0.64 (0.44\u20130.92) 0.02 0.85 (0.71\u20131.02) 0.08 1.12 (0.90\u20131.4) 0.30LOC647979 rs1204552 A\/T \u22120.02 (\u22120.09\u20130.05) \u22121.77 0.63 0.93 (0.66\u20131.33) 0.71 0.91 (0.75\u20131.11) 0.35 1.05 (0.83\u20131.33) 0.68MX2 rs45430 G\/A \u22120.06 (\u22120.11 to\u22120.02) \u22126.14 0.004 0.90 (0.73\u20131.11) 0.34 0.87 (0.77\u20130.97) 0.02 1.12 (0.97\u20131.29) 0.13PLA2G6 rs6001027 G\/A 0.01 (\u22120.03\u20130.06) 1.35 0.54 0.87 (0.70\u20131.09) 0.23 0.93 (0.83\u20131.05) 0.25 0.94 (0.81\u20131.08) 0.39PLA2G6 rs132985 T\/C 0.01 (\u22120.03\u20130.05) 1.21 0.56 0.90 (0.74\u20131.10) 0.30 0.99 (0.89\u20131.11) 0.87 0.93 (0.82\u20131.07) 0.32PLA2G6 rs738322 G\/A 0.007 (\u22120.03\u20130.05) 0.75 0.72 0.94 (0.77\u20131.14) 0.51 1.00 (0.89\u20131.12) 1.00 0.93 (0.82\u20131.07) 0.31Abbreviations: SNP, single nucleotide polymorphism; GEM, Genes, Environment and Melanoma; TIL, tumor-infiltrating lymphocyte; Chr, chromosome; a, minor allele; A, major allele; CI, confidence interval;OR, odds ratio. Bold type indicates p values \u2264 0.05 (two-sided). 1 Limited to 3285 to individuals of European origin with incident invasive first- or higher-order primary melanoma who had their melanomascored for the histopathologic variable of interest (i.e., Breslow thickness, ulceration, mitoses, or TIL grade). 2 Adjusted for baseline features (age at diagnosis, sex, and study center) and status as first- orhigher-order primary. The mean changes and 95% CIs per minor allele are provided. 3 As the outcome (Breslow thickness) was log-transformed, the values here are presented as 100 \u00d7 (eestimated beta coefficient \u2212 1),which may be interpreted as the percentage change in the estimated mean of Breslow thickness per minor allele. 4 Adjusted for baseline features and status as first- or higher-order primary. The ORs and 95% CIsper minor allele are provided. a rs6735656 is a proxy for rs10931936 (r2 = 0.965). b rs12278954 is a proxy for rs1801516 (r2 =1.00).Curr. Oncol. 2021, 28 4764Table 3. Associations of melanoma-risk SNPs with melanoma-specific survival among patients in the GEM study 1.Total Censored Death as a Resultof Melanoma Melanoma-Specific SurvivalGeneNeighborhood SNP a\/A No. No. No. Per allele HR (95% CI)2 pARNT rs7412746 C\/T 2420 2262 158 1.02 (0.82\u20131.28) 0.84PARP1 rs3219090 A\/G 2387 2232 155 1.18 (0.94\u20131.50) 0.16PARP1 rs2695238 C\/G 2428 2267 161 1.07 (0.85\u20131.35) 0.58NID1 rs3768080 G\/A 2409 2251 158 0.82 (0.66\u20131.02) 0.08NID1 rs10754833 C\/T 2419 2260 159 0.83 (0.66\u20131.03) 0.09CASP8 rs6735656 a G\/T 2400 2244 156 0.94 (0.73\u20131.21) 0.64CASP8 rs13016963 A\/G 2423 2264 159 0.93 (0.75\u20131.17) 0.55TERT rs2242652 T\/C 2305 2153 152 0.96 (0.73\u20131.28) 0.80TERT rs2853676 A\/G 2420 2259 161 0.96 (0.76\u20131.22) 0.73TERT rs13356727 G\/A 2439 2279 160 0.94 (0.75\u20131.17) 0.59TERT; CLPTM1L rs4975616 G\/A 2343 2193 150 0.94 (0.75\u20131.19) 0.61TERT; CLPTM1L rs401681 T\/C 2408 2249 159 0.97 (0.77\u20131.21) 0.76SLC45A2 rs16891982 C\/G 2425 2265 160 1.29 (0.65\u20132.57) 0.46SLC45A2 rs35391 T\/C 2411 2254 157 0.75 (0.25\u20132.31) 0.62SLC45A2 rs26722 T\/C 2397 2239 158 1.36 (0.56\u20133.30) 0.49SLC45A2 rs13289 G\/C 2413 2252 161 0.82 (0.65\u20131.04) 0.10IRF4 rs12203592 T\/C 2425 2265 160 1.28 (1.00\u20131.65) 0.05IRF4 rs872071 A\/G 2406 2247 159 0.95 (0.76\u20131.18) 0.63TYRP1 rs1408799 T\/C 2401 2242 159 1.17 (0.93\u20131.46) 0.18TYRP1 rs2733832 C\/T 2405 2248 157 1.23 (0.98\u20131.53) 0.07MTAP rs2218220 T\/C 2419 2258 161 1.05 (0.84\u20131.30) 0.68MTAP rs1335510 G\/T 2404 2249 155 0.98 (0.78\u20131.23) 0.87MTAP rs7023329 G\/A 2401 2244 157 1.05 (0.84\u20131.30) 0.69MTAP rs10811629 G\/A 2414 2255 159 1.00 (0.80\u20131.25) 1.00CCND1 rs11604821 G\/A 2427 2269 158 1.02 (0.81\u20131.29) 0.86CCND1 rs1485993 T\/C 2410 2250 160 