Updated field synopsis and systematic meta-analyses of genetic association studies in cutaneous melanoma: the MelGene database

A protocol for annotation of total body photography for machine learning to analyze skin phenotype and lesion classification

Introduction

Artificial Intelligence (AI) has proven effective in classifying skin cancers using dermoscopy images. In experimental settings, algorithms have outperformed expert dermatologists in classifying melanoma and keratinocyte cancers. However, clinical application is limited when algorithms are presented with 'untrained' or out-of-distribution lesion categories, often misclassifying benign lesions as malignant, or misclassifying malignant lesions as benign. Another limitation often raised is the lack of clinical context (e.g., medical history) used as input for the AI decision process. The increasing use of Total Body Photography (TBP) in clinical examinations presents new opportunities for AI to perform holistic analysis of the whole patient, rather than a single lesion. Currently there is a lack of existing literature or standards for image annotation of TBP, or on preserving patient privacy during the machine learning process.

Methods

This protocol describes the methods for the acquisition of patient data, including TBP, medical history, and genetic risk factors, to create a comprehensive dataset for machine learning. 500 patients of various risk profiles will be recruited from two clinical sites (Australia and Spain), to undergo temporal total body imaging, complete surveys on sun behaviors and medical history, and provide a DNA sample. This patient-level metadata is applied to image datasets using DICOM labels. Anonymization and masking methods are applied to preserve patient privacy. A two-step annotation process is followed to label skin images for lesion detection and classification using deep learning models. Skin phenotype characteristics are extracted from images, including innate and facultative skin color, nevi distribution, and UV damage. Several algorithms will be developed relating to skin lesion detection, segmentation and classification, 3D mapping, change detection, and risk profiling. Simultaneously, explainable AI (XAI) methods will be incorporated to foster clinician and patient trust. Additionally, a publicly released dataset of anonymized annotated TBP images will be released for an international challenge to advance the development of new algorithms using this type of data.

Conclusion

The anticipated results from this protocol are validated AI-based tools to provide holistic risk assessment for individual lesions, and risk stratification of patients to assist clinicians in monitoring for skin cancer.

Genetic testing for familial melanoma

While the average lifetime risk of melanoma worldwide is approximately 3%, those with inherited high-penetrance mutations face an increased lifetime risk of 52-84%. In countries of low melanoma incidence, such as in Southern Europe, familial melanoma genetic testing may be warranted when there are two first degree relatives with a melanoma diagnosis. Testing criteria for high incidence countries such as USA, or with very-high incidence, such as Australia and New Zealand, would require a threshold of 3 to 4 affected family members. A mutation in the most common gene associated with familial melanoma, CDKN2A, is identified in approximately 10-40% of those meeting testing criteria. However, the use of multi-gene panels covering additional less common risk genes can significantly increase the diagnostic yield. Currently, genetic testing for familial melanoma is typically conducted by qualified genetic counsellors, however with increasing demand on testing services and high incidence rate in certain countries, a mainstream model should be considered. With appropriate training, dermatologists are well placed to identify high risk individuals and offer melanoma genetic test in dermatology clinics. Genetic testing should be given in conjunction with pre- and post-test consultation. Informed patient consent should cover possible results, the limitations and implications of testing including inconclusive results, and potential for genetic discrimination. Previous studies reporting on participant outcomes of genetic testing for familial melanoma have found significant improvements in both sun protective behavior and screening frequency in mutation carriers.

Advancements in melanoma cancer metastasis models

Metastatic melanoma is a complex and deadly disease. Due to its complexity, the development of novel therapeutic strategies to inhibit metastatic melanoma remains an outstanding challenge. Our ability to study metastasis is advanced with the development of in vitro and in vivo models that better mimic the different steps of the metastatic cascade beginning from primary tumor initiation to final metastatic seeding. In this review, we provide a comprehensive summary of in vitro models, in vivo models, and in silico platforms to study the individual steps of melanoma metastasis. Furthermore, we highlight the advantages and limitations of each model and discuss the challenges of how to improve current models to enhance translation for melanoma cancer patients and future therapies.

