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Identification of Susceptibility Loci for Cutaneous Squamous Cell Carcinoma

Open ArchivePublished:January 29, 2016DOI:https://doi.org/10.1016/j.jid.2016.01.013
      We report a genome-wide association study of cutaneous squamous cell carcinoma conducted among non-Hispanic white members of the Kaiser Permanente Northern California health care system. The study includes a genome-wide screen of 61,457 members (6,891 cases and 54,566 controls) genotyped on the Affymetrix Axiom European array and a replication phase involving an independent set of 6,410 additional members (810 cases and 5,600 controls). Combined analysis of screening and replication phases identified 10 loci containing single-nucleotide polymorphisms (SNPs) with P-values < 5 × 10−8. Six loci contain genes in the pigmentation pathway; SNPs at these loci appear to modulate squamous cell carcinoma risk independently of the pigmentation phenotypes. Another locus contains HLA class II genes studied in relation to elevated squamous cell carcinoma risk following immunosuppression. SNPs at the remaining three loci include an intronic SNP in FOXP1 at locus 3p13, an intergenic SNP at 3q28 near TP63, and an intergenic SNP at 9p22 near BNC2. These findings provide insights into the genetic factors accounting for inherited squamous cell carcinoma susceptibility.

      Abbreviations:

      BCC (basal cell carcinoma), CMM (cutaneous malignant melanoma), GWAS (genome-wide association study), LD (linkage disequilibrium), NHW (non-Hispanic white), NMSC (nonmelanoma skin cancer), OCA (oculocutaneous albinism), ORs (odds ratios), RPGEH (Research Program on Genes, Environment, and Health), SCC (squamous cell carcinoma), SNPs (single-nucleotide polymorphisms)

      Introduction

      Squamous cell carcinoma (SCC) is among the most common and costly malignancies in populations of European ancestry (
      • Housman T.S.
      • Feldman S.R.
      • Williford P.M.
      • Fleischer Jr., A.B.
      • Goldman N.D.
      • Acostamadiedo J.M.
      • et al.
      Skin cancer is among the most costly of all cancers to treat for the Medicare population.
      ). Its primary cause is ultraviolet radiation exposure, which causes DNA damage in keratinocytes (
      • Dessinioti C.
      • Tzannis K.
      • Sypsa V.
      • Nikolaou V.
      • Kypreou K.
      • Antoniou C.
      • et al.
      Epidemiologic risk factors of basal cell carcinoma development and age at onset in a Southern European population from Greece.
      ,
      • Roewert-Huber J.
      • Lange-Asschenfeldt B.
      • Stockfleth E.
      • Kerl H.
      Epidemiology and aetiology of basal cell carcinoma.
      ), for which melanin provides a protective filter. An inherited basis for SCC risk is supported by the increased risk among first-degree relatives of SCC cases (
      • Hemminki K.
      • Zhang H.
      • Czene K.
      Familial invasive and in situ squamous cell carcinoma of the skin.
      ,
      • Hussain S.K.
      • Sundquist J.
      • Hemminki K.
      The effect of having an affected parent or sibling on invasive and in situ skin cancer risk in Sweden.
      ), but the specific genetic factors that determine susceptibility are not well understood. Although genome-wide association studies (GWASs) have identified susceptibility loci for other skin cancers, for example, cutaneous malignant melanoma (CMM) (
      • Barrett J.H.
      • Iles M.M.
      • Harland M.
      • Taylor J.C.
      • Aitken J.F.
      • Andresen P.A.
      • et al.
      Genome-wide association study identifies three new melanoma susceptibility loci.
      ,
      • Bishop D.T.
      • Demenais F.
      • Iles M.M.
      • Harland M.
      • Taylor J.C.
      • Corda E.
      • et al.
      Genome-wide association study identifies three loci associated with melanoma risk.
      ), basal cell carcinoma (BCC) (
      • Nan H.
      • Xu M.
      • Kraft P.
      • Qureshi A.A.
      • Chen C.
      • Guo Q.
      • et al.
      Genome-wide association study identifies novel alleles associated with risk of cutaneous basal cell carcinoma and squamous cell carcinoma.
      ,
      • Stacey S.N.
      • Gudbjartsson D.F.
      • Sulem P.
      • Bergthorsson J.T.
      • Kumar R.
      • Thorleifsson G.
      • et al.
      Common variants on 1p36 and 1q42 are associated with cutaneous basal cell carcinoma but not with melanoma or pigmentation traits.
      ), and BCC and SCC combined as nonmelanoma skin cancer (NMSC) (
      • Stacey S.N.
      • Sulem P.
      • Masson G.
      • Gudjonsson S.A.
      • Thorleifsson G.
      • Jakobsdottir M.
      • et al.
      New common variants affecting susceptibility to basal cell carcinoma.
      ), we are unaware of previous GWASs focused solely on SCC. Although the GWAS of NMSC investigated the single-nucleotide polymorphisms (SNPs) identified in the combined analysis for their individual effects on BCC and SCC, the power to detect SNPs specifically related to SCC was limited by the number of SCC cases. We describe an internally validated GWAS based on data from 67,867 non-Hispanic white (NHW) individuals (7,701 SCC cases and 60,166 controls) enrolled in the Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH).

