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. Author manuscript; available in PMC: 2015 May 1.
Published in final edited form as: Pigment Cell Melanoma Res. 2014 Jan 30;27(3):485–488. doi: 10.1111/pcmr.12215

MITF E318K’s effect on melanoma risk independent of, but modified by, other risk factors

Marianne Berwick 1, Jamie MacArthur 2, Irene Orlow 3, Peter Kanetsky 4, Colin B Begg 5, Li Luo 6, Anne Reiner 7, Ajay Sharma 8, Bruce K Armstrong 9, Anne Kricker 10, Anne E Cust 11, Loraine D Marrett 12, Stephen B Gruber 13, Hoda Anton-Culver 14, Roberto Zanetti 15, Stefano Rosso 16, Richard P Gallagher 17, Terrance Dwyer 18, Alison Venn 19, Klaus Busam 20, Lynn From 21, Kirsten White 22, Nancy E Thomas 23, For the GEM Study Group
PMCID: PMC3988207  NIHMSID: NIHMS558405  PMID: 24406078

Summary

A rare germline variant in the MITF (microphthalmia-associated transcription factor) gene, E318K, has been reported as associated with melanoma. We confirmed its independent association with melanoma (odds ratio (OR) 1.7, 95% Confidence Interval (CI) = 1.1, 2.7, p = 0.03); adjusted for age, sex, center, age*sex interaction, pigmentation characteristics, family history of melanoma and nevus density). In stratified analyses, carriage of MITF E318K was associated with melanoma more strongly in people with dark hair than fair hair (p for interaction, 0.03) and in those with no moles than some or many moles (p for interaction, <0.01). There was no evidence of interaction between MC1R “red hair variants” and MITF E318K. Moreover, risk of melanoma among carriers with “low risk” phenotypes was as great or greater than among those with “at risk” phenotypes with few exceptions.

Keywords: MITF, melanoma, risk factors, single nucleotide polymorphism, case control study

MITF, the microphthalmia-associated transcription factor, is critical for lineage commitment of undifferentiated, immature neural crest cells to mature, melanin-producing melanocytes (Goding, 2000). UV exposure to the epidermis promotes alpha-MSH release, which then binds to the melanocortin-1 receptor (MC1R), a transmembrane G-protein-coupled receptor located on the cell membrane of melanocytes. This binding culminates in the activation of the M-isoform of MITF, termed MITF-M, expressed in melanocytes through a cAMP-mediated signaling pathway (Haq and Fisher, 2011; Fuse et al., 1996). The activation of MITF, in turn, induces the transcription of pigmentation-related genes, which produce eumelanin that protects cells from UV damage (Cheli et al., 2009). Other MITF functions may be based on the fact that several MITF-target genes regulate cell cycle and survival (Cheli et al., 2010), and MITF appears to protect against oxidative stress (Liu et al., 2009).

The E318K variant of MITF (rs149617956) is a functional and rare variant that is associated with melanoma risk. It is located in a small-ubiquitin-like modifier (SUMO) consensus site and the missense variant impairs the SUMOylation of MITF, leading to the binding of MITF and the transcriptional regulation of MITF’s target genes. In a large Australian case-control study of 2,059 melanoma cases and in a UK case-control study of 1,929 cases, the E318K variant conferred a 2.2-fold risk for developing melanoma (Yokoyama et al., 2011). Among a sample of 586 French melanoma patients, genetically enriched for melanoma and renal cell carcinoma, a 4.8-fold increased risk of melanoma was observed in MITF variant carriers (Bertolotto et al., 2011). An Italian study of 667 patients in a clinic setting found a 2.9-fold increased risk for melanoma, which was greater with nodular than with other histological types of melanoma (Ghiorzo et al., 2013). They also observed positive associations of the variant with personal or family history of renal cell or pancreatic cancer.

The prevalence of the MITF E318K minor allele variant among melanoma cases is low: 0.017 in Australia; 0.018 in the UK; 0.016 in France; and 0.009 in Italy (Yokoyama et al., 2011; Bertolotto et al., 2011; Ghiorzo et al., 2013). Our large international, multicenter melanoma case control study, GEM, was designed especially to identify the effects of rare genetic variants in melanoma (Begg and Berwick, 1997). A detailed description of the methods used in this study is available elsewhere (Begg et al., 2006). It was conducted in nine centers in four countries--Australia, Italy, Canada and the United States. Institutional review board approval was obtained from all centers. Written informed consent was obtained prior to interview.

