Melanocortin-1 receptor, skin cancer and phenotypic characteristics (M-SKIP) project: study design and methods for pooling results of genetic epidemiological studies

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.

Extended two-stage designs for environmental research

BACKGROUND

The two-stage design has become a standard tool in environmental epidemiology to model multi-location data. However, its standard form is rather inflexible and poses important limitations for modelling complex risks associated with environmental factors. In this contribution, we illustrate multiple design extensions of the classical two-stage method, all implemented within a unified analytic framework.

METHODS

We extended standard two-stage meta-analytic models along the lines of linear mixed-effects models, by allowing location-specific estimates to be pooled through flexible fixed and random-effects structures. This permits the analysis of associations characterised by combinations of multivariate outcomes, hierarchical geographical structures, repeated measures, and/or longitudinal settings. The analytic framework and inferential procedures are implemented in the R package mixmeta.

RESULTS

The design extensions are illustrated in examples using multi-city time series data collected as part of the National Morbidity, Mortality and Air Pollution Study (NMMAPS). Specifically, four case studies demonstrate applications for modelling complex associations with air pollution and temperature, including non-linear exposure-response relationships, effects clustered at multiple geographical levels, differential risks by age, and effect modification by air conditioning in a longitudinal analysis.

CONCLUSIONS

The definition of several design extensions of the classical two-stage design within a unified framework, along with its implementation in freely-available software, will provide researchers with a flexible tool to address novel research questions in two-stage analyses of environmental health risks.

Melanoma in children and adolescents: analysis of susceptibility genes in 123 Italian patients

BACKGROUND

A polygenic inheritance involving high, medium and low penetrance genes has been suggested for melanoma susceptibility in adults, but genetic information is scarce for paediatric patients.

OBJECTIVE

We aim to analyse the major high and intermediate melanoma risk genes, CDKN2A, CDK4, POT1, MITF and MC1R, in a large multicentre cohort of Italian children and adolescents in order to explore the genetic context of paediatric melanoma and to reveal potential differences in heritability between children and adolescents.

METHODS

One-hundred-twenty-three patients (<21 years) from nine Italian centres were analysed for the CDKN2A, CDK4, POT1, MITF, and MC1R melanoma predisposing genes. The rate of gene variants was compared between sporadic, familial and multiple melanoma patients and between children and adolescents, and their association with clinico-pathological characteristics was evaluated.

RESULTS

Most patients carried MC1R variants (67%), while CDKN2A pathogenic variants were found in 9% of the cases, the MITF E318K in 2% of patients and none carried CDK4 or the POT1 S270N pathogenic variant. Sporadic melanoma patients significantly differed from familial and multiple cases for the young age at diagnosis, infrequent red hair colour, low number of nevi, low frequency of CDKN2A pathogenic variants and of the MC1R R160W variant. Melanoma in children (≤12 years) had more frequently spitzoid histotype, were located on the head/neck and upper limbs and had higher Breslow thickness. The MC1R V92M variant was more common in children than in adolescents. CDKN2A common polymorphisms and MC1R variants were associated with a high number of nevi.

CONCLUSION

Our results confirm the scarce involvement of the major high-risk susceptibility genes in paediatric melanoma and suggest the implication of MC1R gene variants especially in the children population.

MC1R variants and cutaneous melanoma risk according to histological type, body site, and Breslow thickness: a pooled analysis from the M-SKIP project

Little is known on whether melanocortin 1 receptor (MC1R) associated cutaneous melanoma (CM) risk varies depending on histological subtype and body site, and whether tumour thickness at diagnosis (the most important prognostic factor for CM patients) differs between MC1R variant carriers and wild-type individuals. We studied the association between MC1R variants and CM risk by histological subtype, body site, and Breslow thickness, using the database of the M-SKIP project. We pooled individual data from 15 case-control studies conducted during 2005-2015 in Europe and the USA. Study-specific, multi-adjusted odds ratios were pooled into summary odds ratios (SOR) and 95% confidence intervals (CI) using random-effects models. Six thousand eight hundred ninety-one CM cases and 5555 controls were included. CM risk was increased among MC1R variant carriers vs. wild-type individuals. The increase in risk was comparable across histological subtypes (SOR for any variant vs. wild-type ranged between 1.57 and 1.70, always statistical significant) except acral lentiginous melanoma (ALM), for which no association emerged; and slightly greater on chronically (1.74, 95% CI 1.47-2.07) than intermittently (1.55, 95% CI 1.34-1.78) sun-exposed skin. CM risk was greater for those carrying 'R' vs. 'r' variants; correlated with the number of variants; and was more evident among individuals not showing the red hair colour phenotype. Breslow thickness was not associated with MC1R status. MC1R variants were associated with an increased risk of CM of any histological subtype (except ALM) and occurring on both chronically and intermittently sun-exposed skin.

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.