      Results

      We identified 10 loci containing SNPs with combined P-values meeting the genome-wide threshold of 5 × 10−8 (
      • Pe'er I.
      • Yelensky R.
      • Altshuler D.
      • Daly M.J.
      Estimation of the multiple testing burden for genomewide association studies of nearly all common variants.
      ) (Figure 1). Table 1 shows per-allele odds ratios (ORs) and P-values for the screening phase, replication phase, and combined data for the most significant SNPs at these 10 loci. Six of the 10 loci encompass genes that play established roles in the pigmentation pathway (
      • Scherer D.
      • Kumar R.
      Genetics of pigmentation in skin cancer—a review.
      ); SNPs at these loci have been associated with skin cancers and/or pigment-related phenotypes such as eye, hair or skin color, tanning, burning, or freckles (
      • Gerstenblith M.R.
      • Shi J.
      • Landi M.T.
      Genome-wide association studies of pigmentation and skin cancer: a review and meta-analysis.
      ).
      Figure 1
      Figure 1Manhattan plot showing –log10 P-values of squared Cochran-Armitage trend statistics. The horizontal line represents the threshold P-value of 5 × 10−8. Markers within 50 kb of SNPs with P-values < 5 × 10−8 are indicated with black asterisks for those in pigment-related regions and in red triangles for those in other regions. The y-axis is truncated at P = 10−30, although three SNPs at the 6p25 locus have P-values between 10−30 and 10−97, and 72 SNPs at the 16q24 locus have P-values between 10−30 and 10−44. SNPs, single-nucleotide polymorphisms.
      Table 1Genome-wide association and replication for 10 SCC loci
      Regions containing SNPs with combined P-values < 5 × 10−8.
      LocusSNP
      SNP with strongest combined P-value in the region.
      GeneMinor alleleMAF
      MAF = minor allele frequency among control subjects.
      Info
      For imputed data, the info is the IMPUTE-2 information measure for imputation accuracy (Marchini and Howie, 2010).
      Initial screenReplication phaseCombined
      OR
      OR = odds ratio per minor allele, CI = 95% confidence interval.
      CI
      OR = odds ratio per minor allele, CI = 95% confidence interval.
      P-value
      Based on the squared Cochran-Armitage trend test.
      ORCIP-valueORCIP-value
      A. Pigment-related loci
      Chr 5p13rs16891982SLC45A2C0.45Typed0.530.47–0.601.64 × 10−240.480.34–0.682.88 × 10−50.520.47–0.592.77 × 10−28
      Chr 6p25rs12203592IRF4T0.171.001.541.48–1.612.45 × 10−831.711.49–1.955.95 × 10−151.561.49–1.628.29 × 10−97
      Chr 11q14rs1126809TYRA0.281.001.191.16–1.251.20× 10−201.080.96–1.222.09 × 10−11.191.15–1.242.18× 10−20
      Chr 15q13rs12916300HERC2C0.261.000.890.85–0.931.84 × 10−70.820.72–0.932.40 × 10−30.880.85–0.923.30 × 10−9
      Chr 16q24rs4268748DEF8C0.260.851.341.28–1.403.24 × 10−411.281.13–1.457.85 × 10−51.331.28–1.391.75 × 10−44
      Chr 20q11rs6059655RALYA0.080.991.301.22–1.385.18 × 10−171.491.25–1.781.14 × 10−51.321.24–1.399.03 × 10−21
      B. Other loci
      Chr 3p13rs62246017FOXP1A0.330.941.121.08–1.161.70 × 10−81.070.95–1.20.26 × 10−11.111.07–1.161.16 × 10−8
      Chr 3q28rs6791479TPRG1/TP63
      Two flanking genes of an intergenic SNP.
      T0.431.001.121.08–1.162.57 × 10−91.211.09–1.355.03 × 10−41.131.09–1.161.47 × 10−11
      Chr 6p21rs4455710HLA-DQA1T0.381.001.171.12–1.211.80 × 10−161.181.06–1.322.28 × 10−31.171.13–1.211.86 × 10−18
      Chr 9p22rs74664507BNC2/CNTLN
      Two flanking genes of an intergenic SNP.
      T0.440.950.900.87–0.933.64 × 10−80.910.81–1.018.69 × 10−20.900.87–0.938.24 × 10−9
      Abbreviations: SCC, squamous cell carcinoma; SNP, single-nucleotide polymorphisms.
      1 Regions containing SNPs with combined P-values < 5 × 10−8.
      2 SNP with strongest combined P-value in the region.
      3 MAF = minor allele frequency among control subjects.
      4 For imputed data, the info is the IMPUTE-2 information measure for imputation accuracy (
      • Marchini J.
      • Howie B.
      Genotype imputation for genome-wide association studies.
      ).
      5 OR = odds ratio per minor allele, CI = 95% confidence interval.
      6 Based on the squared Cochran-Armitage trend test.
      7 Two flanking genes of an intergenic SNP.