A Comprehensive Analysis of Cutaneous Melanoma Patients in Greece Based on Multi-Omic Data

Cutaneous melanoma (CM) is the most aggressive type of skin cancer, and it is characterised by high mutational load and heterogeneity. In this study, we aimed to analyse the genomic and transcriptomic profile of primary melanomas from forty-six Formalin-Fixed, Paraffin-Embedded (FFPE) tissues from Greek patients. Molecular analysis for both germline and somatic variations was performed in genomic DNA from peripheral blood and melanoma samples, respectively, exploiting whole exome and targeted sequencing, and transcriptomic analysis. Detailed clinicopathological data were also included in our analyses and previously reported associations with specific mutations were recognised. Most analysed samples (43/46) were found to harbour at least one clinically actionable somatic variant. A subset of samples was profiled at the transcriptomic level, and it was shown that specific melanoma phenotypic states could be inferred from bulk RNA isolated from FFPE primary melanoma tissue. Integrative bioinformatics analyses, including variant prioritisation, differential gene expression analysis, and functional and gene set enrichment analysis by group and per sample, were conducted and molecular circuits that are implicated in melanoma cell programmes were highlighted. Integration of mutational and transcriptomic data in CM characterisation could shed light on genes and pathways that support the maintenance of phenotypic states encrypted into heterogeneous primary tumours.

Functional annotation and investigation of the 10q24.33 melanoma risk locus identifies a common variant that influences transcriptional regulation of OBFC1

The 10q24.33 locus is known to be associated with susceptibility to cutaneous malignant melanoma (CMM), but the mechanisms underlying this association have been not extensively investigated. We carried out an integrative genomic analysis of 10q24.33 using epigenomic annotations and in vitro reporter gene assays to identify regulatory variants. We found two putative functional single nucleotide polymorphisms (SNPs) in an enhancer and in the promoter of OBFC1, respectively, in neural crest and CMM cells, one, rs2995264, altering enhancer activity. The minor allele G of rs2995264 correlated with lower OBFC1 expression in 470 CMM tumors and was confirmed to increase the CMM risk in a cohort of 484 CMM cases and 1801 controls of Italian origin. Hi-C and chromosome conformation capture (3C) experiments showed the interaction between the enhancer-SNP region and the promoter of OBFC1 and an isogenic model characterized by CRISPR-Cas9 deletion of the enhancer-SNP region confirmed the potential regulatory effect of rs2995264 on OBFC1 transcription. Moreover, the presence of G-rs2995264 risk allele reduced the binding affinity of the transcription factor MEOX2. Biologic investigations showed significant cell viability upon depletion of OBFC1, specifically in CMM cells that were homozygous for the protective allele. Clinically, high levels of OBFC1 expression associated with histologically favorable CMM tumors. Finally, preliminary results suggested the potential effect of decreased OBFC1 expression on telomerase activity in tumorigenic conditions. Our results support the hypothesis that reduced expression of OBFC1 gene through functional heritable DNA variation can contribute to malignant transformation of normal melanocytes.