In GEM, patients newly diagnosed with a second or higher order primary melanoma are cases, and individuals newly diagnosed with a first primary melanoma are controls; this design produces similar results to classic case-control studies, but with greater statistical power to detect effects of rare risk factors (Begg and Berwick, 1997). We assessed MITF E318K in 1,194 cases and 2,430 controls. It was genotyped by mass spectrometry with the MassArray iPLEX genotyping platform (Sequenom Inc, San Diego, CA). Quality control included use of internal negative controls, sequencing of selected samples to confirm specificity, and agreement between blinded duplicates (Orlow et al., 2012). All statistical tests were two-sided with P < 0.05 considered statistically significant. All data were analyzed using SAS 9.3 (Cary, NC). There were 97 carriers of the E138K variant, 44 (3.7%) among the 1,194 cases and 53 (2.2%) among the 2,430 controls. The minor allele frequency was 0.014 among all melanoma patients, similar to other studies noted above.

Presence of MITF E318K was significantly associated with risk for melanoma (OR 1.7, 95 % CI 1.1, 2.6, p = 0.02) in a logistic regression model adjusted for the design variables: age at diagnosis, sex, age*sex interaction, and recruitment center. This association is similar in strength to that observed in the Australian and UK studies described above. After further adjustment for pigmentation characteristics, family history of melanoma, and nevus density, the OR remained as 1.7 (95% CI = 1.1, 2.7, p = 0.03).

Odds ratios for the association of MITF E318K with melanoma in categories of other melanoma risk factors (which have been shown to be associated with melanoma in this study (Begg et al., 2006) are shown in Table 1. Increased risk of melanoma with carriage of MITF E318K appeared to be strongest among those with traditionally low risk phenotypes: “nonblue” eyes, black/dark brown hair, absence of moles, absence of freckling in youth and absence of a family history of melanoma (Table 1) This effect modification, though, was significant only for mole count and hair color. However, although the interaction is significant, red hair color had an odds ratio of 3.1 (95% CI 0.9, 10.8), so this association needs further study. When evaluating the mole count in relationship to the MITF variant, it can be seen that our results are similar to those reported by Yokoyama et al. (2011), where there is a significant trend among single primary melanomas, our controls, for the association between mole count and the presence of the variant E318K in MITF (p = 0.04)

Table 1.

Odds ratios for the association of the MITF E318K variant with melanoma risk in strata of other melanoma risk factors.