      Pigmentation loci

      The first three pigment-related SNPs in Table 1 (section A) have been associated previously with SCC, BCC, and CMM. SNP rs16891982 at locus 5p13, a nonsynonymous SNP (Phe374Leu) in SLC45A2, has been associated with SCC (
      • Stacey S.N.
      • Sulem P.
      • Masson G.
      • Gudjonsson S.A.
      • Thorleifsson G.
      • Jakobsdottir M.
      • et al.
      New common variants affecting susceptibility to basal cell carcinoma.
      ), BCC (
      • Stacey S.N.
      • Sulem P.
      • Masson G.
      • Gudjonsson S.A.
      • Thorleifsson G.
      • Jakobsdottir M.
      • et al.
      New common variants affecting susceptibility to basal cell carcinoma.
      ), and CMM (
      • Barrett J.H.
      • Iles M.M.
      • Harland M.
      • Taylor J.C.
      • Aitken J.F.
      • Andresen P.A.
      • et al.
      Genome-wide association study identifies three new melanoma susceptibility loci.
      ,
      • Duffy D.L.
      • Zhao Z.Z.
      • Sturm R.A.
      • Hayward N.K.
      • Martin N.G.
      • Montgomery G.W.
      Multiple pigmentation gene polymorphisms account for a substantial proportion of risk of cutaneous malignant melanoma.
      ,
      • Fernandez L.P.
      • Milne R.L.
      • Pita G.
      • Aviles J.A.
      • Lazaro P.
      • Benitez J.
      • et al.
      SLC45A2: a novel malignant melanoma-associated gene.
      ,
      • Guedj M.
      • Bourillon A.
      • Combadieres C.
      • Rodero M.
      • Dieude P.
      • Descamps V.
      • et al.
      Variants of the MATP/SLC45A2 gene are protective for melanoma in the French population.
      ,
      • Ibarrola-Villava M.
      • Hu H.H.
      • Guedj M.
      • Fernandez L.P.
      • Descamps V.
      • Basset-Seguin N.
      • et al.
      MC1R, SLC45A2 and TYR genetic variants involved in melanoma susceptibility in southern European populations: results from a meta-analysis.
      ,
      • Kosiniak-Kamysz A.
      • Marczakiewicz-Lustig A.
      • Marcinska M.
      • Skowron M.
      • Wojas-Pelc A.
      • Pospiech E.
      • et al.
      Increased risk of developing cutaneous malignant melanoma is associated with variation in pigmentation genes and VDR, and may involve epistatic effects.
      ,
      • Stacey S.N.
      • Sulem P.
      • Masson G.
      • Gudjonsson S.A.
      • Thorleifsson G.
      • Jakobsdottir M.
      • et al.
      New common variants affecting susceptibility to basal cell carcinoma.
      ) as well as eye, hair, and skin color (
      • Branicki W.
      • Brudnik U.
      • Wojas-Pelc A.
      Interactions between HERC2, OCA2 and MC1R may influence human pigmentation phenotype.
      ,
      • Duffy D.L.
      • Zhao Z.Z.
      • Sturm R.A.
      • Hayward N.K.
      • Martin N.G.
      • Montgomery G.W.
      Multiple pigmentation gene polymorphisms account for a substantial proportion of risk of cutaneous malignant melanoma.
      ,
      • Eriksson N.
      • Macpherson J.M.
      • Tung J.Y.
      • Hon L.S.
      • Naughton B.
      • Saxonov S.
      • et al.
      Web-based, participant-driven studies yield novel genetic associations for common traits.
      ,
      • Liu F.
      • Visser M.
      • Duffy D.L.
      • Hysi P.G.
      • Jacobs L.C.
      • Lao O.
      • et al.
      Genetics of skin color variation in Europeans: genome-wide association studies with functional follow-up.
      ,
      • Soejima M.
      • Koda Y.
      Population differences of two coding SNPs in pigmentation-related genes SLC24A5 and SLC45A2.
      ,
      • Stokowski R.P.
      • Pant P.V.
      • Dadd T.
      • Fereday A.
      • Hinds D.A.
      • Jarman C.
      • et al.
      A genomewide association study of skin pigmentation in a South Asian population.
      ). SLC45A2 encodes a membrane-associated transporter enzyme, and loss of SLC45A2 activity has been found to disrupt post-Golgi-level trafficking of tyrosinase to the melanosomes (
      • Newton R.A.
      • Cook A.L.
      • Roberts D.W.
      • Leonard J.H.
      • Sturm R.A.
      Post-transcriptional regulation of melanin biosynthetic enzymes by cAMP and resveratrol in human melanocytes.
      ) where melanin is synthesized and stored. Mutations in SLC45A2 cause type four oculocutaneous albinism (OCA) syndrome, which is characterized by failure to synthesize melanin (
      • Simeonov D.R.
      • Wang X.
      • Wang C.
      • Sergeev Y.
      • Dolinska M.
      • Bower M.
      • et al.
      DNA variations in oculocutaneous albinism: an updated mutation list and current outstanding issues in molecular diagnostics.
      ). SNP rs12203592 at locus 6p25, an intronic SNP in IRF4, has been associated with SCC, BCC, and CMM (
      • Barrett J.H.
      • Iles M.M.
      • Harland M.
      • Taylor J.C.
      • Aitken J.F.
      • Andresen P.A.
      • et al.
      Genome-wide association study identifies three new melanoma susceptibility loci.
      ,
      • Duffy D.L.
      • Iles M.M.
      • Glass D.
      • Zhu G.
      • Barrett J.H.
      • Hoiom V.
      • et al.
      IRF4 variants have age-specific effects on nevus count and predispose to melanoma.
      ,
      • Han J.
      • Qureshi A.A.
      • Nan H.
      • Zhang J.
      • Song Y.
      • Guo Q.
      • et al.
      A germline variant in the interferon regulatory factor 4 gene as a novel skin cancer risk locus.
      ,
      • Stefanaki I.
      • Panagiotou O.A.
      • Kodela E.
      • Gogas H.
      • Kypreou K.P.
      • Chatzinasiou F.
      • et al.
      Replication and predictive value of SNPs associated with melanoma and pigmentation traits in a Southern European case-control study.
      ,
      • Zhang M.
      • Song F.
      • Liang L.
      • Nan H.
      • Zhang J.
      • Liu H.
      • et al.
      Genome-wide association studies identify several new loci associated with pigmentation traits and skin cancer risk in European Americans.
      ), and with pigmentation phenotypes (
      • Duffy D.L.
      • Zhao Z.Z.
      • Sturm R.A.
      • Hayward N.K.
      • Martin N.G.
      • Montgomery G.W.
      Multiple pigmentation gene polymorphisms account for a substantial proportion of risk of cutaneous malignant melanoma.
      ,
      • Han J.
      • Kraft P.
      • Nan H.
      • Guo Q.
      • Chen C.
      • Qureshi A.
      • et al.
      A genome-wide association study identifies novel alleles associated with hair color and skin pigmentation.
      ,
      • Jacobs L.C.
      • Hamer M.A.
      • Gunn D.A.
      • Deelen J.
      • Lall J.S.
      • van Heemst D.
      • et al.
      A genome-wide association study identifies the skin color genes IRF4, MC1R, ASIP, and BNC2 influencing facial pigmented spots.
      ,
      • Nan H.
      • Kraft P.
      • Hunter D.J.
      • Han J.
      Genetic variants in pigmentation genes, pigmentary phenotypes, and risk of skin cancer in Caucasians.
      ,
      • Soejima M.
      • Koda Y.
      Population differences of two coding SNPs in pigmentation-related genes SLC24A5 and SLC45A2.
      ,
      • Sulem P.
      • Gudbjartsson D.F.
      • Stacey S.N.
      • Helgason A.
      • Rafnar T.
      • Magnusson K.P.
      • et al.
      Genetic determinants of hair, eye and skin pigmentation in Europeans.
      ,
      • Visser M.
      • Palstra R.J.
      • Kayser M.
      Allele-specific transcriptional regulation of IRF4 in melanocytes is mediated by chromatin looping of the intronic rs12203592 enhancer to the IRF4 promoter.
      ). The T allele of this SNP reduces expression of IRF4 (
