For every individual who suspects a hereditary cancer risk, there are likely many more carrying actionable germline variants who were never referred for genetic testing. This large-scale genomic analysis challenges the prevailing triage-based model of cancer genetics — where only patients meeting specific family history or clinical criteria receive germline testing — by revealing the true population-level burden of hereditary cancer risk across an unselected cancer cohort.
Drawing on whole-genome sequencing data from 14,765 cancer patients enrolled across 14 NHS genomic medicine centres in the UK's 100,000 Genomes Project, researchers systematically interrogated 109 curated cancer predisposition genes for pathogenic constitutional (germline) variants. The analysis employed a semi-automated variant interpretation workflow anchored in American College of Medical Genetics and Genomics criteria, further refined through cancer- and gene-specific adaptations developed by the Cancer Variant Interpretation Group UK and the ClinGen consortium. The breadth of the gene panel — spanning high- and moderate-penetrance loci — provides one of the most comprehensive population-scale snapshots of hereditary cancer burden assembled to date.
This study matters beyond its impressive scale. The central tension in clinical cancer genetics has always been efficiency versus completeness: targeted testing finds more actionable positives per test ordered, but systematically misses carriers who fall outside referral criteria. Research consistently shows that family history alone captures fewer than half of BRCA1/2 carriers among breast cancer patients, and emerging data suggest similar gaps for Lynch syndrome and other hereditary syndromes. A population-wide genomic approach, as piloted here, could reframe germline testing as a standard oncology workflow rather than a specialist referral. Limitations include the retrospective design, potential ascertainment biases in the 100,000 Genomes cohort, and the evolving interpretive standards for variants of uncertain significance. Still, this work represents a methodologically rigorous, potentially paradigm-shifting contribution to the case for broader germline sequencing in oncology.