Breast Cancer Risk Enhancers
Breast Cancer Risk Enhancers
批准号:
8791816
负责人:
Gerhard A Coetzee
金额:
$37.7万
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-02-01 至 2015-11-30
关键词:
AffectAllelesBRCA1 MutationBRCA2 geneBindingBiological AssayBiologyBreastBreast Cancer GeneticsCancer BiologyCandidate Disease GeneCell LineClinicalDNADataDetectionDiabetes MellitusDiseaseEnhancersExonsGene TargetingGenesGenetic RiskGenetic VariationGenetic studyGenomicsHealthHeart DiseasesIn VitroIndividualInterventionLinkMCF10A cellsMCF7 cellMalignant NeoplasmsMeasuresModelingNucleosomesPOU2F1 genePersonsPhenotypePopulationPredispositionResponse ElementsRiskSP1 geneSingle Nucleotide PolymorphismTAL1 geneUntranslated RNAVariantWorkcancer riskfollow-upgenetic variantgenome wide association studyindexingknock-downmalignant breast neoplasmpopulation basedpromoterrisk variantscreeningtraittranscription factor
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Breast Cancer Risk Enhancers Breast cancer (BCa) genetic risk is partly explained by rare pathological mutations (BRCA1 and BRCA2, for example) and >70 common variants that contribute to risk; the latter as revealed by genome-wide association (GWAS) hits. The major 'problem' of GWAS loci is the lack of mechanistic understanding of how such risk alleles function and how they contribute to genetic risk. This is further exacerbated by the fact that the vast majority (>90% of BCa risk alleles) resides in non-coding DNA such as enhancers. This application intends to systematically elucidate mechanisms of action and target genes of 20 newly identified BCa risk enhancers. This will be achieved by measuring allele-specific enhancer activity (Aim #1), allele-specific nucleosome depletion and transcription factor occupancy (Aim #2), identifying risk enhancer target genes, using eQTL, 3C and CRIPR/Cas (Aim #3) and finally by determining the functionality of risk genes in terms of cancer phenotypes (Aim #4). The results will link functionality of variants with breast biology and elucidate previously unanticipated risk mechanisms. The results will have a major impact on many aspects of disease including population based screening for early disease detection, and new treatments.
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