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Does the Germline Genome Encode for the Invasiveness of a Cutaneous Melanoma? | Dermatology | JAMA Dermatology | ÌÇÐÄvlog

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Editorial
August 14, 2024

Does the Germline Genome Encode for the Invasiveness of a Cutaneous Melanoma?

Author Affiliations
  • 1Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
  • 2Theme Cancer, Karolinska University Hospital, Stockholm, Sweden
JAMA Dermatol. 2024;160(9):922-924. doi:10.1001/jamadermatol.2024.2599

Heritability is a factor that has been demonstrated to be strongly associated with the diagnosis of cutaneous melanoma, and there are several inherited gene variants that have been identified as melanoma risk alleles.1,2 Previous studies have mainly focused on invasive melanoma or on melanoma irrespective of invasiveness.2 In this issue of JAMA Dermatology, Ingold et al3 present their investigation on the influence of germline genetic variation on the risk of developing in situ vs invasive melanoma. The study by Ingold et al3 is a notable attempt to unravel a complicated biology as melanoma in situ traditionally is considered as a precursor to invasive melanomas, and the idea that these lesions in a sense represent different class of tumors with different etiology is unproven. The authors conducted this study using 5 different datasets of populations with European ancestry (from the UK, Finland, and Australia), with more than 10 000 and more than 3000 patients in total with invasive and in situ melanomas, respectively, together with more than 500 000 controls. The study is a meta-analysis of the different cohorts, assessing associations between common single-nucleotide variant (SNV) genotypes, comparing (1) invasive melanoma with controls, (2) in situ melanoma with controls, and (3) invasive melanoma with in situ melanoma (case-case analysis). Further, 3 separate bioinformatics approaches were applied: (1) genome-wide association study (GWAS) to identify significant chromosomal risk loci, (2) polygenic risk score (PRS) analyses based on 64 497 SNVs to identify joint score combining identified variants that had a P value threshold less than .10 in the case-case GWAS meta-analysis, and (3) SNV-based heritability, which is a method to assess how much of the variation in a trait can be explained by the cumulative effect of SNVs.

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