Citrus-Gene interaction and melanoma risk in the UK Biobank

High citrus consumption may increase melanoma risk; however, little is known about the biological mechanisms of this association, or whether it is modified by genetic variants. We conducted a genome-wide analysis of gene-citrus consumption interactions on melanoma risk among 1563 melanoma cases and 193 296 controls from the UK Biobank. Both the 2-degrees-of-freedom (df) joint test of genetic main effect and gene-environment (G-E) interaction and the standard 1-df G-E interaction test were performed. Three index SNPs (lowest P-value SNP among highly correlated variants [r²  > .6]) were identified from among the 365 genome-wide significant 2-df test results (rs183783391 on chromosome 3 [MITF], rs869329 on chromosome 9 [MTAP] and rs11446223 on chromosome 16 [DEF8]). Although all three were statistically significant for the 2-df test (4.25e-08, 1.98e-10 and 4.93e-13, respectively), none showed evidence of interaction according to the 1-df test (P = .73, .24 and .12, respectively). Eight nonindex, 2-df test significant SNPs on chromosome 16 were significant (P < .05) according to the 1-df test, providing evidence of citrus-gene interaction. Seven of these SNPs were mapped to AFG3L1P (rs199600347, rs111822773, rs113178244, rs3803683, rs73283867, rs78800020, rs73283871), and one SNP was mapped to GAS8 (rs74583214). We identified several genetic loci that may elucidate the association between citrus consumption and melanoma risk. Further studies are needed to confirm these findings.

An annotated dataset for extracting gene-melanoma relations from scientific literature

Background

Melanoma is one of the least common but the deadliest of skin cancers. This cancer begins when the genes of a cell suffer damage or fail, and identifying the genes involved in melanoma is crucial for understanding the melanoma tumorigenesis. Thousands of publications about human melanoma appear every year. However, while biological curation of data is costly and time-consuming, to date the application of machine learning for gene-melanoma relation extraction from text has been severely limited by the lack of annotated resources.

Results

To overcome this lack of resources for melanoma, we have exploited the information of the Melanoma Gene Database (MGDB, a manually curated database of genes involved in human melanoma) to automatically build an annotated dataset of binary relations between gene and melanoma entities occurring in PubMed abstracts. The entities were automatically annotated by state-of-the-art text-mining tools. Their annotation includes both the mention text spans and normalized concept identifiers. The relations among the entities were annotated at concept- and mention-level. The concept-level annotation was produced using the information of the genes in MGDB to decide if a relation holds between a gene and melanoma concept in the whole abstract. The exploitability of this dataset was tested with both traditional machine learning, and neural network-based models like BERT. The models were then used to automatically extract gene-melanoma relations from the biomedical literature. Most of the current models use context-aware representations of the target entities to establish relations between them. To facilitate researchers in their experiments we generated a mention-level annotation in support to the concept-level annotation. The mention-level annotation was generated by automatically linking gene and melanoma mentions co-occurring within the sentences that in MGDB establish the association of the gene with melanoma.

Conclusions

This paper presents a corpus containing gene-melanoma annotated relations. Additionally, it discusses experiments which show the usefulness of such a corpus for training a system capable of mining gene-melanoma relationships from the literature. Researchers can use the corpus to develop and compare their own models, and produce results which might be integrated with existing structured knowledge databases, which in turn might facilitate medical research.

A large Canadian cohort provides insights into the genetic architecture of human hair colour

Hair colour is a polygenic phenotype that results from differences in the amount and ratio of melanins located in the hair bulb. Genome-wide association studies (GWAS) have identified many loci involved in the pigmentation pathway affecting hair colour. However, most of the associated loci overlap non-protein coding regions and many of the molecular mechanisms underlying pigmentation variation are still not understood. Here, we conduct GWAS meta-analyses of hair colour in a Canadian cohort of 12,741 individuals of European ancestry. By performing fine-mapping analyses we identify candidate causal variants in pigmentation loci associated with blonde, red and brown hair colour. Additionally, we observe colocalization of several GWAS hits with expression and methylation quantitative trait loci (QTLs) of cultured melanocytes. Finally, transcriptome-wide association studies (TWAS) further nominate the expression of EDNRB and CDK10 as significantly associated with hair colour. Our results provide insights on the mechanisms regulating pigmentation biology in humans.

CDKN2A Polymorphism in Melanoma Patients in Colombian Population: A Case-Control Study

INTRODUCTION

Melanoma is the most aggressive type of skin cancer, with poor prognosis in advanced stages. The incidence and mortality rates have increased in recent years. Single nucleotide polymorphisms p.R24P, p.M53I, p.G101W, p.V126D, and p.A148T in the CDKN2A (HGNC ID: 1787) gene have been associated with the development of melanoma in different populations; however, this association has not been studied in Colombia.

