Skip to navigation Skip to main content Skip to footer

Approved Research

A contemporary assessment of high-penetrance melanoma genes

Principal Investigator: Dr Peter Kanetsky
Approved Research ID: 52303
Approval date: August 7th 2020

Lay summary

Our current understanding of spectrum of disease outcomes associated with inherited genetic variation in major genes, including ACD, CDKN2A, CDK4, MITF, POT1, SLC45A2, TERF2IP, and TERT, that result in familial melanoma is limited.  We plan to use genotype and whole-exome sequencing data available in the UKBB resource to agnostically determine associations with other (non-melanoma) cancers and non-cancer phenotypes through linkage to cancer registry, hospital, and primary care files.  Results will be combined with those arising from parallel analyses in an independent large US data resource to identify top ranking genetically-associated cancers and non-cancer conditions.  Findings will be used to inform follow up of melanoma-prone families across the globe.

Scope extension: We propose a "modern" approach to identify associations of inherited genetic variation in known melanoma high- and moderate-penetrance genes (i.e. CDKN2A, CDK4, ACD, POT1, TERF2IP, TERT, MITF, and SLC45A2) with a spectrum of cancer and non-cancer outcomes. 

  1. We will query germline exome data on 450,000 individuals in UK Biobank for genetic variation in known high- and moderate-penetrance melanoma susceptibility genes.  After validation and prioritization , we will conduct a phenotype-wide association study (PheWAS) to determine associations with cancer and non-cancer phenotypic outcomes.  We will conduct a similar exercise in an independent set of 200,000 patients enrolled in a US-based health system.  Results will be meta-analyzed.
  2. Using existing array genotyping, we will calculate melanoma polygenic risk scores in 450,000 individuals in UK Biobank and 200,000 patients from a US-based health system and will meta-analyze PheWAS results to determine top associations with cancer and non-cancer phenotypic outcomes.  We will assess whether phenotypic profiles associated with the polygenic risk score differs among individuals with and without variants in the targeted set of high- and moderate-penetrance melanoma genes.
  3. Using array genotype data, we will infer family structure for individuals with melanoma and other top ranking associated cancers and determine the effect of a PRS for melanoma and related heritable traits on melanoma risk according to number of family members affected with melanoma and taking into consideration carriage of genetic variation in the targeted set of melanoma genes.

We propose a "modern" approach to identify associations of inherited genetic variation in known melanoma high- and moderate-penetrance genes (i.e. CDKN2A, CDK4, ACD, POT1, TERF2IP, TERT, MITF, and SLC45A2) with a spectrum of cancer and non-cancer outcomes. 

1. We will query germline exome data on 450,000 individuals in UK Biobank for genetic variation in known high- and moderate-penetrance melanoma susceptibility genes.  After validation and prioritization , we will conduct a phenotype-wide association study (PheWAS) to determine associations with cancer and non-cancer phenotypic outcomes.  We will conduct a similar exercise in an independent set of 200,000 patients enrolled in a US-based health system.  Results will be meta-analyzed.

2. Using existing array genotyping, we will calculate melanoma polygenic risk scores in 450,000 individuals in UK Biobank and 200,000 patients from a US-based health system and will meta-analyze PheWAS results to determine top associations with cancer and non-cancer phenotypic outcomes.  We will assess whether phenotypic profiles associated with the polygenic risk score differs among individuals with and without variants in the targeted set of high- and moderate-penetrance melanoma genes.

3. Using array genotype data, we will infer family structure for individuals with melanoma and other top ranking associated cancers and determine the effect of a PRS for melanoma and related heritable traits on melanoma risk according to number of family members affected with melanoma and taking into consideration carriage of genetic variation in the targeted set of melanoma genes.

We seek to identify other cancers and non-cancer conditions for which surveillance during clinical follow up of patients with melanoma should be considered.  To accomplish this goal, we propose to:

1. Use a phenome-wide association study (PheWAS) approach to determine associations of a melanoma polygenic risk score (PRS) with cancer and non-cancer phenotypic outcomes among UK Biobank participants.  Results will be meta-analyzed with those identified in a parallel PheWAS among 200,000 patients from a US-based health system to determine top-ranking other cancers and non-cancer phenotypes.

2. Determine the contributions of updated PRS's for melanoma and melanoma-related traits to risk of top-ranking other cancers and non-cancer phenotypes.  Prediction models will be validated using data available from a US-based health system.

3. We will query germline exome data from UK Biobank participants for genetic variation at 27 cancer genes for which melanoma is the primary or subordinate tumor.  We then will investigate PRS-based risk models for other cancer and non-cancer phenotypes among individuals who carry pathogenic variants in these melanoma-relevant cancer genes.