Matthew Lyon, Jade Heath, Sian Morgan, Sheila Palmer-Smith, Ruth Best, Peter Davies, Christopher Anderson and Rachel Butler
Cardiff and Vale University Health Board
Gene deletions and duplications (collectively known as Copy-Number Variants (CNVs)) account for 5-10% of all pathogenic mutations but are difficult to detect and require specialist secondary testing. Recently, the All-Wales Medical Genetics Laboratory implemented next-generation sequencing (NGS) for detection of single base changes in several cancer predisposition genes.
This cutting edge technique provides higher resolution, improved accuracy and faster gene characterisation at a fraction of the cost of previous technologies. Reports in the scientific literature also suggest this data can be used for CNV analysis. The aim of the study was to compare CNV identification using NGS with the current gold standard test, with the anticipation of eliminating the need for secondary testing.
38 known CNVs across 17 genes identified using current NHS gold standard testing were interrogated using NGS. 36 true-positive mutations were correctly recalled (94.7%, 82.3%-99.4% 95CI).
Two false-negative mutations were subsequently identified using alternative analysis approaches.
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This new analysis method has potential to increase mutation detection compared with current NHS testing. In principle the approach can be applied to any genetic region or disease.
During this study cancer predisposition genes were selected for characterisation. Identifying this type of mutation will affect patient management in order to increase surveillance and early detection of cancerous legions improving health outcomes.
In doing so, patients and their families’ with the greatest healthcare needs are identified.
Additionally, the new method improves resource efficiency by eliminating the need for secondary testing, saving staff time, consumables and equipment maintenance. The patient experience is also improved by minimising the time taken to report results.
These preliminary results demonstrate high sensitivity for CNV detection using NGS data. Further analysis will be undertaken to fully assess the characteristics of this method before the current gold-standard can be displaced.