METHODS

Cutaneous melanoma patients and healthy controls (85 cases and 166 controls) were included in this study. These subjects were screened through HRM-qPCR assay and detected variants in exon 1 and 2 of CDKN2A gene and confirmed with Sanger sequencing. Chi-square test was used to compare allele and genotype distributions between cases and controls. Odds ratio (OR) with 95% confidence interval (CI) was calculated to determine the association between polymorphisms and haplotypes with melanoma susceptibility. Statistical and haplotype analyses were performed using Stata® and R-Studio®.

RESULTS

Fifty-four percent of women were identified both in cases and controls. The frequencies of melanoma subtypes were 36,47% lentigo maligna, 24,71% acral lentiginous, 23,53% superficial extension, and 15,29% nodular. Variants in the CDKN2A gene were 11.76% in cases and 8.43% in controls. The most frequent was p.A148T in 5.88% of cases and in 4.82% of controls. GGTTG haplotype showed statistically significant differences between cases and controls (p value = 0.04).

CONCLUSION

CDKN2A polymorphisms p.G101W, p.R24P, p.M53I, and A148T are not associated with melanoma susceptibility in the Colombian population; further studies regarding genetic interaction and additive effects between more variants are required.

Computational models of melanoma

Genes, proteins, or cells influence each other and consequently create patterns, which can be increasingly better observed by experimental biology and medicine. Thereby, descriptive methods of statistics and bioinformatics sharpen and structure our perception. However, additionally considering the interconnectivity between biological elements promises a deeper and more coherent understanding of melanoma. For instance, integrative network-based tools and well-grounded inductive in silico research reveal disease mechanisms, stratify patients, and support treatment individualization. This review gives an overview of different modeling techniques beyond statistics, shows how different strategies align with the respective medical biology, and identifies possible areas of new computational melanoma research.

Genome-wide association meta-analyses combining multiple risk phenotypes provide insights into the genetic architecture of cutaneous melanoma susceptibility

Most genetic susceptibility to cutaneous melanoma remains to be discovered. Meta-analysis genome-wide association study (GWAS) of 36,760 cases of melanoma (67% newly genotyped) and 375,188 controls identified 54 significant (P < 5 × 10-8) loci with 68 independent single nucleotide polymorphisms. Analysis of risk estimates across geographical regions and host factors suggests the acral melanoma subtype is uniquely unrelated to pigmentation. Combining this meta-analysis with GWAS of nevus count and hair color, and transcriptome association approaches, uncovered 31 potential secondary loci for a total of 85 cutaneous melanoma susceptibility loci. These findings provide insights into cutaneous melanoma genetic architecture, reinforcing the importance of nevogenesis, pigmentation and telomere maintenance, together with identifying potential new pathways for cutaneous melanoma pathogenesis.

Evolution of approaches to identify melanoma missing heritability

Introduction: Around 10% of melanoma patients have a positive family history of melanoma and/or related cancers. Although a germline pathogenic variant in a high-risk gene can be identified in up to 40% of these patients, the remaining part of melanoma heritability remains largely unexplained.Areas covered: The aim of this review is to provide an overview of the impact that new technologies and new research approaches had and are having on finding more efficient ways to unravel the missing heritability in melanoma.Expert opinion: High-throughput sequencing technologies have been crucial in increasing the number of genes/loci that might be implicated in melanoma predisposition. However, results from these approaches may have been inferior to the expectations, due to an increase in quantitative information which hasn't been followed at the same speed by an improvement of the methods to correctly interpret these data. Optimal approaches for improving our knowledge on melanoma heritability are currently based on segregation analysis coupled with functional assessment of candidate genes. An improvement of computational methods to infer genotype-phenotype correlations could help address the issue of missing heritability.