Variables Strata Variant Status Odds Ratio (95% CI)1 for melanoma associated with MITF variant P-value for interacti on
Cases Controls
Variant−
N (%)		 Variant+
N (%)		 Variant−
N (%)		 Variant+
N (%)
MITF All subjects 1150 (96.3) 44 (3.7) 2377 (97.8) 53 (2.2) 1.7 (1.1, 2.6) NA
Eye color Blue 532 (97.8) 12 (2.2) 987 (98.3) 17 (1.7) 1.2 (0.5, 2.6)
Other 618 (95.1) 32 (4.9) 1390 (97.5) 36 (2.5) 2.1 (1.2, 3.5) 0.25
Hair Color Black/dark brown 291 (95.7) 13 (4.3) 754 (98.6) 11 (1.4) 3.8 (1.5, 9.6)
light brown/blond 727 (97.1) 22 (2.9) 1393 (97.6) 35 (2.4) 1.0 (0.6, 1.8)
red 127 (93.4) 9 (6.6) 207 (97.6) 5 (2.4) 3.1 (0.9, 10.8) 0.03
Skin color Olive 92 (97.9) 2 (2.1) 320 (98.8) 4 (1.2) 1.9 (0.2, 14.2)
Fair 793 (96.4) 30 (3.6) 1597 (98.2) 30 (1.8) 2.2 (1.2, 3.8)
Very fair 263 (95.6) 12 (4.4) 450 (95.9) 19 (4.1) 0.9 (0.4, 2.0) 0.23
Moles None 254 (94.4) 15 (5.6) 564 (99.1) 5 (0.9) 5.9 (1.9, 18.0)
Few 551 (97.0) 17 (3.0) 1207 (97.4) 32 (2.6) 1.1 (0.6, 2.1)
Moderate 233 (96.7) 8 (3.3) 359 (97.5) 9 (2.5) 1.5 (0.5, 4.5)
Many 75 (96.2) 3 (3.8) 114 (96.6) 4 (3.4) 1.2 (0.2, 7.0) <0.01
Propensity to Burn Low 575 (97.0) 18 (3.0) 1319 (98.2) 24 (2.8) 1.7 (0.9, 3.4)
High 548 (95.8) 24 (4.2) 1003 (97.3) 28 (2.7) 1.7 (0.9, 3.0) 0.97
Inability to Tan No 602 (97.4) 16 (2.6) 1377 (98.3) 24 (1.7) 1.5 (0.8, 3.1)
Yes 521 (95.1) 27 (4.9) 945 (97.3) 26 (2.7) 1.9 (1.0 3.5) 0.62
Freckling in youth None 451 (95.4) 22 (4.6) 1018 (97.8) 23 (2.2) 2.3 (1.1, 4.5)
Some 673 (97.1) 20 (2.9) 1244 (97.9) 27 (2.1) 1.4 (0.7, 2.5) 0.22
Family History of Melanoma None 875 (96.2) 35 (3.8) 2051 (98.0) 42 (2.0) 1.9 (1.2, 3.2)
Present 251 (96.9) 8 (3.1) 288 (96.3) 11 (3.7) 0.8 (0.3, 2.1) 0.11
Personal History of NMSC None 588 (96.5) 21 (3.5) 1814 (97.9) 38 (2.1) 1.5 (0.7, 3.1)
Present 541 (96.1) 22 (3.9) 536 (97.3) 15 (2.7) 1.7 (0.9, 3.0) 0.96
MC1R No MC1R variant 146 (98.0) 3 (2.0) 363 (98.4) 6 (1.6) 1.09 (0.24, 4.99)
Any MCIR variant 903 (96.1) 37 (3.9) 1770 (97.6) 44 (2.4) 1.65 (1.01, 2.69) 0.55
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1

Odds ratio and 95% CI adjusted for age, sex, center and age*sex interaction.

The well-established effects of MC1R variants on risk of melanoma are similar to those we have found for MITF E318K, in being independent of the classical melanoma risk factors. Sturm et al. (2013) suggest the potential for an interaction between MC1R “R” variants and the MITF variant. However, we have found no evidence of such (either as the traditional “R” variants – D84E, R151C, R160W and D294H – or as these four, including R142H plus stop variants and indels that result in frameshifts and premature stop codons—or as “any” MC1R variant) with the presence of the MITF variant E318K. We also evaluated the role of such an interaction on pigmentation of the melanoma (amelanotic or pigmented) and found no association. It is likely that both have extra-pigmentary effects that are independent, and stronger in people with dark hair than those with light hair (Demenais et al., 2010; Kanetsky et al., 2011; Egan et al., 2003; Ozolo et al., 2013; Cust et al., 2012). These similarities are consistent with the fact that both genes act in the pathway from UV exposure to eumelanin production. The complexities of this pathway’s role in melanomagenesis merit further investigation.

The modification of effects of MCIR “R” variants and MITF E318K within strata of classical melanoma risk factors suggests that these genetic variants may also be valuable in predicting risk of melanoma in people without classical risk factors and that this information could help in public health and clinical prevention strategies.

Significance.

These relationships with melanoma risk factors suggest that MITF E318K is a genetic risk factor that may be valuable in predicting risk of melanoma in people without classic risk factors for melanoma such as fair hair and multiple nevi and that this information may help with public health and clinical prevention strategies.

Acknowledgments

This work was supported by the National Cancer Institute at the National Institutes of Health (UO1 CA83180, R01 CA112524, K05 CA131675 to M.B., R01 CA112243 and R01 CA 112243-0521 to N.E.T.).