      • Praetorius C.
      • Grill C.
      • Stacey S.N.
      • Metcalf A.M.
      • Gorkin D.U.
      • Robinson K.C.
      • et al.
      A polymorphism in IRF4 affects human pigmentation through a tyrosinase-dependent MITF/TFAP2A pathway.
      ), which encodes a transcription factor that, in cooperation with MITF, activates expression of TYR and is used by melanocytes to produce and store melanin. SNP rs1126809 at locus 11q14 is a nonsynonymous SNP (Arg402Gln) in TYR, which encodes the enzyme tyrosinase that catalyzes multiple steps in the conversion of tyrosine to melanin. SNP rs1126809 has been associated with SCC (
      • Nan H.
      • Xu M.
      • Kraft P.
      • Qureshi A.A.
      • Chen C.
      • Guo Q.
      • et al.
      Genome-wide association study identifies novel alleles associated with risk of cutaneous basal cell carcinoma and squamous cell carcinoma.
      ), BCC (
      • Nan H.
      • Xu M.
      • Kraft P.
      • Qureshi A.A.
      • Chen C.
      • Guo Q.
      • et al.
      Genome-wide association study identifies novel alleles associated with risk of cutaneous basal cell carcinoma and squamous cell carcinoma.
      ), and CMM (
      • Bishop D.T.
      • Demenais F.
      • Iles M.M.
      • Harland M.
      • Taylor J.C.
      • Corda E.
      • et al.
      Genome-wide association study identifies three loci associated with melanoma risk.
      ,
      • Duffy D.L.
      • Zhao Z.Z.
      • Sturm R.A.
      • Hayward N.K.
      • Martin N.G.
      • Montgomery G.W.
      Multiple pigmentation gene polymorphisms account for a substantial proportion of risk of cutaneous malignant melanoma.
      ,
      • Gudbjartsson D.F.
      • Sulem P.
      • Stacey S.N.
      • Goldstein A.M.
      • Rafnar T.
      • Sigurgeirsson B.
      • et al.
      ASIP and TYR pigmentation variants associate with cutaneous melanoma and basal cell carcinoma.
      ,
      • Hu H.H.
      • Guedj M.
      • Descamps V.
      • Jouary T.
      • Bourillon A.
      • Ezzedine K.
      • et al.
      Assessment of tyrosinase variants and skin cancer risk in a large cohort of French subjects.
      ,
      • Ibarrola-Villava M.
      • Hu H.H.
      • Guedj M.
      • Fernandez L.P.
      • Descamps V.
      • Basset-Seguin N.
      • et al.
      MC1R, SLC45A2 and TYR genetic variants involved in melanoma susceptibility in southern European populations: results from a meta-analysis.
      ,
      • Nan H.
      • Xu M.
      • Kraft P.
      • Qureshi A.A.
      • Chen C.
      • Guo Q.
      • et al.
      Genome-wide association study identifies novel alleles associated with risk of cutaneous basal cell carcinoma and squamous cell carcinoma.
      ).
      The remaining three SNPs in Table 1 (section A) lie near genes that play established roles in the pigmentation pathway and that have been associated with pigmentation traits and/or skin cancer risk. However, the relationships of these SNPs to SCC risk are uncertain. For example, SNP rs12916300 at 15q13 (Supplementary Figure S1 online) lies within intron 68 of HERC2, which encodes a ubiquitin-protein ligase recruited to sites of DNA damage from ionizing radiation, and which has been associated with BCC (
      • Han J.
      • Qureshi A.A.
      • Nan H.
      • Zhang J.
      • Song Y.
      • Guo Q.
      • et al.
      A germline variant in the interferon regulatory factor 4 gene as a novel skin cancer risk locus.
      ) and pigmentation phenotypes (
      • Eiberg H.
      • Troelsen J.
      • Nielsen M.
      • Mikkelsen A.
      • Mengel-From J.
      • Kjaer K.W.
      • et al.
      Blue eye color in humans may be caused by a perfectly associated founder mutation in a regulatory element located within the HERC2 gene inhibiting OCA2 expression.
      ,
      • Han J.
      • Qureshi A.A.
      • Nan H.
      • Zhang J.
      • Song Y.
      • Guo Q.
      • et al.
      A germline variant in the interferon regulatory factor 4 gene as a novel skin cancer risk locus.
      ). This SNP is in high linkage disequilibrium (R2 = 0.85) with rs12913832, another intronic SNP in HERC2 that has been associated with pigmentation phenotypes (
      • Branicki W.
      • Brudnik U.
      • Wojas-Pelc A.
      Interactions between HERC2, OCA2 and MC1R may influence human pigmentation phenotype.
      ,
      • Eiberg H.
      • Troelsen J.
      • Nielsen M.
      • Mikkelsen A.
      • Mengel-From J.
      • Kjaer K.W.
      • et al.
      Blue eye color in humans may be caused by a perfectly associated founder mutation in a regulatory element located within the HERC2 gene inhibiting OCA2 expression.
      ,
      • Han J.
      • Kraft P.
      • Nan H.
      • Guo Q.
      • Chen C.
      • Qureshi A.
      • et al.
      A genome-wide association study identifies novel alleles associated with hair color and skin pigmentation.
      ,
      • Nan H.
      • Kraft P.
      • Qureshi A.A.
      • Guo Q.
      • Chen C.
      • Hankinson S.E.
      • et al.
      Genome-wide association study of tanning phenotype in a population of European ancestry.
      ,
      • Sturm R.A.
      • Duffy D.L.
      • Zhao Z.Z.
      • Leite F.P.
      • Stark M.S.
      • Hayward N.K.
      • et al.
      A single SNP in an evolutionary conserved region within intron 86 of the HERC2 gene determines human blue-brown eye color.
      ) and that modifies expression of OCA2, a nearby gene encoding a melanosomal enzyme needed for melanin synthesis (
      • Visser M.
      • Kayser M.
      • Palstra R.J.
      HERC2 rs12913832 modulates human pigmentation by attenuating chromatin-loop formation between a long-range enhancer and the OCA2 promoter.
      ). However, SNP rs12916300 remained associated with SCC risk with genome-wide significance after adjustment for rs12913832, suggesting that its effects are not merely due to its correlation with rs12913832. Currently, there is no specific evidence that rs12916300 disrupts any transcription factor binding sites, although it is located two base pairs from the binding motif of the transcription factor FOXI1 (
      • Pique-Regi R.
      • Degner J.F.
      • Pai A.A.
      • Gaffner D.J.
      • Gilad Y.
      • Pritchard J.K.
      Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data.
      , and http://regulomedb.org/snp). In data from the
      GTEx Consortium
      The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans.
      , rs12916300 was not associated with OCA2 expression in sun-exposed skin (P = 0.056 compared with a P-value of 0.013 for rs12913832) or in non–sun-exposed skin (P = 0.44), even without adjustment for linkage disequilibrium with rs12913832. None of the established pigment-related SNPs in HERC2/OCA2 met genome-wide significance for association in these data, despite their imputation with high accuracy (Supplementary Table S1a online). However, nine additional SNPs (three in HERC2 and six in OCA2) achieved genome-wide significance after adjustment for all 10 SNPs in Table 1 (Supplementary Table S1b). Further research is needed to clarify the roles in SCC risk of these nine SNPs, whose pairwise correlations range from weak to strong (Supplementary Figure S2 online).
      SNP rs4268748 at 16q24 is intronic in DEF8, which encodes an activator of intracellular signal transduction. This SNP is associated with expression levels of CDK10 (a gene critical for cell cycle progression) in sun-exposed skin (P = 2.3 × 10−11) and in nonexposed (supra-pubic) skin (P = 1.4 × 10−8) (
      GTEx Consortium