Identification of interactions of binary variables associated with survival time using survivalFS

Many medical studies aim to identify factors associated with a time to an event such as survival time or time to relapse. Often, in particular, when binary variables are considered in such studies, interactions of these variables might be the actual relevant factors for predicting, e.g., the time to recurrence of a disease. Testing all possible interactions is often not possible, so that procedures such as logic regression are required that avoid such an exhaustive search. In this article, we present an ensemble method based on logic regression that can cope with the instability of the regression models generated by logic regression. This procedure called survivalFS also provides measures for quantifying the importance of the interactions forming the logic regression models on the time to an event and for the assessment of the individual variables that take the multivariate data structure into account. In this context, we introduce a new performance measure, which is an adaptation of Harrel's concordance index. The performance of survivalFS and the proposed importance measures is evaluated in a simulation study as well as in an application to genotype data from a urinary bladder cancer study. Furthermore, we compare the performance of survivalFS and its importance measures for the individual variables with the variable importance measure used in random survival forests, a popular procedure for the analysis of survival data. These applications show that survivalFS is able to identify interactions associated with time to an event and to outperform random survival forests.

MC1R variants as melanoma risk factors independent of at-risk phenotypic characteristics: a pooled analysis from the M-SKIP project

PURPOSE

Melanoma represents an important public health problem, due to its high case-fatality rate. Identification of individuals at high risk would be of major interest to improve early diagnosis and ultimately survival. The aim of this study was to evaluate whether MC1R variants predicted melanoma risk independently of at-risk phenotypic characteristics.

MATERIALS AND METHODS

Data were collected within an international collaboration - the M-SKIP project. The present pooled analysis included data on 3,830 single, primary, sporadic, cutaneous melanoma cases and 2,619 controls from seven previously published case-control studies. All the studies had information on MC1R gene variants by sequencing analysis and on hair color, skin phototype, and freckles, ie, the phenotypic characteristics used to define the red hair phenotype.

RESULTS

The presence of any MC1R variant was associated with melanoma risk independently of phenotypic characteristics (OR 1.60; 95% CI 1.36-1.88). Inclusion of MC1R variants in a risk prediction model increased melanoma predictive accuracy (area under the receiver-operating characteristic curve) by 0.7% over a base clinical model (P=0.002), and 24% of participants were better assessed (net reclassification index 95% CI 20%-30%). Subgroup analysis suggested a possibly stronger role of MC1R in melanoma prediction for participants without the red hair phenotype (net reclassification index: 28%) compared to paler skinned participants (15%).

CONCLUSION

The authors suggest that measuring the MC1R genotype might result in a benefit for melanoma prediction. The results could be a valid starting point to guide the development of scientific protocols assessing melanoma risk prediction tools incorporating the MC1R genotype.

MC1R gene variants and non-melanoma skin cancer: a pooled-analysis from the M-SKIP project

BACKGROUND

The melanocortin-1-receptor (MC1R) gene regulates human pigmentation and is highly polymorphic in populations of European origins. The aims of this study were to evaluate the association between MC1R variants and the risk of non-melanoma skin cancer (NMSC), and to investigate whether risk estimates differed by phenotypic characteristics.

METHODS

Data on 3527 NMSC cases and 9391 controls were gathered through the M-SKIP Project, an international pooled-analysis on MC1R, skin cancer and phenotypic characteristics. We calculated summary odds ratios (SOR) with random-effect models, and performed stratified analyses.

RESULTS

Subjects carrying at least one MC1R variant had an increased risk of NMSC overall, basal cell carcinoma (BCC) and squamous cell carcinoma (SCC): SOR (95%CI) were 1.48 (1.24-1.76), 1.39 (1.15-1.69) and 1.61 (1.35-1.91), respectively. All of the investigated variants showed positive associations with NMSC, with consistent significant results obtained for V60L, D84E, V92M, R151C, R160W, R163Q and D294H: SOR (95%CI) ranged from 1.42 (1.19-1.70) for V60L to 2.66 (1.06-6.65) for D84E variant. In stratified analysis, there was no consistent pattern of association between MC1R and NMSC by skin type, but we consistently observed higher SORs for subjects without red hair.

CONCLUSIONS

Our pooled-analysis highlighted a role of MC1R variants in NMSC development and suggested an effect modification by red hair colour phenotype.

MC1R variants increased the risk of sporadic cutaneous melanoma in darker-pigmented Caucasians: a pooled-analysis from the M-SKIP project

The MC1R gene is a key regulator of skin pigmentation. We aimed to evaluate the association between MC1R variants and the risk of sporadic cutaneous melanoma (CM) within the M-SKIP project, an international pooled-analysis on MC1R, skin cancer and phenotypic characteristics. Data included 5,160 cases and 12,119 controls from 17 studies. We calculated a summary odds ratio (SOR) for the association of each of the nine most studied MC1R variants and of variants combined with CM by using random-effects models. Stratified analysis by phenotypic characteristics were also performed. Melanoma risk increased with presence of any of the main MC1R variants: the SOR for each variant ranged from 1.47 (95%CI: 1.17-1.84) for V60L to 2.74 (1.53-4.89) for D84E. Carriers of any MC1R variant had a 66% higher risk of developing melanoma compared with wild-type subjects (SOR; 95%CI: 1.66; 1.41-1.96) and the risk attributable to MC1R variants was 28%. When taking into account phenotypic characteristics, we found that MC1R-associated melanoma risk increased only for darker-pigmented Caucasians: SOR (95%CI) was 3.14 (2.06-4.80) for subjects with no freckles, no red hair and skin Type III/IV. Our study documents the important role of all the main MC1R variants in sporadic CM and suggests that they have a direct effect on melanoma risk, independently on the phenotypic characteristics of carriers. This is of particular importance for assessing preventive strategies, which may be directed to darker-pigmented Caucasians with MC1R variants as well as to lightly pigmented, fair-skinned subjects.