Advanced tools for HCMI model genetic perturbation and metastasis characterization
Advanced tools for HCMI model genetic perturbation and metastasis characterization
批准号:
10005595
负责人:
John Doench
金额:
$78.99万
依托单位:
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:
2020-08-05 至 2023-07-31
关键词:
3-DimensionalAddressBar CodesBenchmarkingBrainCRISPR screenCRISPR/Cas technologyCancer ModelCancer cell lineCell modelCellsClinicalClinical DataClustered Regularly Interspaced Short Palindromic RepeatsCommunitiesComplexComputational ScienceConsumptionDataDevelopmentDropoutEnsureEnzymesEpigenetic ProcessFutureGene Expression ProfilingGenerationsGeneticGenetic ModelsGenetic ScreeningGrowthGuide RNAHumanImmunodeficient MouseInjectionsKidneyKnock-outLibrariesLiverLungMalignant NeoplasmsMapsMeasuresMediatingMethodsModelingMolecularMonitorNeoplasm MetastasisOrganOrganoidsOutcomePhenotypePhysiologicalPopulationProliferatingProtocols documentationReagentResearchResourcesSystemSystems BiologyTimeTranslational ResearchUltrasonographyanticancer researchbasebonecell growthcostexperimental studyfunctional genomicsgene discoverygenome editinggenome-widehigh throughput screeningin vivoinnovationmodel developmentmultidisciplinaryneoplastic cellnext generationpatient responseprecision medicineprecision oncologyscale upscreeningsingle-cell RNA sequencingtargeted treatmenttechnology developmenttissue culturetooltumortumor microenvironmentvector
中文摘要
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英文摘要
ABSTRACT
The Human Cancer Models Initiative (HCMI) is creating next generation cancer models that will drive the future
of cancer precision medicine research. Historical cancer cell lines have been selected for their rapid proliferation
on tissue culture plastic, which has made them amenable to high throughput screening such as genome-wide
CRISPR/Cas9 knock-out screens. However, the historical lines have large gaps in their representation of the
diversity of human cancer, and they may lack physiological relevance given their optimization for rapid
proliferation. Next generation HCMI models address these concerns, but will require the development of new
methods to make them useful. Specifically, standard approaches to genome editing (involving first creating Cas9-
stably expressing lines and then introducing guide RNAs) will not work for slowly proliferating cells often growing
in 3D. We will therefore develop all-in-one genome editing vector systems that will make it possible to bring the
power of genome editing to HCMI models. In addition, standard viability read-outs of such “drop-out” screens
involve the growth of cells over many population doublings. But for slowly proliferating HCMI models, alternative
readouts will be required for efficient screening. We will therefore develop short-term single cell RNA sequencing
(scRNAseq) methods that will serve as surrogate read-outs for long-term viability. Given the clinical annotation
associated with HCMI models, there is also enormous opportunity to expand the use of these models beyond
viability measures to more complex, physiologically relevant phenotypes such as organ-specific metastatic
potential. We will therefore develop methods that make it possible to determine the metastatic potential for next
generation cancer models, and we will create a public resource of the metastasis map (MetMap) for at least 50
HCMI models. All data and protocols will be made publicly available without restriction, all reagents will be made
available via Addgene, and all modified models made available to ATCC for distribution. Importantly, throughout
the project, all cell models will be rigorously monitored for evidence of genetic and epigenetic drift. At the
conclusion of the proposed project, we expect to have generated a set of tools and data that will help propel the
future of cancer precision medicine based on next generation cancer models.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
CRISPR screens for SARS-CoV-2 Host Factors
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批准号:10163544
-
项目类别:
-
资助金额:$44.0万
-
财政年份:2020
-
负责人:John Doench
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依托单位:
Advanced tools for HCMI model genetic perturbation and metastasis characterization
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批准号:10229465
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项目类别:
-
资助金额:$78.99万
-
财政年份:2020
-
负责人:John Doench
-
依托单位:
Advanced tools for HCMI model genetic perturbation and metastasis characterization
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批准号:10465033
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项目类别:
-
资助金额:$78.76万
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财政年份:2020
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负责人:John Doench
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依托单位:
Core C: Defining regulators of immunity to acute infection using CRISPR screens
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批准号:10207347
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项目类别:
-
资助金额:$36.25万
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财政年份:2017
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负责人:John Doench
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依托单位:
海外基金