Clinical and genomic features of extrachromosomal circular DNA in pediatric cancer
Clinical and genomic features of extrachromosomal circular DNA in pediatric cancer
批准号:
10604306
负责人:
Owen Shojiro Chapman
金额:
$2.2万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-04-01 至 2023-08-11
关键词:
ATAC-seqAdultAlgorithmsBioinformaticsCRISPR interferenceCancer PatientCell divisionCellsCentromereChildhood Malignant Brain TumorChromatinChromosomal BreaksChromosomesCircular DNAClinicalComputer softwareComputing MethodologiesDNA SequenceDNA Sequence RearrangementDNA StructureDNA copy numberDetectionDevelopmentDiseaseDrug resistanceEvolutionFrequenciesGenesGenomeGenomic SegmentGenomicsGerm-Line MutationHematologyHeterogeneityHi-CHumanImageIncidenceIndividualInstitutionLengthMalignant - descriptorMalignant Childhood NeoplasmMalignant NeoplasmsMapsMethodsModelingMolecularMutationNeoplasm MetastasisNucleic Acid Regulatory SequencesOncogenesOutcomePathway interactionsPatientsPediatric NeoplasmPediatric OncologyPopulationPrognosisPropertyRecurrenceReportingResearch PersonnelResistanceResolutionRoleSHH geneSequence AnalysisSolidSomatic MutationStructureSubgroupSurveysTestingTissuesTreatment FailureTumor TissueWorkcancer genomecancer genomicscancer predispositioncancer typechemotherapyclinically significantcohortcomputerized toolsdata resourcedetection methodeffective therapygenome resourcegenome sequencinggenomic datagenomic locusmedulloblastomamultiple omicsneoplastic cellopen sourcepatient derived xenograft modelpressureprognosticprognostic significancereconstructionresponsesingle cell technologytherapy resistanttumortumor heterogeneitytumorigenesiswhole genome
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ABSTRACT/PROJECT SUMMARY
Extrachromosomal circular DNA (ecDNA) is a structural rearrangement of the genome whereby 1 or more genomic
regions breaks from the chromosomes and is circularized, forming an acentric circular DNA sequence 100kbp-10Mbp in
length and generally containing multiple genes and regulatory regions. These bodies are found exclusively in tumor cells
and are associated with exceptionally malignant cancers. Although ecDNA has been observed in tumor tissue since the
1960s, recent work has highlighted the central role of ecDNA in oncogene amplification and as a contributor to intra-
tumoral heterogeneity. Intra-tumoral heterogeneity is one of the leading determinants of therapeutic resistance and
treatment failure and one of the main reasons for poor overall survival in cancer patients. However, the functional
relevance of ecDNA as a driver of tumor heterogeneity and drug resistance in pediatric cancers has lagged behind advances
in adult tumors. We hypothesize that ecDNA is a frequent molecular driver of tumorigenesis, metastasis and resistance to
treatment in pediatric cancer. We propose to test this hypothesis by the following specific aims:
Aim 1: Establish the genomic, clinical, and molecular properties of ecDNA in medulloblastoma. We will characterize
ecDNA structures across a multi-institutional cohort of medulloblastoma patients and patient-derived xenograft
models. To better understand molecular mechanisms of ecDNA-driven malignancy, we will perform comprehensive
multi-omic sequence analysis of ecDNAs in MB.
Aim 2: Characterize intratumoral copy-number heterogeneity conferred by ecDNA at single-cell resolution. Because
ecDNAs lack centromeres, a tumor may acquire intratumoral copy-number heterogeneity with every cell division. We
will develop methods to detect ecDNA in single cells, and apply them to characterize ecDNA heterogeneity in a paired
patient tumor and patient derived xenograft model.
Aim 3: Survey the genomic, clinical and molecular properties of ecDNA across pediatric cancer types. We will screen for
ecDNA across thousands of patients from 22 pediatric cancer types by deploying computational tools for ecDNA
detection to large pediatric cancer genomic data platforms. We will also leverage the high-quality mutation
annotations already available for these tumors to find genomic correlates of ecDNA.
Upon completion of this project, we will have established the prognostic relevance of ecDNA status across pediatric cancer
types, and developed open-source software to decompose ecDNA heterogeneity at the single-cell level.
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