Characterizing non-coding somatic and germline variant interactions in ovarian cancer
Characterizing non-coding somatic and germline variant interactions in ovarian cancer
批准号:
10405651
负责人:
ALEXANDER GUSEV
金额:
$66.37万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-06-01 至 2025-05-31
关键词:
AddressAutomobile DrivingBRCA1 geneBinding SitesBiological AssayCRISPR screenCRISPR/Cas technologyCancer BiologyCandidate Disease GeneCell physiologyCellsCessation of lifeChIP-seqChemoresistanceChromosomesClinicalCodeDNA Sequence AlterationDataDevelopmentDiseaseEnhancersEpithelial CellsEpithelial ovarian cancerEvolutionGene ExpressionGenesGeneticGenetic CodeGenetic RiskGenetic VariationGenomeGenomic SegmentGenotypeGoalsHeritabilityHuman GeneticsIn VitroInterdisciplinary StudyInterventionInvadedKnowledgeMalignant NeoplasmsMalignant neoplasm of ovaryMammalian OviductsModelingMolecular ConformationMutateMutationNucleotidesOutcomeOvarianPathogenesisPenetrancePhenotypePrevention approachProteinsRegulator GenesRegulatory ElementResearchRoleSomatic MutationSusceptibility GeneSyndromeTP53 geneTissuesUntranslated RNAValidationVariantcancer initiationcancer predispositioncancer riskchromosome conformation captureclinical translationepigenomicsgene regulatory networkgenetic variantgenome editinggenome sequencinggenome wide association studygenome-widemortalitynovelovarian neoplasmpopulation basedprecursor cellprogramsrisk variantthree-dimensional modelingtooltraittranscription factortreatment responsetumorwhole genome
中文摘要
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英文摘要
ABSTRACT
A fundamental goal of human genetics is to decipher the relationship between genotype and phenotype.
Cancer is defined as a disease comprising a heritable genetic component that confers cancer predisposition
and an acquired (somatic) component where disease is driven by an accumulation of genetic mutations
leading to ever increasing deregulation of normal cellular functions. Population based genome wide
association studies (GWAS) and whole genome sequencing (WGS) analyses have identified thousands of
germline risk variants for ovarian cancer and somatic non-coding mutations involved in ovarian cancer
development. Identifying genomic regions where there are interactions between germline and somatic variants
may enable us to identify the critical drivers of disease. We have established an end-to-end pipeline that can
efficiently evaluate the functional significance of thousands of genetic variants in disease at once. We have
also established ex-vivo models of fallopian tube secretary epithelial cells (precursors of ovarian cancer) and in
vitro 3D models of chemoresistant ovarian cancer. In this proposal, we plan to address provocative question #3
“Do genetic interactions between germline variations and somatic mutations contribute to differences in tumor
evolution or response to therapy?” with the following specific aims: (1) Use computational approaches, to
identify genomic regions where germline and somatic genetic variants converge to indicate shared target
genes and regulatory networks driving ovarian cancer development; (2) Use chromosome conformation
capture assays to validate interactions between regulatory targets and their target genes; (3) Use
CRISPR/Cas9 screens to establish the functional significance of germline-somatic interacting regions in
ovarian cancer development.
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