1.13 (0.90\u20131.42) 0.28CCND1 rs11263498 T\/C 2421 2263 158 1.12 (0.89\u20131.40) 0.35TYR rs1042602 A\/C 2429 2270 159 0.90 (0.71\u20131.14) 0.38TYR rs10765198 C\/T 2428 2270 158 0.90 (0.71\u20131.14) 0.37TYR rs1847142 A\/G 2424 2264 160 0.91 (0.73\u20131.15) 0.45TYR rs10830253 G\/T 2403 2247 156 0.92 (0.73\u20131.16) 0.48ATM rs12278954 b A\/C 2429 2268 161 1.37 (1.04\u20131.80) 0.03OCA2 rs1800407 A\/G 2429 2270 159 1.45 (1.02\u20132.04) 0.04OCA2 rs1800401 T\/C 2434 2273 161 0.65 (0.34\u20131.21) 0.17HERC2 rs1129038 G\/A 2409 2252 157 1.38 (1.07\u20131.77) 0.01HERC2 rs12913832 A\/G 2429 2268 161 1.38 (1.08\u20131.76) 0.01ASIP rs17305657 C\/T 2417 2257 160 0.98 (0.67\u20131.43) 0.92ASIP rs4911414 T\/G 2426 2265 161 0.83 (0.66\u20131.05) 0.12PIGU rs910873 A\/G 2431 2271 160 0.99 (0.70\u20131.41) 0.96PIGU rs17305573 C\/T 2143 2003 140 1.00 (0.68\u20131.47) 0.99NCOA6 rs4911442 G\/A 2399 2241 158 1.00 (0.73\u20131.38) 0.98MYH7B rs1885120 C\/G 2417 2259 158 0.95 (0.65\u20131.38) 0.79LOC647979 rs1204552 A\/T 2356 2202 154 1.09 (0.74\u20131.62) 0.67MX2 rs45430 G\/A 2421 2259 162 0.79 (0.62\u20130.99) 0.05PLA2G6 rs6001027 G\/A 2281 2133 148 1.17 (0.92\u20131.48) 0.20PLA2G6 rs132985 T\/C 2422 2263 159 1.07 (0.85\u20131.33) 0.57PLA2G6 rs738322 G\/A 2412 2254 158 1.14 (0.91\u20131.42) 0.25Abbreviations: SNP, single nucleotide polymorphism; GEM, Genes, Environment and Melanoma; Chr, chromosome; a, minor allele; A,major allele; CI, confidence interval; HR; hazard ratio. Bold type indicates p values \u2264 0.05 (two-sided). 1 Limited to 2458 individualsof European origin with incident invasive first-order primary melanoma. 2 Adjusted for baseline features (age at diagnosis, sex, andstudy center) and a time-dependent covariate. The HRs and 95% CIs per minor allele are provided. a rs6735656 is a proxy for rs10931936(r2 = 0.965). b rs12278954 is a proxy for rs1801516 (r2 = 1.00).4. DiscussionOur results indicate that many of these 47 melanoma-risk SNPs are not significantlyassociated with tumor prognostic characteristics or melanoma-specific survival whenconsidering false discovery. Similarly, Mangantig et al., in a GWAS meta-analysis, found nosignificant associations with log of Breslow thickness for the ARNT, PARP1, NID1, TERT,SLC45A2, MTAP, TYR, OCA2, HERC2, ASIP, PIGU, or PLA2G6 variants we studied [47].Mangantig et al. also found no significant association with log of Breslow thickness forCurr. Oncol. 2021, 28 4765CCND1 rs11263498 [47], while this SNP was nominally associated with log of Breslowthickness in GEM.Consistent with GEM, Mangantig et al. found IRF4 rs12203592*T was positively asso-ciated with increased log of Breslow thickness, although not reaching genome-wide signif-icance [47]. Similarly consistent with GEM, Potrony et al. found that IRF4 rs12203592*Tincreased the risk of dying from melanoma in patients from two European hospitals [48].The IRF4 rs12203592*T allele was the melanoma-risk allele in two US studies [22,23], whileit was protective in a Spanish population [20] as well as a combined analysis of Australian,UK, and Swedish subjects [21]. Here, we report the overall positive associations of IRF4rs12203592*T with increased log of Breslow thickness, presence of mitoses, and worsemelanoma-specific survival, along with a borderline association with presence of ulcer-ation. IRF4 is a transcription factor required for the maturation of B and T cells and forthe differentiation of B lymphocytes into plasma cells [49]. In immune cells, the IRF4rs12203592*T allele increases IRF4 expression, which upregulates telomerase activity byactivating TERT transcription [50\u201352]. Furthermore, it has been suggested that increasedIRF4 expression in immune cells increases the ability of regulatory T cells to suppress TH2responses [53], which may accelerate tumor growth. However, it