Background: Vitamin D serum levels have been found to be related to sun exposure and diet, together with cell differentiation, growth control and consequently, cancer risk. Vitamin D receptor (VDR) genotypes may influence cancer risk; however, no epidemiological studies in sporadic breast cancer (BC) or malignant melanoma (MM) have been performed in a southern European population. In this study, the VDR gene has been evaluated in two epithelial cancers BC and MM. Methods: We have conducted an analysis in 549 consecutive and non-related sporadic BC cases and 556 controls, all from the Spanish population, and 283 MM cases and 245 controls. Genotyping analyses were carried out on four putatively functional SNPs within the VDR gene. Results: An association with the minor allele A of the non-synonymous SNP rs2228570 (rs10735810, FokI, Met1Thr) was observed for BC, with an estimated odds ratio (OR) of 1.26 (95% CI = 1.02–1.57; p = 0.036). The synonymous variant rs731236 (TaqI) appeared to be associated with protection from BC (OR = 0.80, 95%CI = 0.64–0.99; p = 0.047). No statistically significant associations with MM were observed for any SNP. Nevertheless, sub-group analyses revealed an association between rs2228570 (FokI) and absence of childhood sunburns (OR = 0.65, p = 0.003), between the 3'utr SNP rs739837 (BglI) and fair skin (OR = 1.31, p = 0.048), and between the promoter SNP rs4516035 and the more aggressive tumour location in head-neck and trunk (OR = 1.54, p = 0.020). Conclusion: In summary, we observed associations between SNPs in the VDR gene and BC risk, and a comprehensive analysis using clinical and tumour characteristics as outcome variables has revealed potential associations with MM. These associations required confirmation in independent studies.

Background: Few high penetrance genes are known in Malignant Melanoma (MM), however, the involvement of low-penetrance genes such as MC1R, OCA2, ASIP, SLC45A2 and TYR has been observed. Lately, genome-wide association studies (GWAS) have been the ideal strategy to identify new common, low-penetrance susceptibility loci. In this case–control study, we try to validate in our population nine melanoma associated markers selected from published GWAS in melanoma predisposition. Methods: We genotyped the 9 markers corresponding to 8 genes (PARP1, MX2, ATM, CCND1, NADSYN1, CASP8, IRF4 and CYP2R1) in 566 cases and 347 controls from a Spanish population using KASPar probes. Genotypes were analyzed by logistic regression and adjusted by phenotypic characteristics. Results: We confirm the protective role in MM of the rs3219090 located on the PARP1 gene (p-value 0.027). Additionally, this SNP was also associated with eye color (p-value 0.002). A second polymorphism, rs12203592, located on the IRF4 gene was associated with protection to develop MM for the dominant model (p-value 0.037). We have also observed an association of this SNP with both lentigines (p-value 0.014) and light eye color (p-value 3.76 × 10^-4). Furthermore, we detected a novel association with rs1485993, located on the CCND1 gene, and dark eye color (p-value 4.96 × 10^-4). Finally, rs1801516, located on the ATM gene, showed a trend towards a protective role in MM similar to the one firstly described in a GWAS study. Conclusions: To our knowledge, this is the first time that these SNPs have been associated with MM in a Spanish population. We confirmed the proposed role of rs3219090, located on the PARP1 gene, and rs12203592, located on the IRF4 gene, as protective to MM along the same lines as have previous genome-wide associated works. Finally, we have seen associations between IRF4, PARP1, and CCND1 and phenotypic characteristics, confirming previous results for the IRF4 gene and presenting novel data for the last two, suggesting that pigmentation characteristics correlated with eye color are potential mediators between PARP1 and MM protection.

(1) Background: The purpose of this study was to evaluate the efficacy in terms of sensitivity, specificity, and accuracy of the quantusSKIN system, a new clinical tool based on deep learning, to distinguish between benign skin lesions and melanoma in a hospital population. (2) Methods: A retrospective study was performed using 232 dermoscopic images from the clinical database of the Ramón y Cajal University Hospital (Madrid, Spain). The skin lesions images, previously diagnosed as nevus (n = 177) or melanoma (n = 55), were analyzed by the quantusSKIN system, which offers a probabilistic percentage (diagnostic threshold) for melanoma diagnosis. The optimum diagnostic threshold, sensitivity, specificity, and accuracy of the quantusSKIN system to diagnose melanoma were quantified. (3) Results: The mean diagnostic threshold was statistically lower (p < 0.001) in the nevus group (27.12 ± 35.44%) compared with the melanoma group (72.50 ± 34.03%). The area under the ROC curve was 0.813. For a diagnostic threshold of 67.33%, a sensitivity of 0.691, a specificity of 0.802, and an accuracy of 0.776 were obtained. (4) Conclusions: The quantusSKIN system is proposed as a useful screening tool for melanoma detection to be incorporated in primary health care systems.