      The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans.
      ). The role of rs4268748 in SCC is complicated by its proximity (39 kb) to MC1R, a gene that encodes a receptor for melanocyte stimulating hormone and that contains several nonsynonymous SNPs associated with skin pigmentation (
      • Liu F.
      • Visser M.
      • Duffy D.L.
      • Hysi P.G.
      • Jacobs L.C.
      • Lao O.
      • et al.
      Genetics of skin color variation in Europeans: genome-wide association studies with functional follow-up.
      ,
      • Valverde P.
      • Healy E.
      • Jackson I.
      • Rees J.L.
      • Thody A.J.
      Variants of the melanocyte-stimulating hormone receptor gene are associated with red hair and fair skin in humans.
      ) and skin cancer (
      • Barrett J.H.
      • Iles M.M.
      • Harland M.
      • Taylor J.C.
      • Aitken J.F.
      • Andresen P.A.
      • et al.
      Genome-wide association study identifies three new melanoma susceptibility loci.
      ,
      • Bishop D.T.
      • Demenais F.
      • Iles M.M.
      • Harland M.
      • Taylor J.C.
      • Corda E.
      • et al.
      Genome-wide association study identifies three loci associated with melanoma risk.
      ,
      • Box N.F.
      • Duffy D.L.
      • Irving R.E.
      • Russell A.
      • Chen W.
      • Griffyths L.R.
      • et al.
      Melanocortin-1 receptor genotype is a risk factor for basal and squamous cell carcinoma.
      ,
      • Duffy D.L.
      • Zhao Z.Z.
      • Sturm R.A.
      • Hayward N.K.
      • Martin N.G.
      • Montgomery G.W.
      Multiple pigmentation gene polymorphisms account for a substantial proportion of risk of cutaneous malignant melanoma.
      ,
      • Ibarrola-Villava M.
      • Hu H.H.
      • Guedj M.
      • Fernandez L.P.
      • Descamps V.
      • Basset-Seguin N.
      • et al.
      MC1R, SLC45A2 and TYR genetic variants involved in melanoma susceptibility in southern European populations: results from a meta-analysis.
      ,
      • Palmer J.S.
      • Duffy D.L.
      • Box N.F.
      • Aitken J.F.
      • O'Gorman L.E.
      • Green A.C.
      • et al.
      Melanocortin-1 receptor polymorphisms and risk of melanoma: is the association explained solely by pigmentation phenotype?.
      ,
      • Sulem P.
      • Gudbjartsson D.F.
      • Stacey S.N.
      • Helgason A.
      • Rafnar T.
      • Magnusson K.P.
      • et al.
      Genetic determinants of hair, eye and skin pigmentation in Europeans.
      ) (Supplementary Table S2 online). In particular, SNPs in MC1R meeting genome-wide significance in this study include rs258322, which has been associated with CMM (
      • Barrett J.H.
      • Iles M.M.
      • Harland M.
      • Taylor J.C.
      • Aitken J.F.
      • Andresen P.A.
      • et al.
      Genome-wide association study identifies three new melanoma susceptibility loci.
      ,
      • Bishop D.T.
      • Demenais F.
      • Iles M.M.
      • Harland M.
      • Taylor J.C.
      • Corda E.
      • et al.
      Genome-wide association study identifies three loci associated with melanoma risk.
      ,
      • Stefanaki I.
      • Panagiotou O.A.
      • Kodela E.
      • Gogas H.
      • Kypreou K.P.
      • Chatzinasiou F.
      • et al.
      Replication and predictive value of SNPs associated with melanoma and pigmentation traits in a Southern European case-control study.
      ) and pigment-related traits (
      • Valverde P.
      • Healy E.
      • Jackson I.
      • Rees J.L.
      • Thody A.J.
      Variants of the melanocyte-stimulating hormone receptor gene are associated with red hair and fair skin in humans.
      ), and the nonsynonymous SNPs rs1805007 (Arg151Cys) and rs1805008 (Arg160Trp), which have been associated with CMM (
      • Duffy D.L.
      • Zhao Z.Z.
      • Sturm R.A.
      • Hayward N.K.
      • Martin N.G.
      • Montgomery G.W.
      Multiple pigmentation gene polymorphisms account for a substantial proportion of risk of cutaneous malignant melanoma.
      ,
      • Ibarrola-Villava M.
      • Hu H.H.
      • Guedj M.
      • Fernandez L.P.
      • Descamps V.
      • Basset-Seguin N.
      • et al.
      MC1R, SLC45A2 and TYR genetic variants involved in melanoma susceptibility in southern European populations: results from a meta-analysis.
      ,
      • Palmer J.S.
      • Duffy D.L.
      • Box N.F.
      • Aitken J.F.
      • O'Gorman L.E.
      • Green A.C.
      • et al.
      Melanocortin-1 receptor polymorphisms and risk of melanoma: is the association explained solely by pigmentation phenotype?.
      ,
      • Sulem P.
      • Gudbjartsson D.F.
      • Stacey S.N.
      • Helgason A.
      • Rafnar T.
      • Magnusson K.P.
      • et al.
      Genetic determinants of hair, eye and skin pigmentation in Europeans.
      ), NMSC (
      • Box N.F.
      • Duffy D.L.
      • Irving R.E.
      • Russell A.
      • Chen W.
      • Griffyths L.R.
      • et al.
      Melanocortin-1 receptor genotype is a risk factor for basal and squamous cell carcinoma.
      ), and, among renal transplant patients, SCC (
      • Andresen P.A.
      • Nymoen D.A.
      • Kjaerheim K.
      • Leivestad T.
      • Helsing P.
      Susceptibility to cutaneous squamous cell carcinoma in renal transplant recipients associates with genes regulating melanogenesis independent of their role in pigmentation.
      ). However, none of these three SNPs maintained genome-wide significance after adjusting for genotypes at rs4268748, which has been associated with MC1R expression with borderline statistical significance (P = 0.012) in sun-exposed skin (
      GTEx Consortium
      The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans.
      ). Furthermore, two additional SNPs at this locus (rs35063026 in an untranslated region of SPATA33, and rs78703231 in an intron in SPIRE2) were independently associated with SCC risk after adjustment for rs4268748 (Figure 2 and Supplementary Materials online). These three SNPs (rs4268748, rs35063026, and rs78703231) lie at most 249 kb downstream of MC1R, and their SCC associations could reflect correlation with one or more of the nonsynonymous MC1R SNPs previously associated with pigmentation and/or skin cancer risk. Indeed, after adjustment for the subset of these SNPs with minor allele frequencies greater than 1% in this study (Supplementary Materials and Table S3 online), rs78703231 lost statistical significance, with pre- and postadjustment risk ratios of 1.21 (P = 1.77 × 10−17) and 1.05 (P = 8.21 × 10−2). However, strong associations persisted for both rs4268748 (postadjustment risk ratio = 1.22, P = 1.96 × 10−16) and rs35063026 (postadjustment risk ratio = 1.33, P = 5.38 × 10−11). These findings suggest the existence of multiple independent SCC susceptibility loci in the 16q24 region whose precise roles in SCC pathogenesis remain to be elucidated.
      Figure 2
      Figure 2Manhattan plot enlargement showing the 0.7 Mb region at the 16q24 locus. The upper panel shows the name and location of genes in the region, with an arrow indicating the transcribed strand of a gene and ticks indicating exons. The genes DEF8 (containing the top SNP rs4268748) and MC1R (associated with skin pigmentation and skin cancer) are shown in boxes. The lower panel shows the significance levels of the SNPs in this region, with labels for the three SNPs that are independently associated with SCC risk.
      Finally, SNP rs6059655 at 20q11, which is intronic in RALY, lies 182 kb upstream of ASIP, a gene that encompasses SNPs associated with pigmentation traits (