The complementary effect of rs1042522 in TP53 and rs1805007 in MC1R is associated with an elevated risk of cutaneous melanoma in Latvian population

Genetic factors serve important roles in melanoma susceptibility. Although much genetic variation has been associated with cutaneous melanoma (CM), little is known about the interactions between genetic variants. The current study investigated the joint effect of rs1042522 in the tumour protein 53 (TP53) gene, rs2279744 in the murine double minute-2 (MDM2) gene and several single nucleotide polymorphisms (SNPs) in the melanocortin 1 receptor (MC1R) gene. All of these genes are interconnected in a single signalling pathway that regulates pigmentation. The current study included 479 individuals, of which, 255 were patients with CM and 224 were controls from the Latvian population. Multifaceted analyses of potential interactions between SNPs were performed, whilst taking into account the pigmentation phenotypes of individuals and tumour characteristics (Breslow thickness and ulceration). Univariate analyses revealed a borderline significant association between rs1042522 in the TP53 gene and CM risk. The results also confirmed a known association with rs1805007 in the MC1R gene. The rs1042522 was also selected as a CM risk factor in multivariate models, suggesting an effect that is independent from and complementary to that of rs1805007. The results indicated that these SNPs need to be taken into account when determining melanoma risk. A strong association between CM and red hair was identified for rs1805007, and rs1805008 in the MC1R gene was mainly associated with red hair. An association was also determined between rs2279744 in the MDM2 gene and brown eye colour. No convincing associations were identified between the analysed SNPs and Breslow thickness of tumours or ulcerations.

Genome-wide association studies and polygenic risk scores for skin cancer: clinically useful yet?

BACKGROUND

Genome-wide association studies (GWAS) have identified thousands of susceptibility variants, although most have been associated with small individual risk estimates that offer little predictive value. However, combining multiple variants into polygenic risk scores (PRS) may be more informative. Multiple studies have developed PRS composed of GWAS-identified variants for cutaneous cancers. This review highlights data from these studies.

OBJECTIVES

To review published GWAS and PRS studies for melanoma, cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC), and discuss their potential clinical utility.

METHODS

We searched PubMed and the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue to identify relevant studies.

RESULTS

Results from 21 GWAS (11 melanoma, 3 cSCC, 7 BCC) and 11 PRS studies are summarized. Six loci in pigmentation genes overlap between these three cancers (ASIP/RALY, IRF4, MC1R, OCA2, SLC45A2 and TYR). Additional loci overlap for cSCC/BCC and BCC/melanoma, but no other loci are shared between cSCC and melanoma. PRS for melanoma show roughly two-to-threefold increases in risk and modest improvements in risk prediction (2-7% increases). PRS are associated with twofold and threefold increases in risk of cSCC and BCC, respectively, with small improvements (2% increase) in predictive ability.

CONCLUSIONS

Existing data indicate that PRS may offer small, but potentially meaningful, improvements to risk prediction. Additional research is needed to clarify the potential utility of PRS in cutaneous carcinomas. Clinical translation will require well-powered validation studies incorporating known risk factors to evaluate PRS as tools for screening. What's already known about this topic? Over 50 susceptibility loci for melanoma, basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC) have been identified in genome-wide association studies (GWAS). Polygenic risk scores (PRS) using variants identified from GWAS have also been developed for melanoma, BCC and cSCC, and investigated with respect to clinical risk prediction. What does this study add? This review provides an overview of GWAS findings and the potential clinical utility of PRS for melanoma, BCC and cSCC.

Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches

Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcriptomics and proteomics to epigenomics, pharmacogenomics, metagenomics and metabolomics. Systems Bioinformatics is the framework in which systems approaches are applied to such data, setting the level of resolution as well as the boundary of the system of interest and studying the emerging properties of the system as a whole rather than the sum of the properties derived from the system's individual components. A key approach in Systems Bioinformatics is the construction of multiple networks representing each level of the omics spectrum and their integration in a layered network that exchanges information within and between layers. Here, we provide evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine. The aim of this review is to familiarize the reader with the emerging field of Systems Bioinformatics and to provide a comprehensive overview of its current state-of-the-art methods and technologies. Moreover, we provide examples of success stories and case studies that utilize such methods and tools to significantly advance research in the fields of systems biology and systems medicine.

