Advanced tools for HCMI model genetic perturbation and metastasis characterization
用于 HCMI 模型遗传扰动和转移表征的高级工具
基本信息
- 批准号:10005595
- 负责人:
- 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
- 起止时间:2020-08-05 至 2023-07-31
- 项目状态:已结题
- 来源:
- 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
项目摘要
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.
摘要
人类癌症模型倡议(HCMI)正在创造下一代癌症模型,将推动未来
癌症精准医学研究。历史上的癌细胞系因其快速增殖而被选中
在组织培养塑料上,这使得它们能够进行高通量筛选,如全基因组筛选
CRISPR/CAS9淘汰屏。然而,历史的线条在它们对
人类癌症的多样性,它们可能缺乏生理相关性,因为它们对快速
扩散。下一代HCMI模型解决了这些问题,但将需要开发新的
方法使它们变得有用。具体来说,基因组编辑的标准方法(包括首先创建Cas9-
稳定表达细胞系,然后导入引导RNA)对通常生长的缓慢增殖的细胞不起作用
在3D中。因此,我们将开发一体式基因组编辑载体系统,使其能够将
基因组编辑对HCMI模型的影响。此外,这种“辍学”屏幕的标准生存能力读数
涉及细胞在许多种群倍增过程中的生长。但对于缓慢增长的HCMI模型,替代方案
需要读数才能进行有效的筛查。因此,我们将开发短期单细胞RNA测序
(ScRNAseq)方法,将作为长期生存能力的替代读出。给出了临床注释
与HCMI模型相关联,也有巨大的机会将这些模型的使用扩展到
对更复杂的、与生理相关的表型的生存能力测量,如器官特异性转移
潜力。因此,我们将开发能够确定NEXT转移潜能的方法
生成癌症模型,我们将创建一个公共资源的转移图(Metmap),用于至少50
人机界面模型。所有数据和方案将不受限制地向公众开放,所有试剂将
可通过Addgene获得,所有修改后的型号均可供ATCC分发。重要的是,自始至终
在该项目中,所有的细胞模型都将受到严格的监测,以寻找遗传和表观遗传漂移的证据。在
在拟议的项目结束时,我们预计已经生成了一套工具和数据,将有助于推动
基于下一代癌症模型的癌症精准医学的未来。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
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John Doench其他文献
John Doench的其他文献
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{{ truncateString('John Doench', 18)}}的其他基金
CRISPR screens for SARS-CoV-2 Host Factors
CRISPR 筛选 SARS-CoV-2 宿主因子
- 批准号:
10163544 - 财政年份:2020
- 资助金额:
$ 78.99万 - 项目类别:
Advanced tools for HCMI model genetic perturbation and metastasis characterization
用于 HCMI 模型遗传扰动和转移表征的高级工具
- 批准号:
10229465 - 财政年份:2020
- 资助金额:
$ 78.99万 - 项目类别:
Advanced tools for HCMI model genetic perturbation and metastasis characterization
用于 HCMI 模型遗传扰动和转移表征的高级工具
- 批准号:
10465033 - 财政年份:2020
- 资助金额:
$ 78.99万 - 项目类别:
Core C: Defining regulators of immunity to acute infection using CRISPR screens
核心 C:使用 CRISPR 筛选定义急性感染免疫调节因子
- 批准号:
10207347 - 财政年份:2017
- 资助金额:
$ 78.99万 - 项目类别:
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