Increasingly available genomic sequencing data are exploited to identify genes and variants contributing to diseases, particularly cancer. Traditionally, methods to find such variants have relied heavily on allele frequency and/or familial history, often neglecting to consider any mechanistic understanding of their functional consequences. Thus, while the set of known cancer-related genes has increased, for many, their mechanistic role in the disease is not completely understood. This issue highlights a wide gap between the disciplines of genetics, which largely aims to correlate genetic events with phenotype, and molecular biology, which ultimately aims at a mechanistic understanding of biological processes. Fortunately, new methods and several systematic studies have proved illuminating for many disease genes and variants by integrating sequencing with mechanistic data, including biomolecular structures and interactions. These have provided new interpretations for known mutations and suggested new disease-relevant variants and genes. Here, we review these approaches and discuss particular examples where these have had a profound impact on the understanding of human cancers.
Keywords: bioinformatics; genetics; mechanism; protein interactions; protein structure.
© 2018 Federation of European Biochemical Societies.