has also been shown thatIRF4 overexpression in myeloid-derived suppressor cells induces a decreased suppressiveeffect on CD8+ T cell proliferation, resulting in less rapid tumor progression [54,55].The melanoma-risk CCND1 rs1485993*T allele [5] was positively associated with de-creased Breslow thickness, passing false discovery, and borderline associated with absenceof mitoses. The melanoma-risk alleles of other SNPs in the CCND1 gene neighborhood(rs11604821*G and rs11263498*T) [5] were nominally associated with both decreased Bres-low thickness and absence of mitoses. These results are plausible based on CCND1\u2032simpact on cell proliferation [56]. CCND1 is a cyclin that associates with CDK4 or CDK6to inactivate the cell cycle inhibiting the function of the retinoblastoma protein (pRB),which promotes progression through the G1-S phase of the cell cycle [56,57]. It is inter-esting that the melanoma-risk alleles were associated with decreased Breslow thicknessand absence of mitoses. This indicates that while these variants are related to increasedmelanoma susceptibility, they may also be associated with decreased tumor aggressiv-ity. A recent meta-analysis investigating the associations of CCND1 and cyclin proteinD1 with melanoma prognostic factors found that upregulation of CCND1\/cyclin D1 wasassociated with the presence of ulceration and mitoses, while the associations with Breslowthickness and survival conflicted across studies [58]. However, the associations of CCND1rs1485993*T, CCND1 rs11604821*G, and CCND1 rs11263498*T with CCND1 expressionremain unknown, and thus, we are unable to establish whether our results are consistentwith the prior studies evaluating prognostic factors in the context of CCND1 expression.The melanoma-risk TERT rs2242652*T allele [24] was positively associated with ab-sence of mitoses, passing false discovery. The melanoma-risk TERT rs2853676*A allele [24]was also nominally associated with absence of mitoses, and the melanoma-risk rs401681*Tallele [5,24,59,60] was nominally associated with decreased log of Breslow thickness andabsence of mitoses. These results are reasonable based on TERT\u2019s regulation of telom-erase activity [61]. Again, it is notable that the melanoma-risk alleles were associatedwith decreased Breslow thickness and\/or absence of mitoses. Activating TERT promotermutations result in increased gene expression and have been associated with increasedBreslow thickness and the presence of ulceration and mitoses in melanoma patients [62\u201366].Other studies have not found associations between TERT promoter mutations and Breslowthickness, ulceration, or mitotic rate [67\u201369]. However, similarly to CCND1, the associa-tions of our genotypes with TERT expression remain unknown, and thus, we are unable toestablish whether our results are consistent with these prior studies.Also noteworthy are the results that the melanoma-risk MX2 rs45430*A allele [5]was positively associated with increased Breslow thickness, presence of mitoses, andworse melanoma-specific survival in GEM. MX2 is a dynamin-like GTPase that is aninterferon-induced inhibitor of HIV-1 and other primate lentiviruses [70]. Impairing MX2Curr. Oncol. 2021, 28 4766function also leads to a delay in progression through the G1-S phase of the cell cycle [71].Although Mangantig et al. found no association of MX2 rs45430 with Breslow thickness [47],other studies indicate MX2 may influence melanoma progression [72,73]. MX2 rs45430is in linkage disequilibrium with MX2 rs398206 (D\u2019 = 0.98 in the CEU population), andMX2 rs45430*A is strongly positively correlated with MX2 rs398206*A [74]. Choi et al.identified MX2 rs398206 as a functional intronic variant that mediates Yingyang-1 (YY1)binding to increase MX2 levels, with MX2 rs398206*A driving significantly