      • Jacobs L.C.
      • Hamer M.A.
      • Gunn D.A.
      • Deelen J.
      • Lall J.S.
      • van Heemst D.
      • et al.
      A genome-wide association study identifies the skin color genes IRF4, MC1R, ASIP, and BNC2 influencing facial pigmented spots.
      ,
      • Liu F.
      • Visser M.
      • Duffy D.L.
      • Hysi P.G.
      • Jacobs L.C.
      • Lao O.
      • et al.
      Genetics of skin color variation in Europeans: genome-wide association studies with functional follow-up.
      ), CMM (
      • Amos 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.
      ,
      • Barrett J.H.
      • Iles M.M.
      • Harland M.
      • Taylor J.C.
      • Aitken J.F.
      • Andresen P.A.
      • et al.
      Genome-wide association study identifies three new melanoma susceptibility loci.
      ,
      • Brown K.M.
      • Macgregor S.
      • Montgomery G.W.
      • Craig D.W.
      • Zhao Z.Z.
      • Iyadurai K.
      • et al.
      Common sequence variants on 20q11.22 confer melanoma susceptibility.
      ,
      • Duffy D.L.
      • Zhao Z.Z.
      • Sturm R.A.
      • Hayward N.K.
      • Martin N.G.
      • Montgomery G.W.
      Multiple pigmentation gene polymorphisms account for a substantial proportion of risk of cutaneous malignant melanoma.
      ,
      • Maccioni L.
      • Rachakonda P.S.
      • Scherer D.
      • Bermejo J.L.
      • Planelles D.
      • Requena C.
      • et al.
      Variants at chromosome 20 (ASIP locus) and melanoma risk.
      ), and NMSC (
      • Binstock M.
      • Hafeez F.
      • Metchnikoff C.
      • Arron S.T.
      Single-nucleotide polymorphisms in pigment genes and nonmelanoma skin cancer predisposition: a systematic review.
      ,
      • Lin W.
      • Qureshi A.A.
      • Kraft P.
      • Nan H.
      • Guo Q.
      • Hu F.B.
      • et al.
      ASIP genetic variants and the number of non-melanoma skin cancers.
      ,
      • Nan H.
      • Kraft P.
      • Hunter D.J.
      • Han J.
      Genetic variants in pigmentation genes, pigmentary phenotypes, and risk of skin cancer in Caucasians.
      ,
      • Nan H.
      • Qureshi A.A.
      • Han J.
      Melanoma susceptibility variants on chromosome 20q11.22 are associated with pigmentary traits and the risk of nonmelanoma skin cancer.
      ) (Supplementary Figure S3 online). Only three of these SNPs (rs4911442, rs910873, and rs1885120) met the genome-wide significance threshold for association with SCC in the present data, and none maintained genome-wide significance after adjustment for rs6059655. A haplotype in ASIP containing the T allele of rs4911414 and the G allele of rs1015362 has been associated with pigment-related traits and with CMM and BCC (
      • Gudbjartsson D.F.
      • Sulem P.
      • Stacey S.N.
      • Goldstein A.M.
      • Rafnar T.
      • Sigurgeirsson B.
      • et al.
      ASIP and TYR pigmentation variants associate with cutaneous melanoma and basal cell carcinoma.
      ,
      • Sulem P.
      • Gudbjartsson D.F.
      • Stacey S.N.
      • Helgason A.
      • Rafnar T.
      • Magnusson K.P.
      • et al.
      Genetic determinants of hair, eye and skin pigmentation in Europeans.
      ). However, adjustment for this haplotype did not eliminate the observed association between SCC and rs6059655 (OR: 1.40, P = 1.31 × 10−10 for rs6059655 and 1.30, P = 2.0 × 10−16 for the haplotype). This finding, coupled with the observed association between rs6059655 and ASIP expression levels in sun-exposed skin (P = 5.3 × 10−9) and non–sun-exposed skin (P = 4.4 × 10−4) (
      GTEx Consortium
      The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans.
      ), lends support to the possibility that rs6059655 (or a nearby functional SNP) affects ASIP activity independently of the ASIP haplotype.
      In summary, the observed associations between SCC risk and SNPs at 15q13, 16q24, and 20q11 could not be explained by their proximity to previously studied SNPs in the pigmentation and skin cancer genes HERC2/OCA2, MC1R, and ASIP, respectively. Further work on the functions of these SNPs is needed to elucidate their potential causal roles and mechanisms in SCC.
      We checked whether subjects’ total counts of risk alleles of the six pigment-related SNPs in Table 1 (section A) (called their risk indices) influence their SCC risk independently of their pigment-related phenotypes (skin color, tanning, and sun sensitivity). Because we lacked self-reported or clinical data on these pigment-related phenotypes, we estimated them using subjects’ total allele counts for SNPs associated with fair skin, poor tanning ability, and tendency to sunburn (see Supplementary Materials and Table S4 online for details on how we assembled these pigmentation scores). Supplementary Table S5 online shows the joint distribution of subjects by tertiles of risk index and of skin phenotype score, with tertiles determined by the distributions in controls. The table also shows joint and marginal ORs relating SCC risk to tertiles of risk index and pigmentation score. Because some SNPs were used to calculate both the risk indices and the pigmentation scores, the ORs may be attenuated toward unity. Nevertheless, consistently with the findings of others (
      • Andresen P.A.
      • Nymoen D.A.
      • Kjaerheim K.
      • Leivestad T.
      • Helsing P.
      Susceptibility to cutaneous squamous cell carcinoma in renal transplant recipients associates with genes regulating melanogenesis independent of their role in pigmentation.
      ,
      • Bastiaens M.T.
      • ter Huurne J.A.
      • Kielich C.
      • Gruis N.A.
      • Westendorp R.G.
      • Vermeer B.J.
      • et al.
      Melanocortin-1 receptor gene variants determine the risk of nonmelanoma skin cancer independently of fair skin and red hair.
      ,
      • Gerstenblith M.R.
      • Shi J.
      • Landi M.T.
      Genome-wide association studies of pigmentation and skin cancer: a review and meta-analysis.
      ,
      • Kennedy C.
      • ter Huurne J.
      • Berkhout M.
      • Gruis N.
      • Bastiaens M.
      • Bergman W.
      • et al.
      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.
      ,
      • Nan H.
      • Kraft P.
      • Hunter D.J.
      • Han J.
      Genetic variants in pigmentation genes, pigmentary phenotypes, and risk of skin cancer in Caucasians.
      ,
      • Palmer J.S.
      • Duffy D.L.
      • Box N.F.
      • Aitken J.F.
      • O'Gorman L.E.
      • Green A.C.
      • et al.
      Melanocortin-1 receptor polymorphisms and risk of melanoma: is the association explained solely by pigmentation phenotype?.
      ), we observed increased SCC risk with increasing risk index, independently of the estimated pigmentation phenotypes. Specifically, Supplementary Table S5 shows strong trends of increased SCC risk with increasing risk index within each tertile of the skin pigmentation scores, as well as overall, after adjustment for pigmentation score. Moreover, the data suggest trends of increasing risk index ORs with increasingly sun-sensitive pigmentation phenotypes, with significance levels of P = 0.85, P = 1.15 × 10−7, and P = 0.002 for skin color, sun sensitivity, and tanning ability, respectively. We also found similar trends of higher SCC risk with increasing pigmentation score within each tertile of risk index, and overall, after adjustment for risk index, suggesting independent contributions of genetic risk index and pigmentation phenotypes in determining SCC susceptibility.