The ancient sarcomeric myosins found in specialized muscles

Striated muscles express an array of sarcomeric myosin motors that are tuned to accomplish specific tasks. Each myosin isoform found in muscle fibers confers unique contractile properties to the fiber in order to meet the demands of the muscle. The sarcomeric myosin heavy chain (MYH) genes expressed in the major cardiac and skeletal muscles have been studied for decades. However, three ancient myosins, MYH7b, MYH15, and MYH16, remained uncharacterized due to their unique expression patterns in common mammalian model organisms and due to their relatively recent discovery in these genomes. This article reviews the literature surrounding these three ancient sarcomeric myosins and the specialized muscles in which they are expressed. Further study of these ancient myosins and how they contribute to the functions of the specialized muscles may provide novel insight into the history of striated muscle evolution.

Identification of cancer-related potential biomarkers based on lncRNA-pseudogene-mRNA competitive networks

Accumulating evidence indicates that mRNAs and noncoding RNAs act as competitive endogenous RNAs (ceRNAs) and play a key role in tumorigenesis. However, the complex competitive relationship among genes remains unknown. In the present study, the long noncoding RNAs (lncRNAs), pseudogenes and mRNAs that compete with common microRNAs are defined as lncRNA-pseudogene-mRNA competitive triples. We find that some candidate ceRNAs, modules and triples are associated with cancers and can significantly divide patients into high-risk and low-risk groups; thus, they may serve as potential cancer biomarkers. In sum, the present study systematically analyzes the association between competitive triples and cancer, which provides a reference for a deeper understanding of cancer progression.

The awakening of the CDK10/Cyclin M protein kinase

Cyclin-dependent kinases (CDKs) play important roles in the control of fundamental cellular processes. Some of the most characterized CDKs are considered to be pertinent therapeutic targets for cancers and other diseases, and first clinical successes have recently been obtained with CDK inhibitors. Although discovered in the pre-genomic era, CDK10 attracted little attention until it was identified as a major determinant of resistance to endocrine therapy for breast cancer. In some studies, CDK10 has been shown to promote cell proliferation whereas other studies have revealed a tumor suppressor function. The recent discovery of Cyclin M as a CDK10 activating partner has allowed the unveiling of a protein kinase activity against the ETS2 oncoprotein, whose degradation is activated by CDK10/Cyclin M-mediated phosphorylation. CDK10/Cyclin M has also been shown to repress ciliogenesis and to maintain actin network architecture, through the phoshorylation of the PKN2 protein kinase and the control of RhoA stability. These findings shed light on the molecular mechanisms underlying STAR syndrome, a severe human developmental genetic disorder caused by mutations in the Cyclin M coding gene. They also pave the way to a better understanding of the role of CDK10/Cyclin M in cancer.

Dissecting the Mutational Landscape of Cutaneous Melanoma: An Omic Analysis Based on Patients from Greece

Melanoma is a lethal type of skin cancer, unless it is diagnosed early. Formalin-fixed, paraffin-embedded (FFPE) tissue is a valuable source for molecular assays after diagnostic examination, but isolated nucleic acids often suffer from degradation. Here, for the first time, we examine primary melanomas from Greek patients, using whole exome sequencing, so as to derive their mutational profile. Application of a bioinformatic framework revealed a total of 10,030 somatic mutations. Regarding the genes containing putative protein-altering mutations, 73 were common in at least three patients. Sixty-five of these 73 top common genes have been previously identified in melanoma cases. Biological processes related to melanoma were affected by varied genes in each patient, suggesting differences in the components of a pathway possibly contributing to pathogenesis. We performed a multi-level analysis highlighting a short list of candidate genes with a probable causative role in melanoma.

