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Artykuł oryginalny

Zależność między polimorfizmami genu kodującego receptor witaminy D i ryzykiem wystąpienia czerniaka skóry – metaanaliza 40 badań kliniczno-kontrolnych

Seyed Mohammadreza Niktabar
Seyed Mojtaba Latifi
Mansour Moghimi
Jamal Jafari-Nedooshan
Kazem Aghili
Seyed Mohsen Miresmaeili
Masoud Zare-Shehneh
Hossein Neamatzadeh
5, 6

Department of Surgery, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
Department of Pathology, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
Department of Radiology, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
Department of Biology, Science and Arts University, Yazd, Iran
Department of Medical Genetics, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
Mother and Newborn Health Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
Dermatol Rev/Przegl Dermatol 2019, 106, 268–279
Data publikacji online: 2019/08/24
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Melanoma is a malignant skin cancer originating from the unregulated growth of melanocytes, which is responsible for over 70% of skin cancer deaths [1, 2]. Melanoma is a heterogeneous disease with different genetic alterations, and the modifications within the tumors and metastases make it difficult to target [3, 4]. The most dangerous aspect of melanoma is its ability, in later stages, to metastasize to other parts of the body [5]. In 2011, an estimated 166 900 new cases of melanoma will be diagnosed in developed countries [6].
In malignant melanoma, a number of mechanisms leading to neoplasia have been described [7]. Melanomas that occur in humans are usually deregulated in the RAS pathway, either by mutations or upregulation of surface receptors genes such as c-KIT and EGFR or by mutations in intracellular signaling genes such as NRAS, BRAF, and NF-1, which leads to elevated levels of activated ERK [8]. In addition to gene deletion and mutational alteration of protein activity, epigenetic alterations in DNA and histones have recently become a part of melanoma genetic aberrations [9]. Evidence is rapidly accumulating that low to moderate risk genes such as FTO, XRCC1, MC1R, MITF, ASIP, MTAP, PAX3, IL-10, IL-1β, TNF-α, IRF4, and VDR may play a central role in the pathobiology of melanoma [10–12].
There is evidence that vitamin D receptor (VDR) gene polymorphic variants such as FokI (rs10735810), BsmI (rs1544410), ApaI (rs7975232) and TaqI (rs731236) may contribute to the risk of melanoma in certain populations [13–15]. For example, the study by Zeljic et al. suggested that VDR polymorphisms might affect the melanoma risk in a Serbian population [16]. Vitamin D modulates immune cells’ activity through binding to the VDR, triggering innate and adaptive immune responses [17]. VDR is a ligand-dependent nuclear transcription factor, which plays an important role in maintaining calcium metabolism, and regulating cell proliferation and differentiation [18]. The VDR gene is situated at chromosome 12q13.11, which spans ~100 kb and has five promoters, eight coding exons, and six untranslated exons [15].
Although several epidemiological studies have assessed the association between the VDR gene polymorphisms and the risk of melanoma [11, 13, 15], the results are to some extent divergent and inconclusive, which may be due to limitations in individual studies. To gain better insight into the impact of VDR gene polymorphisms on the risk of melanoma, a meta-analysis with subgroup analysis from all published case-control studies was performed. Recently, increasing evidence has been accumulated to support the hypothesis that common genetic variations of the VDR gene may be of importance in determining an individual’s sensitivity to develop melanoma.

