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.

Evolution of approaches to identify melanoma missing heritability

Dalmasso B.;Ghiorzo P.
2020-01-01

Abstract

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1009810
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