Recurrent, low-frequency coding variants contributing to colorectal cancer in the Swedish population

Genome-wide association studies (GWAS) have identified dozens of common genetic variants associated with risk of colorectal cancer (CRC). However, the majority of CRC heritability remains unclear. In order to discover low-frequency, high-risk CRC susceptibility variants in Swedish population, we genotyped 1 515 CRC patients enriched for familial cases, and 12 108 controls. Case/control association analysis suggested eight novel variants associated with CRC risk (OR 2.0-17.6, p-value < 2.0E-07), comprised of seven coding variants in genes RAB11FIP5, POTEA, COL27A1, MUC5B, PSMA8, MYH7B, and PABPC1L as well as one variant downstream of NEU1 gene. We also confirmed 27 out of 30 risk variants previously reported from GWAS in CRC with a mixed European population background. This study identified rare, coding sequence variants associated with CRC risk through analysis in a relatively homogeneous population. The segregation data suggest a complex mode of inheritance in seemingly dominant pedigrees.

A GWAS in uveal melanoma identifies risk polymorphisms in the CLPTM1L locus

Uveal melanoma, a rare malignant tumor of the eye, is predominantly observed in populations of European ancestry. A genome-wide association study of 259 uveal melanoma patients compared to 401 controls all of European ancestry revealed a candidate locus at chromosome 5p15.33 (region rs421284: OR = 1.7, CI 1.43-2.05). This locus was replicated in an independent set of 276 cases and 184 controls. In addition, risk variants from this region were positively associated with higher expression of CLPTM1L. In conclusion, the CLPTM1L region contains risk alleles for uveal melanoma susceptibility, suggesting that CLPTM1L could play a role in uveal melanoma oncogenesis.

Non-genetic risk factors for cutaneous melanoma and keratinocyte skin cancers: An umbrella review of meta-analyses

BACKGROUND

Skin cancers have a complex disease mechanism, involving both genetic and non-genetic risk factors. Numerous meta-analyses have been published claiming statistically significant associations between non-genetic risk factors and skin cancers without applying a thorough methodological assessment.

OBJECTIVE

The present study maps the literature on the non-genetic risk factors of skin cancers, assesses the presence of statistical biases and identifies the associations with robust evidence.

METHODS

We searched PubMed up to January 20, 2016 to identify systematic reviews and meta-analyses of observational studies that examined associations between non-genetic factors and skin cancers. For each meta-analysis, we estimated the summary effect size by random-effects and fixed-effects models, the 95% confidence interval and the 95% prediction interval. We also assessed the between-study heterogeneity (I2 metric), evidence for small-study effects and excess significance bias.

RESULTS

Forty-four eligible papers were identified and included a total of 85 associations. Twenty-one associations were significant at P<10-6. Fifty-two associations had large or very large heterogeneity. Evidence for small-study effects and excess significance bias was found in fifteen and thirteen associations, respectively. Overall, thirteen associations (actinic keratosis, serum vitamin D, sunburns, and hair color for basal cell carcinoma and density of freckles, eye color, hair color, history of melanoma, skin type, sunburns, premalignant skin lesions, common and atypical nevi for melanoma) presented high level of credibility.

CONCLUSION

The majority of meta-analyses on non-genetic risk factors for skin cancers suffered from large between-study heterogeneity and small-study effects or excess significance bias. The associations with convincing and highly suggestive evidence were mainly focused on skin photosensitivity and phenotypic characteristics.