      Other loci

      Four additional SCC loci met the genome-wide significance threshold (Table 1, section B), which, to our knowledge, have limited or no relation to the pigmentation pathway. Among the four, the HLA locus at 6p21 was most strongly associated with SCC risk, with a per-allele risk ratio of 1.17 (P = 1.86 × 10−8) for the most significant SNP, rs4455710 (Figure 1). This SNP is intronic in the class II HLA gene HLADQA1 (Supplementary Figure S4 online), which binds peptides derived from antigens that access the endocytic route of antigen-presenting cells and presents them on the cell surface for recognition by CD4 T cells. No other SNP in the region maintained genome-wide significance after adjusting for rs4455710. This SNP is also strongly associated with expression levels of nearby genes, including HLA-DQA1 (P = 3.3 × 10−7 and P = 4.2 × 10−6 in sun-exposed and nonexposed skin, respectively), HLA-DQB1 (P = 1.1 × 10−6 in sun-exposed skin), and HLA-DRB5 (P = 4.3 × 10−12 and P = 2.6 × 10−9 in sun-exposed and nonexposed skin, respectively) (
      GTEx Consortium
      The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans.
      ). A role for HLA antigens and immune response in SCC is supported by findings of elevated SCC risk in immunocompromised individuals (
      • Bouwes Bavinck J.N.
      • Vermeer B.J.
      • van der Woude F.J.
      • Vandenbroucke J.P.
      • Schreuder G.M.
      • Thorogood J.
      • et al.
      Relation between skin cancer and HLA antigens in renal-transplant recipients.
      ), by data relating NMSCs to specific HLA alleles (
      • Bouwes Bavinck J.N.
      • Claas F.H.
      The role of HLA molecules in the development of skin cancer.
      ), and by elevated SCC risk in cigarette smokers (
      • Leonardi-Bee J.
      • Ellison T.
      • Bath-Hextall F.
      Smoking and the risk of nonmelanoma skin cancer: systematic review and meta-analysis.
      ), because smoking is associated with changes in circulating markers for immune response (
      • Shiels M.S.
      • Katki H.A.
      • Freedman N.D.
      • Purdue M.P.
      • Wentzensen N.
      • Trabert B.
      • et al.
      Cigarette smoking and variations in systemic immune and inflammation markers.
      ). However, we did not find strong evidence that the risk ratio per allele of rs4455710 varies by the history of smoking or immunosuppression (Supplementary Table S6 online).
      The remaining three SNPs in Table 1 (section B) open avenues for further study. SNP rs62246017 at 3p13 is intronic in FOXP1, which encodes a transcription repressor with important roles in immune response, organ development, and the pathogenesis of epithelial malignancies. Alterations in FOXP1 expression have been implicated in the pathogenesis of squamous cell cancers of the lung and of the head and neck (
      • Feng J.
      • Zhang X.
      • Zhu H.
      • Wang X.
      • Ni S.
      • Huang J.
      High expression of FoxP1 is associated with improved survival in patients with non-small cell lung cancer.
      ,
      • Yang M.H.
      • Lin B.R.
      • Chang C.H.
      • Chen S.T.
      • Lin S.K.
      • Kuo M.Y.
      • et al.
      Connective tissue growth factor modulates oral squamous cell carcinoma invasion by activating a miR-504/FOXP1 signalling.
      ).
      The intergenic SNP rs6791479 at 3q28 lies 144 kb upstream of TP63, which encodes a member of the p53 family of transcription factors (
      • Poligone B.
      • Gilmore E.S.
      • Alexander C.V.
      • Oleksyn D.
      • Gillespie K.
      • Zhao J.
      • et al.
      PKK suppresses tumor growth and is decreased in squamous cell carcinoma of the skin.
      ). One of its two main isoforms (ΔNp63) is involved in multiple functions during skin development and in adult stem/progenitor cell regulation (
      • Crum C.P.
      • McKeon F.D.
      p63 in epithelial survival, germ cell surveillance, and neoplasia.
      ,
      • Leonard M.K.
      • Kommagani R.
      • Payal V.
      • Mayo L.D.
      • Shamma H.N.
      • Kadakia M.P.
      DeltaNp63alpha regulates keratinocyte proliferation by controlling PTEN expression and localization.
      ). TP63 immunostaining has utility for differentiating subtypes of head and neck SCCs. In other tissues, TP63 is helpful in distinguishing poorly differentiated SCC (strong staining) from small cell carcinoma or adenocarcinoma (no staining). SNP rs6791479 is associated with expression of TP63 in non–sun-exposed skin (P = 0.0036) (
      GTEx Consortium
      The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans.
      ).
      Finally, the intergenic SNP rs74664507 at 9p22 lies 43 kb upstream of BNC2, which encodes a zinc-finger protein thought to be involved in mRNA processing (
      • Vanhoutteghem A.
      • Djian P.
      Basonuclins 1 and 2, whose genes share a common origin, are proteins with widely different properties and functions.
      ) and to function as a transcription factor (
      • Romano R.A.
      • Li H.
      • Tummala R.
      • Maul R.
      • Sinha S.
      Identification of basonuclin2, a DNA-binding zinc-finger protein expressed in germ tissues and skin keratinocytes.
      ). The role of BNC2 in human pigmentation is unclear, despite experimental evidence suggesting that the gene influences pigmentation in mice (
      • Smyth I.M.
      • Wilming L.
      • Lee A.W.
      • Taylor M.S.
      • Gautier P.
      • Barlow K.
      • et al.
      Genomic anatomy of the Tyrp1 (brown) deletion complex.
      ) and zebrafish (
      • Patterson L.B.
      • Parichy D.M.
      Interactions with iridophores and the tissue environment required for patterning melanophores and xanthophores during zebrafish adult pigment stripe formation.
      ), and despite its elevated expression levels in human epidermal skin samples and melanocytic cell lines from dark-skinned donors (
      • Visser M.
      • Palstra R.J.
      • Kayser M.
      Human skin color is influenced by an intergenic DNA polymorphism regulating transcription of the nearby BNC2 pigmentation gene.
      ). Functional data indicate that BNC2 expression is influenced by the intergenic SNP rs12350739 located in a BNC2 enhancer (
      • Visser M.
      • Palstra R.J.
      • Kayser M.
      Human skin color is influenced by an intergenic DNA polymorphism regulating transcription of the nearby BNC2 pigmentation gene.
      ). This finding, coupled with the high linkage disequilibrium at this locus, has suggested that rs12350739 is responsible for the observed associations of intronic SNP rs10756819 with skin color (
      • Jacobs L.C.
      • Wollstein A.
      • Lao O.
      • Hofman A.
      • Klaver C.C.
      • Uitterlinden A.G.
      • et al.
      Comprehensive candidate gene study highlights UGT1A and BNC2 as new genes determining continuous skin color variation in Europeans.
      ) and of intronic SNP rs215327 with freckling (
      • Eriksson N.
      • Macpherson J.M.
      • Tung J.Y.
      • Hon L.S.
      • Naughton B.
      • Saxonov S.
      • et al.
      Web-based, participant-driven studies yield novel genetic associations for common traits.
      ). Interestingly, SNPs rs74664507 and rs12350739 are also in high linkage disequilibrium (R2 = 0.84). Thus not surprisingly, univariate regression of SCC risk against genotypes of rs12350739 showed borderline genome-wide significance (P = 7.62 × 10−08), whereas regression of SCC risk against both SNPs showed attenuated association (P = 0.04) for rs74664507 and no association (P = 0.92) for rs12350739. Additional replication and functional work are needed to elucidate the role of BNC2 in SCC risk.

      Allelic effects of SNPs in Table 1

      For each of the SNPs at the 10 susceptibility loci in Table 1, we used a likelihood ratio statistic to evaluate how well allelic effects on SCC risk were captured by a one-degree-of-freedom log-additive logistic model relative to a codominant (two-degree-of-freedom) model. The likelihood ratio statistic has a chi-square distribution with one degree of freedom under the null hypothesis that the log-additive allelic model fits well. We found significant improvement in fit for the codominant model relative to the log-additive model only for SNP rs1126809 in TYR at 11q24 (P = 3.6 × 10−3). SCC odds ratios for heterozygote and homozygote carriers of the A-allele of this SNP were 1.13 (95% confidence interval: 1.07–1.19) and 1.51 (1.39–1.64), respectively.

      Genetic and nongenetic interactions

      We found no evidence that ORs for the SNPs in Table 1 varied by gender, but some varied by age at RPGEH enrollment, as classified into three categories based on the control tertiles and coded ordinally. Specifically, we found significant interaction P-values for SNPs rs12203592 in IRF4 (P = 3.52 × 10−6), rs1126809 in TYR (P = 0.04), and SNP rs4268748 in DEF8 (P = 0.01). In all three analyses, the ORs estimates decreased with increasing age. We also evaluated potential epistatic effects on SCC risk among the 45 pairs of the 10 SNPs in Table 1. We observed evidence for superadditivity (on the log odds scale) of effects at pairs of loci 20q11 and 11q14 (P = 0.017) and for subadditivity for five other pairs: 5p13 and 6p25 (P = 0.013), 6p21 and 15q13 (P = 0.023), 20q11 and 5p13 (P = 0.032), and 20q11 and 16q24 (P = 0.041) (Supplementary Table S7 online). In addition, we evaluated the effects of SNP rs4455710 at 6p21 by a history of smoking and immunosuppression. Specifically, because immunosuppressed recipients of major organ transplants have elevated SCC risk (
      • Andresen P.A.
      • Nymoen D.A.
      • Kjaerheim K.
      • Leivestad T.
      • Helsing P.
      Susceptibility to cutaneous squamous cell carcinoma in renal transplant recipients associates with genes regulating melanogenesis independent of their role in pigmentation.
      ), we examined whether the log odds of SCC varied between subjects with and without a history of immunosuppression, as indicated by a history of organ transplantation, chronic lymphocytic, or HIV infection. Similarly, because cigarette smokers have altered immune status compared with nonsmokers (
      • Shiels M.S.
      • Katki H.A.
      • Freedman N.D.
      • Purdue M.P.
      • Wentzensen N.
      • Trabert B.
      • et al.
      Cigarette smoking and variations in systemic immune and inflammation markers.
      ), we compared SNP ORs in ever- versus never-smokers. Supplementary Table S6 shows no evidence of effect modification at this SNP by either smoking status or history of immunosuppression.

