Inheritance and brain tumour risk
Supervisor(s): Professor Richard Houlston
Team: Molecular and Population Genetics
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Summary
Primary brain tumours (PBTs) are one of the most common cancers between the ages of 35 and 49 years. Gliomas account for ~80% of PBT and generally have a poor prognosis despite treatment. Evidence for genetic predisposition to glioma is provided by the elevated 2-fold in relatives of glioma patients.
To identify risk variants for glioma, we have conducted a genome-wide association (GWA) study of glioma. We identified five genetic risk loci for glioma at 5p15.33 (TERT), 8q24.21 (CCDC26), 9p21.3 (CDKN2A-CDKN2B), 20q13.33 (RTEL1) and 11q23.3 (PHLDB1) [1]. These data show that common genetic variants contribute to the risk of developing glioma and provide insight into disease causation.
The proposed project will comprise three interrelated components:
(1) Identification of additional novel disease loci: The over-representation of associations between SNPs and risk of glioma in our GWA study provides a strong rationale for genotyping additional case-control series in order to identify additional novel disease-causing alleles. These analyses will be undertaken using a number of different genotyping technologies.
(2) Fine mapping of susceptibility loci: We will conduct further mapping and variant identification studies to identify causal variants; prioritising variants on the basis of strength of associations detected. These studies will include harvesting of additional sequence variants from regions of association by resequencing samples from cases and further association studies of these variants.
(3) Identification of causal variants: Association studies based on analysis of tagging SNPs enable common genetic variation to be interrogated, however the genotyped SNPs associated with risk are unlikely to be the functional variants. The genomic regions delineating each locus will be determined from the observed pattern of linkage disequilibrium between tagSNPs and surrounding SNPs within HapMap. Regions will then be prioritized so as to make best use of resources. Additional variants, including those that are population-specific, will include use of multiple resources including the 1000genomes project and sequence data generated. This will be supplemented by haplotype analysis to identify regions likely to harbor rare variants that were not included in the original GWA study. Evidence supporting the association will be sought using in silico bioinformatics tools for examining evolutionary conservation and probable transcription binding sites. The probable basis of the functional SNP will dictate subsequent functional analyses, but is likely to involve use of EMSA and reporter assays, techniques we are well versed in implementing.
References
- Shete, S., et al. (2009) Genome-wide association study identifies five susceptibility loci for glioma. Nature Genetics Vol 41, No 8, p899-904
- Cancer Genome Atlas Research Network