Independent Loss of Methylthioadenosine Phosphorylase (MTAP) in Primary Cutaneous T-Cell Lymphoma

Methylthioadenosine phosphorylase (MTAP) and the tumor suppressor genes CDKN2A-CDKN2B are frequently deleted in malignancies. The specific role of MTAP in cutaneous T-cell lymphoma subgroups, mycosis fungoides (MF) and Sézary syndrome (SS), is unknown. In 213 skin samples from patients with MF/SS, MTAP copy number loss (34%) was more frequent than CDKN2A (12%) in all cutaneous T-cell lymphoma stages using quantitative reverse transcription PCR. Importantly, in early stage MF, MTAP loss occurred independently of CDKN2A loss in 37% of samples. In peripheral blood mononuclear cells from patients with SS, codeletion with CDKN2A occurred in 18% of samples but loss of MTAP alone was uncommon. In CD4(+) cells from SS, reduced MTAP mRNA expression correlated with MTAP copy number loss (P < 0.01) but reduced MTAP expression was also detected in the absence of copy number loss. Deep sequencing of MTAP/CDKN2A-CDKN2B loci in 77 peripheral blood mononuclear cell DNA samples from patients with SS did not show any nonsynonymous mutations, but read-depth analysis suggested focal deletions consistent with MTAP and CDKN2A copy number loss detected with quantitative reverse transcription PCR. In a cutaneous T-cell lymphoma cell line, promoter hypermethylation was shown to downregulate MTAP expression and may represent a mechanism of MTAP inactivation. In conclusion, our findings suggest that there may be selection in early stages of MF for MTAP deletion within the cutaneous tumor microenvironment.

Prediction of Melanoma Risk in a Southern European Population Based on a Weighted Genetic Risk Score

Many single nucleotide polymorphisms (SNPs) have been described as putative risk factors for melanoma. The aim of our study was to validate the most prominent genetic risk loci in an independent Greek melanoma case-control dataset and to assess their cumulative effect solely or combined with established phenotypic risk factors on individualized risk prediction. We genotyped 59 SNPs in 800 patients and 800 controls and tested their association with melanoma using logistic regression analyses. We constructed a weighted genetic risk score (GRSGWS) based on SNPs that showed genome-wide significant (GWS) association with melanoma in previous studies and assessed their impact on risk prediction. Fifteen independent SNPs from 12 loci were significantly associated with melanoma (P < 0.05). Risk score analysis yielded an odds ratio of 1.36 per standard deviation increase of the GRSGWS (P = 1.1 × 10(-7)). Individuals in the highest 20% of the GRSGWS had a 1.88-fold increase in melanoma risk compared with those in the middle quintile. By adding the GRSGWS to a phenotypic risk model, the C-statistic increased from 0.764 to 0.775 (P = 0.007). In summary, the GRSGWS is associated with melanoma risk and achieves a modest improvement in risk prediction when added to a phenotypic risk model.

Genome-wide meta-analysis identifies five new susceptibility loci for cutaneous malignant melanoma

Thirteen common susceptibility loci have been reproducibly associated with cutaneous malignant melanoma (CMM). We report the results of an international 2-stage meta-analysis of CMM genome-wide association studies (GWAS). This meta-analysis combines 11 GWAS (5 previously unpublished) and a further three stage 2 data sets, totaling 15,990 CMM cases and 26,409 controls. Five loci not previously associated with CMM risk reached genome-wide significance (P < 5 × 10(-8)), as did 2 previously reported but unreplicated loci and all 13 established loci. Newly associated SNPs fall within putative melanocyte regulatory elements, and bioinformatic and expression quantitative trait locus (eQTL) data highlight candidate genes in the associated regions, including one involved in telomere biology.

Genetic epidemiology of malignant melanoma susceptibility

Germline CDKN2A mutations were the first to be associated with familial melanoma. MC1R polymorphisms are associated, in conformity with epidemiological observations, with fair skin phenotype and a moderately increased risk for melanoma. The wider implementation of genome-wide association studies along with improved whole exome sequencing techniques made possible the identification of novel high-penetrant mutations (TERT, MITF, POT1, BAP1) beyond the established pathways of pigmentation and nevus count suggesting an additional role for pathways involved in cell cycle control and DNA repair. A multitude of common polymorphisms in the general population have been associated through candidate gene studies with a low risk for melanoma, supporting the hypothesis of a complex disease.