| Title: | Evaluation of rare and common variants in common cancers |
| Lead Institution: | The Cyprus Institute of Neurology and Genetics |
| Principal investigator: |
Application 102655
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About
Clinical genetic testing performed in high-risk cancer genes, often identifies variants of uncertain clinical significance (VUS) of unknown/unclear association to disease risk, that complicate patient management. Variant evidence in association with disease risk can be used under established variant classification frameworks to inform patient testing and assess variant class. We wish to use the UKBiobank dataset to implement variable statistical methodologies, including a method we have recently developed in the analysis of case-control datasets for the use of variant frequency data in variant classification, to inform classification efforts for variants identified within high-risk genes. Using these methods, existing and novel evidence types used in variant interpretation will be evaluated for application in clinical practice and will be combined with other external sources to improve variant classification. The second scope of our project is to explore cancer genetic susceptibility attributed to commonly-occurring low-risk variants. Low-risk variants, primarily identified by GWAS, can be also explored by fine-mapping strategies. Fine-mapping identifies independently-associated variants within regions defined by GWAS as strongly-associated with disease and prioritises them into sets of high-confidence candidate causal variants (CCVs). We aim to use the UK Biobank dataset to apply fine-mapping statistical methods in association with breast and other cancers. Identified CCVs will be explored on their mechanism of disease, by target gene analysis and network and pathway analyses. The final part of our project will be focused on the assessment of different types of Polygenic Risk Scores that have the potential to be used in clinical practice. Overall, our project has the potential to improve patient risk assessments, while enabling the generation of a higher number of clinically-actionable results by genetic testing. We anticipate that the project will take three years to complete.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 14661 | Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction | Kristia Yiangou (+126) | 2024 | Breast Cancer Research |
Enabling scientific discoveries that improve human health