higher luciferaseexpression compared to the C allele [72]. They further found that melanocyte-specificexpression of human MX2 in a zebrafish model accelerated melanoma formation in aBRAFV600E background. Juraleviciute et al. found that primary melanomas homozygousfor MX2 rs45430*A had higher MX2 expression [73]. Interestingly, these authors found theeffects of MX2 expression on melanoma proliferation were context-dependent, with highexpression in primary melanoma cell lines and melanocytes suppressing tumorigenesis,while downregulation in a subset of melanoma cell lines reduced proliferation. Thesedifferential effects in melanoma subsets may obscure associations in epidemiologic studies.Juraleviciute et al. also reported that MX2 expression was significantly higher in tumorswith TILs compared to tumors that had no TILs [73]. Here, we found no significantassociation with TILs for MX2 rs45430.Our study\u2019s strengths are its international population-based design, large samplesize, standardized pathology review, melanoma-specific survival, and comparatively longfollow-up period ending before approvals of new systemic agents, checkpoint inhibitors,and targeted therapies that alter the natural course of the disease and improve over-all survival [75]. Future studies examining melanoma-specific survival will likely beconfounded by these new therapies. A limitation could be insufficient power to detectassociations of SNPs with lower minor allele frequencies (e.g., SLC45A2 rs16891982, MAF0.017). Another limitation is that our study only included participants with cutaneousmelanoma, not mucosal [76,77] or uveal melanomas [78\u201380], which seemingly have differ-ent genetic landscapes.5. ConclusionsOur findings indicate that few melanoma-risk variants are associated with tumorprognostic characteristics (Breslow thickness, presence of ulceration, presence of mitoses,or presence of TILs) or survival. However, further research investigating the associationsof IRF4 rs12203592, CCND1 rs1485993, TERT rs2242652, and MX2 rs45430 with underlyingbiologic pathways related to tumor progression is warranted. Future studies of largerdatasets that include subset analyses may help elucidate the relationship of melanoma-riskvariants with tumor characteristics and survival.Supplementary Materials: The following are available online at https:\/\/www.mdpi.com\/article\/10.3390\/curroncol28060401\/s1, Table S1: Genotype locations, minor\/major alleles, minor allelefrequencies, numbers of samples genotyped in the GEM study, and references for the association of thegenotypes with melanoma; Table S2: Number of GEM participants successfully genotyped for eachSNP and distribution of these participants by prognostic characteristics of primary melanoma tumor.Author Contributions: Conceptualization: D.R.D. and N.E.T.; data curation: I.O., P.A.K., L.L., K.J.B.,A.S., A.K., A.E.C., H.A.-C., S.B.G., R.P.G., R.Z., S.R., L.S., T.D., D.W.O., C.B.B., M.B. and N.E.T.;formal analysis: D.R.D. and N.E.T.; funding acquisition: I.O., A.E.C., H.A.-C., C.B.B., M.B. and N.E.T.;investigation: D.R.D. and N.E.T.; methodology: D.R.D., I.O. and N.E.T.; project administration: N.E.T.;resources: I.O.; software: L.L. and N.E.T.; supervision: N.E.T.; validation: I.O., P.A.K., C.B.B., M.B. andN.E.T.; visualization: D.R.D. and N.E.T.; writing\u2014original draft: D.R.D. and N.E.T.; writing\u2014reviewand editing: I.O., P.A.K., L.L., K.J.B., A.S., A.K., A.E.C., H.A.-C., S.B.G., R.P.G., R.Z., S.R., L.S., T.D.,D.C.G., D.W.O., C.B.B., M.B. and N.E.T. All authors have read and agreed to the published version ofthe manuscript.Funding: This work was supported by the National Cancer Institute (R01CA233524 to N.E. Thomas,M. Berwick, C.B. Begg, and H. Anton-Culver; P01CA206980 to N.E. Thomas and M. Berwick;R01CA112243 to N.E. Thomas; U01CA83180 and R01CA112524 to M. Berwick; R01CA098438 to C.B.Curr. Oncol. 