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Developing high-throughput genetic perturbation strategies for single cells in cancer organoids

Developing high-throughput genetic perturbation strategies for single cells in cancer organoids
开发癌症类器官中单细胞的高通量遗传扰动策略
批准号:
10004966
负责人:
BONNIE BERGER
金额:
$92.22万
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:
已结题
起止时间:
2020-07-08 至 2023-06-30
关键词:
3-DimensionalAddressAdoptionAlgorithmsAneuploidyBar CodesBasic ScienceBioinformaticsBiopsyCRISPR interferenceCancer BiologyCancer ModelCancer cell lineCell LineCellsCharacteristicsClinical OncologyCollectionColon CarcinomaColorCommunitiesCustomDataDevelopmentDoctor of PhilosophyDrug AddictionEnsureEpigenetic ProcessEvaluationExcisionExpression LibraryFoundationsGene CombinationsGenesGeneticGenetic RecombinationGenetic ScreeningGenetic StructuresGenomicsHumanIn VitroIndividualInstitutesInvestigationLibrariesMachine LearningMalignant NeoplasmsMalignant neoplasm of gastrointestinal tractMetabolicModelingNatureNeoplasm MetastasisOperative Surgical ProceduresOrganoidsPathway interactionsPatientsPhenotypePopulationPrimary NeoplasmProteinsProtocols documentationRecombinantsRecurrenceRecurrent tumorReporterReproducibilityResearchResearch PersonnelResistanceRoleScientistScreening procedureSolid NeoplasmSpeedStudy modelsTechnologyTherapeuticTissue HarvestingTumor BiologyTumor TissueTumor-DerivedU-Series Cooperative AgreementsUniversitiesVisualizationanticancer researchbasecancer cellcancer heterogeneitycancer recurrencecancer stem cellcancer typecatalystchemotherapyclinically relevantcombinatorialdata integrationdesignepigenomicsexpression vectorfrontierheterogenous datahuman diseasein vivoin vivo Modelinnovationlarge datasetsmodel developmentmortalitymultidisciplinaryneoplastic cellnew technologynext generationnovelnovel therapeuticspromoterprotein expressionsingle-cell RNA sequencingstem cell biologystem cellssuccesssynthetic biologytherapeutic targettherapy resistantthree dimensional cell culturethree dimensional structuretooltraittranscriptometranscriptomicstumortumor heterogeneity

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PROJECT SUMMARY To address the complexity of heterogeneous cancers that are resistant to chemotherapy and frequently recur or metastasize, we propose to develop a set of tools based on multidisciplinary innovations combining Synthetic Biology, Cancer Organoid Technology, and Bioinformatics. These Synthetic Tools to Annotate Reporter Organoids for Cancer Heterogeneity and Recurrence Development (StarOrchard) include: Synthetic Promoter Activated Recombination of Kaleidoscopic Organoids (SPARKO), Combinatorial Genetics En Masse (CombiGEM), and single-cell RNA sequencing panorama (Scanorama). SPARKO can annotate heterogeneous cancer populations in living cells via fluorescent protein expression libraries to make multi- colored tumor organoids. CombiGEM can rapidly identify potential therapeutic targets via large-scale, massively parallel, and unbiased combinatorial genetic screens. Scanorama can integrate the analysis of large datasets of single-cell transcriptomics via sophisticated bioinformatics algorithms. These tools focus on barcoding strategies to enable accurate tracking and analysis of individual tumor cells that harbor distinct genetic aberrations, and substantially expand the utility of the Next Generation Cancer Models (NGCMs) for cancer mechanistic investigations or therapeutic discovery. The StarOrchard tools enable targeted genetic perturbations in annotated heterogeneous tumor phenotypes without destroying cells for sequencing. These tools will be applied to a large number and variety of NGCMs to optimize experimental protocol. To ensure success, we have convened an outstanding team: PI Timothy K. Lu, MD, PhD, has made strikingly original contributions to Synthetic Biology tools that enable high-throughput genetic interrogation of cancer cell drug dependency; PI Ömer Yilmaz, MD, PhD, has extensive expertise in cancers of the gastrointestinal tract and has developed novel technologies to maintain patient-derived colon cancer organoids for in vivo modeling; and PI Bonnie Berger, PhD, will use her expertise in bioinformatics and her Scanorama algorithm to integrate data across all tumor types based on dynamic single cell RNA sequencing (scRNAseq). We are also supported by leading experts in cancer biology and various cancer types at both the basic science and clinical oncology frontiers of cancer research. The collective commitment and multidisciplinary contributions of the entire team ensure the establishment of an openly distributed investigative tool set that accelerates advancements in cancer biology and therapeutic discovery
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