      Discussion

      This large SCC GWAS has confirmed existing associations between SCC risk and three SNPs in genes known to be related to the pigmentation pathway. These include nonsynonymous SNPs in SLC45A2 on chromosome 5p13 and in TYR on chromosome 11q14, and a functional intronic SNP in IRF4 on chromosome 6p25. It also has identified previously unreported SCC-associated SNPs at three other loci (15q13, 16q24, and 20q11) containing pigmentation genes associated with skin cancer risk, and we were unable to attribute these associations to correlation with putative causal variants in these genes. Finally, we have identified four additional loci previously unrelated to SCC risk.
      Strengths of this study include its large sample size and its use of a demographically diverse NHW cohort characterized by comprehensive clinical data. The findings need replication in an NHW population having demographic characteristics and ancestries that differ from those of the Northern California population studied here. If the associations are replicated, functional research will be needed to better understand the roles of the associated SNPs in the pigment-related regions 15q13, 16q24, and 20q11, and in the four nonpigment-related regions. In summary, the present findings can facilitate the development of SCC prediction models that identify subgroups in need of more intensive screening. They also can motivate future investigations of genetic factors that modify ultraviolet radiation exposures and other lifestyle characteristics in conferring SCC risk.

      Materials and Methods

      Study population

      Potentially eligible study subjects were RPGEH members who at cohort entry reported NHW race/ethnicity, were at least 18 years of age, and had no diagnostic codes for rare genetic disorders associated with increased SCC risk (e.g., xeroderma pigmentosum, oculocutaneous albinism, dystrophic epidermolysis bullosa, epidermodysplasia verruciformis, Fanconi anemia, dyskeratosis congenita, Rothmund-Thomson syndrome, Bloom syndrome, Werner syndrome, and Ferguson Smith syndrome).
      Potentially eligible cases were subjects whose pathology records were consistent with incident SCC (invasive or in situ, excluding anogenital and mucosal SCCs) during the period from survey completion until either 31 December 2012 or departure from the Kaiser Permanente Northern California health care system, whichever occurred first. (See Supplementary Materials for details on SCC case verification by pathology review.) Potentially eligible controls (n = 64,218) were subjects with no RPGEH-survey-reported history of skin cancer and no pathology records consistent with skin cancer in the Kaiser Permanente Northern California database. After quality control was applied to all potentially eligible subjects (as described in Supplementary Materials and Table S8 online), a total of 67,867 subjects were eligible for analysis.

      Genotyping

      Saliva samples from eligible subjects were genotyped on four custom Affymetrix Axiom arrays optimized for individuals of European, East Asian, Latino, and African American race/ethnicity (
      • Hoffmann T.J.
      • Kvale M.N.
      • Hesselson S.E.
      • Zhan Y.
      • Aquino C.
      • Cao Y.
      • et al.
      Next generation genome-wide association tool: design and coverage of a high-throughput European-optimized SNP array.
      ,
      • Hoffmann T.J.
      • Zhan Y.
      • Kvale M.N.
      • Hesselson S.E.
      • Gollub J.
      • Iribarren C.
      • et al.
      Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm.
      , for the other arrays [http://www.ncbi.nlm.nih.gov/pubmed/21903159]). Genotyping and SNP quality control have been described previously (dbGaP phs000674.v1.p1) (
      • Banda Y.
      • Kvale M.N.
      • Hoffmann T.J.
      • Hesselson S.E.
      • Ranatunga D.
      • Tang H.
      • et al.
      Characterizing race/ethnicity and genetic ancestry for 100,000 subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort.
      ,
      • Hoffmann T.J.
      • Kvale M.N.
      • Hesselson S.E.
      • Zhan Y.
      • Aquino C.
      • Cao Y.
      • et al.
      Next generation genome-wide association tool: design and coverage of a high-throughput European-optimized SNP array.
      ,
      • Hoffmann T.J.
      • Zhan Y.
      • Kvale M.N.
      • Hesselson S.E.
      • Gollub J.
      • Iribarren C.
      • et al.
      Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm.
      ,
      • Kvale M.N.
      • Hesselson S.
      • Hoffmann T.J.
      • Cao Y.
      • Chan D.
      • Connell S.
      • et al.
      Genotyping informatics and quality control for 100,000 subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort.
      ). SNP imputation to the 1000 Genomes Project is described in the Supplementary Materials.

      Internal validation

      For the screening phase we used the genotypes of the 61,457 subjects (6,891 cases and 54,566 controls) who had been typed on the European array, and for the replication phase we used the remaining 6,410 NHW subjects (810 cases and 5,600 controls) who had been typed erroneously on a non-European array. Supplementary Table S9 online shows the classification of all subjects by case-control status, gender, and study phase (screening or replication). Subjects’ genotypes for untyped SNPS were imputed to the 1000 Genomes Project.

      eQTL evaluation

      We also examined the public GTEx database for evidence that SNPs of interest regulate the expression of nearby genes in skin tissue (see Supplementary Materials).

      Statistical analysis

      To adjust for population stratification, we determined ancestry principal components for the combined data from screening and replication phases using the smartpca program in the EIGENSOFT4.2 software package (
      • Hemminki K.
      • Zhang H.
      • Czene K.
      Familial invasive and in situ squamous cell carcinoma of the skin.
      ), as has been described elsewhere (dbGaP phs000674.v1.p1). For each of the screening and replication phases, we then evaluated SCC association with each SNP’s allelic count using the Armitage-Cochran trend statistic, adjusted for gender, the first 10 principal components of ancestry, and for the genotyping array and reagent kit. We combined regression coefficients and P-values obtained from screening and replication phases using Cochran’s method (
      • Cochran W.G.
      The combination of estimates from different experiments.
      ,
      • Zhou B.
      • Shi J.
      • Whittemore A.S.
      Optimal methods for meta-analysis of genome-wide association studies.
      ), and identified as significant those SNPs with combined P-values < 5 × 10−8 (
      • Pe'er I.
      • Yelensky R.
      • Altshuler D.
      • Daly M.J.
      Estimation of the multiple testing burden for genomewide association studies of nearly all common variants.
      ). We checked for residual population stratification by examining the inflation factor λGC (
      • Devlin B.
      • Roeder K.
      Genomic control for association studies.
      ), and Q-Q plots of percentiles of the observed distribution of test statistics versus those expected under the global null hypothesis (see Supplementary Materials). Further adjustment for age and immunosuppressive status resulted in negligible changes in the ORs for the top 10 SNPs in Table 1.

      Data accessibility

      Genotypes used in this GWAS have been registered with dbGAP (Study Accession: phs000674.v1.p1).
      All study procedures were approved by the Institutional Review Board of the Kaiser Foundation Research Institute.

      Conflict of Interest

      The authors state no conflicts of interest.

      Acknowledgments

      This research was supported by NIH grant R01CA166672, by the GO grant RC2 AG036607, and by the Wayne and Gladys Valley Foundation, the Ellison Medical Foundation, the Robert Wood Johnson Foundation, and Kaiser Permanente Community Benefit Program. We thank Neil Risch, University of California at San Francisco, and Cathy Schaefer, Kaiser Permanente Northern California Division of Research, for establishing the RPGEH cohort and processing and providing the genetic data. We also thank Julia L. Kay and Dilrini K. Ranatunga, Kaiser Permanente Northern California Division of Research, for their help in documenting and transferring the genetic and nongenetic data and providing the background information needed for the analysis.

      Supplementary Material

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