2021, 28 4767Begg; R03CA125829 and R03CA173806 to I. Orlow; P30CA016086 to the University of North Carolina;and P30CA008748 to Memorial Sloan Kettering). A.E. Cust was supported by a NHMRC CareerDevelopment Fellowship.Institutional Review Board Statement: The study was conducted according to the guidelines of theDeclaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of theUniversity of New Mexico (protocol code CR00006961 and date of approval 24 January 2021).Informed Consent Statement: The Genes, Environment, and Melanoma (GEM) Study obtainedwritten informed consent from all participants involved in the study. This manuscript does notpresent identifying information for any participant and instead provides summary statistics.Data Availability Statement: Data can be requested from Nancy E. Thomas or Marianne Berwickafter review by the GEM Steering Committee.Acknowledgments: GEM Study Group: Coordinating Center, Memorial Sloan Kettering CancerCenter, New York, NY (USA): Marianne Berwick, (PI, currently at the University of New Mex-ico, Albuquerque, NM), Colin Begg, (Co-PI), Irene Orlow, (Co-investigator), Klaus J. Busam, (Der-matopathologist), Isidora Autuori (Research Assistant), Audrey Mauguen, (Biostatistician). GermlineDNA handling, and genotyping design and testing for this study specifically were completed byPampa Roy (Senior Laboratory Technician), Sarah Yoo, (Senior Laboratory Technician), Ajay Sharma,(Senior Laboratory Technician), and Jaipreet Rayar, (Senior Laboratory Technician). University ofNew Mexico, Albuquerque, NM: Marianne Berwick, (PI), Li Luo, (Biostatistician), Tawny W. Boyce,(Data Manager). Study Centers: The University of Sydney and The Cancer Council New South Wales,Sydney, Australia: Anne E. Cust, (PI), Bruce K. Armstrong, (former PI), Anne Kricker, (former co-PI);Menzies Institute for Medical Research University of Tasmania, Hobart, Australia: Alison Venn,(current PI), Terence Dwyer, (PI, currently at University of Oxford, United Kingdom), Paul Tucker(Dermatopathologist); BC Cancer Research Centre, Vancouver, Canada: Richard P. Gallagher, (PI);Cancer Care Ontario, Toronto, Canada: Loraine D. Marrett, (PI), Lynn From, (Dermatopathologist);CPO, Center for Cancer Prevention, Torino, Italy: Roberto Zanetti, (PI), Stefano Rosso, (co-PI), LidiaSacchetto, (Biostatistician); University of California, Irvine, CA: Hoda Anton-Culver, (PI); Universityof Michigan, Ann Arbor, MI: Stephen B. Gruber, (PI, currently at City of Hope National Medical Cen-ter, Duarte, CA), Shu-Chen Huang, (co-Investigator, joint at USC-University of Michigan); Universityof North Carolina, Chapel Hill, NC: Nancy E. Thomas, (PI), Kathleen Conway, (co-Investigator),David W. Ollila, (co-Investigator), Paul B. Googe, (Dermatopathologist), Sharon N. Edmiston, (Re-search Analyst), Honglin Hao (Laboratory Specialist), Eloise Parrish, (Laboratory Specialist), Sara E.Stevens, (Research Assistant), David C. Gibbs, (Research Assistant, currently at Emory University,Atlanta, GA); University of Pennsylvania, Philadelphia, PA: Timothy R. Rebbeck, (former PI), PeterA. Kanetsky, (PI, currently at H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL); UVdata consultants: Julia Lee Taylor, and Sasha Madronich, National Centre for Atmospheric Research,Boulder, CO.Conflicts of Interest: K. Busam has received minor royalties from editing a textbook with Elsevier.S.B. Gruber is the Co-Founder of Brogent International LLC. L. Sacchetto works as a biomarkerstatistician for Bayer AG. The remaining authors state no conflict of interest.References1. Law, M.H.; Macgregor, S.; Hayward, N.K. Melanoma genetics: Recent findings take us beyond well-traveled pathways. J. 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