GEM Study Group: Coordinating Center, Memorial Sloan-Kettering Cancer Center, New York, NY: Marianne Berwick, M.P.H., Ph.D. (Principal Investigator (PI), currently at the University of New Mexico), Colin B. Begg, Ph.D. (co-PI), Irene Orlow, Ph.D. (co-Investigator), Klaus J. Busam, M.D. (Dermatopathologist), Anne S. Reiner, M.P.H. (Biostatistician), Pampa Roy, Ph.D. (Laboratory Technician), Ajay Sharma, M.S. (Laboratory Technician). University of New Mexico, Albuquerque: Marianne Berwick, M.P.H., Ph.D. (PI), Li Luo, Ph.D. (Biostatistician), Kirsten White, MSc (Laboratory Manager), Susan Paine, M.P.H. (Data Manager). Study centers included the following: The University of Sydney and The Cancer Council New South Wales, Sydney, Australia: Bruce K. Armstrong M.B.B.S.; D.Phil., (PI), Anne Kricker, Ph.D. (co-PI), Anne Cust, Ph.D. (co-Investigator); Menzies Research Institute Tasmania, University of Tasmania, Hobart, Australia: Alison Venn, Ph.D. (current PI), Terence Dwyer, M.D. (PI, currently at International Agency for Research on Cancer, Lyon, France), Paul Tucker, M.D. (Dermatopathologist); British Columbia Cancer Research Centre, Vancouver, Canada: Richard P. Gallagher, M.A. (PI), Donna Kan (Coordinator); Cancer Care Ontario, Toronto, Canada: Loraine D. Marrett, Ph.D. (PI), Elizabeth Theis, M.Sc. (co-Investigator), Lynn From, M.D. (Dermatopathologist); CPO, Center for Cancer Prevention, Torino, Italy: Roberto Zanetti, M.D (PI), Stefano Rosso, M.D. (co-PI); University of California, Irvine, CA: Hoda Anton-Culver, Ph.D. (PI), Argyrios Ziogas, Ph.D. (Statistician); University of Michigan, Ann Arbor, MI: University of Michigan, Ann Arbor: Stephen B. Gruber, M.D., M.P.H., Ph.D. (PI, currently at University of Southern California, Los Angeles, CA), Timothy Johnson, M.D. (Director of Melanoma Program), Shu-Chen Huang, M.S., M.B.A. (co-Investigator, joint at USC-University of Michigan); New Jersey Department of Health, Trenton, NJ: Judith Klotz, Ph.D. (PI, currently retired), Homer Wilcox, Ph.D. (co-PI, currently retired), Lisa Paddock, Ph.D. (PI); University of North Carolina, Chapel Hill, NC: Nancy E. Thomas, M.D., Ph.D. (PI), Robert C. Millikan, Ph.D. (previous PI, deceased), David W. Ollila, M.D. (co-Investigator), Kathleen Conway, Ph.D. (co-Investigator), Pamela A. Groben, M.D. (Dermatopathologist), Sharon N. Edmiston, B.A. (Research Analyst), Honglin Hao (Laboratory Specialist), Eloise Parrish, MSPH (Laboratory Specialist), Jill S. Frank, M.S. (Research Assistant); University of Pennsylvania, Philadelphia, PA: Timothy R. Rebbeck, Ph.D. (PI), Peter A. Kanetsky, M.P.H., Ph.D. (co-Investigator); UV data consultants: Julia Lee Taylor, Ph.D. and Sasha Madronich, Ph.D., National Centre for Atmospheric Research, Boulder, CO.

Contributor Information

Marianne Berwick, University of New Mexico.

Jamie MacArthur, University of New Mexico.

Irene Orlow, Memorial Sloan-Kettering Cancer Center.

Peter Kanetsky, University of Pennsylvania.

Colin B. Begg, Memorial Sloan-Kettering Cancer Center

Li Luo, University of New Mexico.

Anne Reiner, Memorial Sloan-Kettering Cancer Center.

Ajay Sharma, Memorial Sloan-Kettering Cancer Center.

Bruce K. Armstrong, University of Sydney

Anne Kricker, University of Sydney.

Anne E. Cust, University of Sydney

Loraine D. Marrett, Cancercare Ontario

Stephen B. Gruber, University of Southern California

Hoda Anton-Culver, University of California, Irvine.

Roberto Zanetti, Piedmont Tumor Registry.

Stefano Rosso, Piedmont Tumor Registry.

Richard P. Gallagher, British Columbia Cancer Research Agency

Terrance Dwyer, International Agency for Cancer Research.

Alison Venn, Menzies Centre for Population Health, University of Tasmania.

Klaus Busam, Memorial Sloan-Kettering Cancer Center.

Lynn From, Children’s Hospital, Toronto.

Kirsten White, University of New Mexico.

Nancy E. Thomas, University of North Carolina

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