权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

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

基本信息

批准号：
10004966
负责人：
BONNIE BERGER
金额：
$ 92.22万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
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：
2020-07-08 至 2023-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10004966
关键词：
3-Dimensional Address Adoption Algorithms Aneuploidy Bar Codes Basic Science Bioinformatics Biopsy CRISPR interference Cancer Biology Cancer Model Cancer cell line Cell Line Cells Characteristics Clinical Oncology Collection Colon Carcinoma Color Communities Custom Data Development Doctor of Philosophy Drug Addiction Ensure Epigenetic Process Evaluation Excision Expression Library Foundations Gene Combinations Genes Genetic Genetic Recombination Genetic Screening Genetic Structures Genomics Human In Vitro Individual Institutes Investigation Libraries Machine Learning Malignant Neoplasms Malignant neoplasm of gastrointestinal tract Metabolic Modeling Nature Neoplasm Metastasis Operative Surgical Procedures Organoids Pathway interactions Patients Phenotype Population Primary Neoplasm Proteins Protocols documentation Recombinants Recurrence Recurrent tumor Reporter Reproducibility Research Research Personnel Resistance Role Scientist Screening procedure Solid Neoplasm Speed Study models Technology Therapeutic Tissue Harvesting Tumor Biology Tumor Tissue Tumor-Derived U-Series Cooperative Agreements Universities Visualization anticancer research base cancer cell cancer heterogeneity cancer recurrence cancer stem cell cancer type catalyst chemotherapy clinically relevant combinatorial data integration design epigenomics expression vector frontier heterogenous data human disease in vivo in vivo Model innovation large datasets model development mortality multidisciplinary neoplastic cell new technology next generation novel novel therapeutics promoter protein expression single-cell RNA sequencing stem cell biology stem cells success synthetic biology therapeutic target therapy resistant three dimensional cell culture three dimensional structure tool trait transcriptome transcriptomics tumor tumor heterogeneity

项目摘要

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

项目摘要解决对化疗耐药且经常复发的异质性癌症的复杂性或转移，我们建议开发一套基于多学科创新的工具，生物学，癌症类器官技术和生物信息学。这些合成工具注释报告用于癌症异质性和复发发展的类器官（StarOrchard）包括：万花筒类器官的活化转化（SPARKO），组合遗传学En Masse（CombiGEM）和单细胞RNA测序全景（Scanorama）。SPARKO可以注释通过荧光蛋白表达文库在活细胞中的异质性癌症群体，着色的肿瘤类器官。CombiGEM可以通过大规模、高通量的检测，大规模平行无偏组合遗传筛选Scanorama可以整合分析单细胞转录组学的大型数据集通过复杂的生物信息学算法。这些工具专注于条形码策略，以实现准确跟踪和分析单个肿瘤细胞，独特的遗传畸变，并大大扩展了下一代癌症模型的实用性（NGCM）用于癌症机理研究或治疗发现。StarOrchard工具使在注释的异质性肿瘤表型中靶向遗传扰动，而不破坏细胞，测序这些工具将应用于大量和各种NGCM，以优化实验议定书为了确保成功，我们召集了一个杰出的团队：PI Timothy K。Lu，医学博士，博士，对合成生物学工具做出了惊人的原创性贡献，询问癌细胞药物依赖性; PI Ömer Yilmaz，医学博士，博士，在癌症方面具有广泛的专业知识并开发了新的技术，以维持患者来源的结肠癌类器官用于体内建模; PI Bonnie Berger博士将利用她在生物信息学方面的专业知识，她的Scanorama算法基于动态单细胞RNA整合所有肿瘤类型的数据测序（scRNAseq）。我们还得到了癌症生物学和各种癌症领域领先专家的支持在癌症研究的基础科学和临床肿瘤学前沿的类型。集体整个团队的承诺和多学科的贡献确保建立一个开放的分布式研究工具集，加速癌症生物学和治疗发现的进步