Material and methods

Study identification and selection

This meta-analysis conformed to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria. Two investigators independently searched the databases MEDLINE (PubMed), Google Scholar, Web of Science (Thomson-Reuters), Chinese National Knowledge Infrastructure (CNKI), the Chinese Wanfang Database, and the Chinese VIP Database for eligible articles examining the association of BsmI, TaqI, FokI, and ApaI polymorphisms of the VDR gene with risk of melanoma published up to March 10, 2018. The following terms were used: (“melanoma” OR “cutaneous melanoma” OR “skin cancer”’) AND (“vitamin D receptor” OR “VDR’’ OR “calcitriol receptor” OR “nuclear receptor subfamily 1” OR “NR1I1”) AND (“BsmI” OR “rs1544410” OR “+ 63980 G > A”) AND (“TaqI” OR “rs731236” OR “+65058 T>C”) AND (“FokI” OR “rs2228570” OR “+30920 C>T”) AND (“ApaI” OR “rs7975232” OR “+64978 C>A”) AND (“polymorphism”, OR “mutation” OR “variant” OR “gene” OR “genotype” OR “SNP” OR “allele”). In addition, hand searching of the references of eligible studies, reviews and related meta-analyses, and the abstracts presented at relevant conferences was performed to identify potentially relevant studies. If there were multiple reports of the same study or overlapping data, only the study with the largest sample sizes or the most recent one should be in the final analysis.

Inclusion and exclusion criteria

Studies were selected according to the following inclusion criteria: (1) full-text published studies up to March 10, 2018; (2) a case-control design or cohort design; (3) the study goal was to evaluate the association of VDR FokI C>T, BsmI G>A, TaqI T>C, EcoRV A>G, ApaI G>T and Cdx2 G>A polymorphisms with risk of melanoma; (4) sufficient data for estimating an odds ratio (OR) with 95% confidence interval (CI). The exclusion criteria were as follows: (1) studies with only case group (no control population), case reports, commentaries, and reviews; (2) studies without detailed genotype frequencies, which were unable to calculate OR.

Data extraction

Information was carefully extracted from all the eligible studies independently by two investigators using a pre-designed form according to the selection criteria listed above. For each study the following information was extracted: name of first author, publication year, country where the study was conducted, racial descent (categorized as Asian, Caucasian, or mixed descent), polymorphisms, genotypic testing method, number of cases and controls, genotype frequency of cases and controls, minor allele frequencies (MAFs) in control subjects, and result of Hardy-Weinberg equilibrium test in control subjects. Disagreements were resolved in consultation with the third reviewer.

Statistical analysis

The strength of associations was assessed using ORs and 95% CIs. The significance of the pooled effect size was determined by Z-tests, and p < 0.05 was considered statistically significant. The pooled ORs were calculated in five genetic models, including: allele model (B vs. A), homozygote model (BB vs. AA), heterozygote model (AB vs. AA), dominant model (BB + AB vs. AA), and recessive model (BB vs. AA + AB);
A represents the major allele and B represents the minor allele. All ORs for the five genetic models will be compared with each other, and the genetic model with the greatest OR and statistically significant result will be the inheritance model that is most likely to contribute to the risk of melanoma. Between-study heterogeneity was calculated through Cochran’s c2-based Q-statistic test. Moreover, the I2 statistic (ranging from 0 to 100%) was then used to quantitatively evaluate heterogeneity, with I2 = 0–25% indicating no heterogeneity, I2 = 25–50% indicating moderate heterogeneity, and I2 > 50% indicating large heterogeneity [19]. The p-value of < 0.05 for the Q-test indicated a lack of heterogeneity among studies, so that the pooled OR estimate of each study was calculated by the fixed-effects model (the Mantel–Haenszel method); otherwise the random effects model (the DerSimonian-Laird method) was used [20, 21]. Furthermore, to explore the source of between-study heterogeneity, subgroup analyses were performed. One-way sensitivity analyses were performed to survey the stability of the results; namely, a single study in the meta-analysis was omitted each time to reflect the influence of the individual data set to the pooled OR. Publication bias was assessed by visually examining the asymmetry of a funnel plot in which the log estimates were plotted against their standard errors. Furthermore, we also employed an Egger regression test in our analysis to calculate two-tailed p-values for quantifying publication bias [22, 23]. A Hardy-Weinberg equilibrium (HWE) test of the VDR gene polymorphisms in healthy subjects was examined using the c2 test. If the p-value > 0.05, the genotype distribution of the control group conformed to the HWE. All the statistical analyses were performed by comprehensive meta-analysis (CMA) version 2.0 software (Biostat, USA). All p-values were two sided and values less than 0.05 were considered significant.


Eligible studies

By searching online databases and references and related articles, 348 records were retrieved, among which 62 irrelevant papers were excluded due to duplication. After screening the titles and abstracts of the 286 articles, 138 articles were excluded because of obvious irrelevance. After systematically reading the full texts, we excluded another 126 articles. Finally, 40 eligible studies in twelve publications were included in the current meta-analysis. The study selection process is presented in detail in figure 1. There were eleven studies for FokI C>T polymorphism (4,581 cases and 4,226 controls) [16, 24–33], eight studies for TaqI T>C polymorphism (4,141 cases and 3,132 controls) [4, 16, 24, 29–31, 33, 34], eight studies for EcoRV A>G polymorphism (3,608 cases and 2,560 controls) [16, 26, 30, 32, 33, 35, 36], seven studies for BsmI G>A polymorphism (3,550 cases and 3,444 controls) [24, 25, 28–30, 37], three studies for ApaI G>T polymorphism (1,444 cases and 1,084 controls) [16, 30], and three studies for Cdx2 G>A polymorphism (1,546 cases and 1,835 controls) [28, 30]. All of the included studies were performed in Caucasian populations. The countries of these studies included the UK, Italy, the USA, Spain, Australia, and Serbia. Genotyping methods used in the studies included PCR-RFLP, real-time PCR, TaqMan, and sequencing. Other basic information, including the first author’s name, year of publication, ethnicity of the study population, number of cases and controls, source of controls, and genotyping methods are listed in table 1. All of the studies indicated that the distribution of genotypes in the controls was consistent with HWE, except one case-control study for ApaI G>T (table 1).

Meta-analysis results

The overall analyses suggested significant associations between the FokI C>T polymorphism and melanoma susceptibility in allele (T vs. C: OR = 1.097, 95% CI: 1.028–1.170; p = 0.005, fig. 1 A) and heterozygote (TC vs. CC: OR = 1.159, 95% CI: 1.054–1.275; p = 0.002) models, and clear evidence of associations was found between the BsmI G>A polymorphism and risk of melanoma in all genetic models (A vs. G: OR = 0.891, 95% CI: 0.829–0.958; p = 0.002; AA vs. GG: OR = 0.834, 95% CI: 0.717–0.971; p = 0.019; AG vs. GG: OR = 0.857, 95% CI: 0.768–0.956; p = 0.006; AA + AG vs. GG: OR = 0.570, 95% CI: 0.349–0.931; p = 0.027 and AA vs. AG + GG: OR = 0.713, 95% CI: 0.513–0.992; p = 0.045, fig. 1 B). However, no evidence of associations was detected between melanoma and three VDR polymorphisms (TaqI T>C, EcoRV A>G, and ApaI G>T) and melanoma susceptibility.
The studies were further stratified on the basis of genotyping method. When stratifying by genotyping technique, significantly increased associations between FokI C>T polymorphism and melanoma risk were found in the PCR-RFLP group under the heterozygote model (TC vs. CC: OR = 1.282, 95% CI: 1.079–1.522, p = 0.005) and the dominant model (TT + TC vs. CC: OR = 1.217, 95% CI: 1.033–1.433, p = 0.019); and in the AS-PCR group under the heterozygote model (TC vs. CC: OR = 1.127, 95% CI: 1.010–1.258, p = 0.032), but not in the TaqMan group. Moreover, there was a significant association between BsmI G>A polymorphism and melanoma in the PCR-RFLP group only under the heterozygote model (CA vs. AA: OR = 0.794, 95% CI: 0.654–0.964, p = 0.020). Meanwhile, no significantly increased risk of melanoma with other polymorphisms was found in the subgroup analyses by genotyping method (data not shown).

Evaluation of heterogeneity and sensitivity analysis

The Q-test and I2 statistic were employed to assess heterogeneity among the selected studies. However, heterogeneity was not found in the VDR polymorphisms. Therefore, a fixed effects model was applied to synthesize the data (table 1). Sensitivity analyses were performed to evaluate the robustness of the association results or the influence of each individual study on the pooled OR by sequential removal of individual studies. The results suggested that no individual study significantly affected the pooled OR, suggesting that the overall results of our meta-analysis were stable and credible to some extent.

Publication bias

Publication bias in the literature was qualitatively assessed by Begg’s funnel plot and quantitatively assessed by Egger’s test. Neither Begg’s funnel plot nor Egger’s test detected obvious evidence of publication bias in the overall and subgroup analyses for FokI C>T, BsmI G>A, ApaI G>T, and Cdx2 G>A polymorphisms in all genetic models (table 2). However, the shapes of the funnel plots displayed some asymmetry for TaqI T>C under the heterozygote model (CT vs. TT) and for EcoRV A>G under the homozygote (GG vs. AA) and the heterozygote (GA vs. AA) models, suggesting the presence of publication bias. Thus, Egger’s test was used to provide statistical evidence of funnel plot symmetry. The statistical results still show evidence of publication bias in these studies for TaqI T>C under the heterozygote model (PBeggs = 0.035, PEggers = 0.030) and for EcoRV A>G under the homozygote (PBeggs = 0.107, PEggers = 0.048) and the heterozygote (PBeggs = 0.035, PEggers = 0.031, fig. 2) models. To adjust for this bias, the trim-and-fill method developed by Duval and Tweedie was used to both identify and correct for funnel plot asymmetry arising from publication bias. Statistically similar data were obtained after trimming, indicating that our results were statistically reliable.

Minor allele frequencies (MAFs)

The minor allele frequencies (MAFs) of the VDR polymorphisms in the healthy subjects are presented in table 1. The allele and genotype distributions of VDR gene polymorphisms exhibited ethnic variations. The FokI T, TaqI C, EcoRV G, BsmI A, ApaI T, and Cdx2 A frequencies were 37.05% (31.40–42.70%), 37.40% (31.90–42.90%), 41.90% (35.10–48.70%), 42.90% (36.10–49.10%), 43.50% (40.50–46.50%), and 20.70% (19.90–21.50%), respectively.


Several studies have examined associations between VDR polymorphisms and melanoma risk, but the results were controversial. Meta-analysis has been recognized as an important tool to more precisely define the effect of genetic polymorphism on the risk of diseases. The present meta-analysis was carried out by critically reviewing 40 relevant and new recently published studies on VDR polymorphisms with melanoma risk. Therefore, it can provide more information.
Our meta-analysis showed that VDR FokI C>T and BsmI G>A polymorphism was associated with risk of melanoma. However, the analysis indicated that VDR TaqI T>C, EcoRV A>G, ApaI G>T, and Cdx2 G>A polymorphisms were not associated with risk of melanomas. In a meta-analysis, Iqbal et al. found that VDR BsmI, ApaI, and FokI polymorphisms may be risk factor for breast cancer [38]. The findings of Liu et al. suggest a significant association between TaqI and prostate cancer risk, but BsmI was not associated with prostate cancer [39]. Ou et al. reported that the ApaI, BsmI, and FokI polymorphisms were associated with the risk of renal cell carcinoma in Asians [40]. However, Sheng et al. reported that TaqI polymorphisms were significantly associated with susceptibility to colorectal cancer [41]. It is clear that different types of cancer have distinct initiation and progression mechanisms, in which VDR gene polymorphisms play critical roles.
According to the results, the exact mechanism for association between VDR polymorphisms and melanoma was not clear, and the carcinogenetic mechanism may also differ by VDR polymorphisms may exert varying effects in melanoma susceptibility. The discrepancy between previous results and the present findings may be attributed to the fact that the polymorphisms of the same gene may exert different genetic effects on different cancers. The inconsistent outcome for the effects of VDR polymorphisms on melanoma susceptibility is partly caused by genetic diversity in different ethnicities. Moreover, reasons for the conflicting results where VDR polymorphisms play different roles in melanoma susceptibility may be genetic heterogeneity in different populations and clinical heterogeneity in different studies. Potentially, differences in patient populations including gender difference and lifestyle might cause different results.
Heterogeneity plays an important role when performing a meta-analysis, and finding the source of heterogeneity is very important for the final result of the meta-analysis [42–46]. It is known that different factors, such as population stratification, source of controls, year of publication, sample size, diversity in design, genotyping methods, measurement errors, deviation from Hardy–Weinberg equilibrium, and other covariates, may contribute to common sources of heterogeneity [44, 47, 48]. In order to control heterogeneity between studies, we have applied inclusion criteria, but obvious between-study heterogeneity still existed in the overall population. Unluckily, the heterogeneity was not eliminated effectively, indicating that all the above factors should be taken into consideration.
Several potential limitations of the present meta-analysis should be acknowledged. First, limited studies have assessed the association of VDR polymorphisms with risk of melanoma in Asians. Therefore, we would refrain from generalizing these findings across populations. Studies with a larger sample size from other ethnicities should be performed in the future. In addition, few studies have been performed on TaqI T>C and EcoRV A>G polymorphisms with the risk of melanoma. Second, the sample size of the VDR ApaI G>T and Cdx2 G>A polymorphisms involved was not large enough. Therefore, they do not have adequate power to detect the possible association for these polymorphisms. Third, the current meta-analysis only included studies published in English or Chinese, and therefore some eligible studies written in other languages were not included. Thus, selection bias might have occurred at the beginning. Fourth, all the studies were conducted in Caucasians; therefore, the findings of the meta-analysis at present should be limited to Caucasians. Moreover, publication bias existed in the meta-analysis for TaqI T>C (the heterozygote model) and EcoRV A>G (the homozygote and heterozygote models) polymorphisms. For example, studies may not have been published if they reported a significant association between VDR polymorphism and risk of melanoma. The publication bias could cause the negative results. Fifth, our results were based on unadjusted estimates, while a more precise analysis should be conducted if individual data were available, which would allow for adjustment by other co-variants, including environmental factors and other lifestyle. Thus, more individual data required to draw a more precise conclusion. Finally, gene-gene, gene-environment or even the different polymorphism loci of the VDR gene interactions were not estimated in the current meta-analysis due to the insufficient data.
Despite these limitations, the current meta-analysis also had some advantages. First, we performed the most comprehensive and up-to-date meta-analysis with more VDR polymorphisms and articles than before, to better understand the association of VDR polymorphisms and melanoma susceptibility. Second, although possible publication bias was suggested between TaqI T>C and EcoRV A>G polymorphisms and risk of melanoma, adjusting for possible publication bias using the Duval and Tweedie nonparametric ”trim and fill” method showed that the results did not change, indicating that the whole pooled results should be unbiased.


The present study suggests a significant risk of melanoma associated with VDR FokI C>T and BsmI G>A polymorphisms, but not with TaqI T>C, EcoRV A>G, ApaI G>T, Cdx2 G>A polymorphisms. According to current findings, the exact mechanism for association between VDR polymorphisms and melanoma was not clear, and VDR polymorphisms may exert varying effects in the carcinogenetic mechanism of melanoma.
Considering the limitations mentioned above, further studies with a larger sample size and population-based studies, especially among Asians, are warranted to further confirm our findings and to explore the potential gene-gene and gene-environment interactions between the VDR gene polymorphisms and melanoma susceptibility.

Conflict of interest

The authors declare no conflict of interest.


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Copyright: © 2019 Polish Dermatological Association. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License (http://creativecommons.org/licenses/by-nc-sa/4.0/), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material, provided the original work is properly cited and states its license.
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