Cancer cell state interactions with immune populations of the tumor microenvironment

癌细胞状态与肿瘤微环境免疫群体的相互作用

• 批准号: 10551999
• 负责人: Dalia Barkley
• 金额: $ 3.23万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10551999
• 关键词: Algorithms; Atlas of Cancer Mortality in the United States; Biological; Biological Assay; Biological Models; Cancer Biology; Cancer Model; Cell Communication; Cell physiology; Cells; Coculture Techniques; Complex; Data; Disease; Drug resistance; Elements; Environment; Epigenetic Process; Experimental Models; Gene Expression; Genes; Genetic; Genetic Transcription; Goals; Heterogeneity; Human; Immune; Immune Evasion; Immune system; Immunotherapy; In Vitro; Invaded; Location; Maintenance; Maps; Measures; Methods; Molecular; Mus; Natural Selections; Neoplasm Metastasis; Patients; Pattern; Phenotype; Physicians; Play; Population; Recurrence; Regimen; Relapse; Research; Resolution; Role; Sampling; Scientist; Spottings; System; Techniques; Technology; Testing; Therapeutic Intervention; Time; Tissue-Specific Gene Expression; Tissues; Training; Treatment Failure; Variant; Work; cancer cell; cancer type; cell type; clinical application; dynamic system; experimental study; improved; in vitro Assay; in vivo Model; innovation; insight; interdisciplinary approach; lens; mortality; neoplastic cell; rational design; single-cell RNA sequencing; transcriptome; transcriptomics; tumor; tumor heterogeneity; tumor microenvironment; tumor progression; tumorigenesis

SUMMARY Tumors are complex systems composed of genetically and transcriptionally heterogeneous cells, and this variation has been implicated as a cause of drug resistance and mortality. Understanding intra-tumor heterogeneity is therefore likely to have widespread scientific implications and clinical applications. The advent of single-cell RNA-Seq has enabled the mapping of transcriptionally distinct states among cancer cells across a wide range of tumor types and disease stages. In this project, I take a gene module-centric view to define cell states in a rigorous and widely applicable manner. In my preliminary work, I have identified specific cancer cell states that are conserved across many cancer types as well as some that are unique to specific tumors. This proposal aims to further characterize these states in relation to the tumor microenvironment, with the goal of furthering our understanding of tumors as complex dynamical systems amenable to therapeutic intervention. In order to systematically map interactions between tumor cell populations within their native context, I will integrate paired single-cell and spatial transcriptomic data obtained in primary patient samples. This will enable me to identify cell populations that interact within the tumor, and to characterize the gene expression changes that occur in these interactions. In order to further establish how cancer cell state function relates to the tumor microenvironment, I will take advantage of experimental model systems amenable to perturbation. I will use orthotopic mouse cancer models as a platform to deplete specific populations of the immune system and measure their effect on cancer cell states. Next, I will perform co-culture experiments followed by transcriptomic and phenotypic profiling to measure direct effects on one cell population on another. Collectively, the experiments and algorithms proposed will significantly improve our understanding of intratumoral heterogeneity through the lens of cancer cell states. Dissecting the complex interactions between cancer cell states and immune cell populations will be of particular translational relevance, as it may enable the rational design of immunotherapy regimens. The research proposed capitalizes on the strengths of the Yanai lab in cutting-edge molecular techniques, computational innovation, and in vitro and in vivo modeling of cancer. Together with the outlined training plan, this work will set me on a path to independent research as a physician-scientist.

总结 肿瘤是由遗传和转录异质性细胞组成的复杂系统， 这种变异被认为是耐药性和死亡率的原因。了解肿瘤内 因此，异质性可能具有广泛的科学意义和临床应用。问世 的单细胞RNA-Seq已经能够在不同的癌症细胞中绘制转录上不同的状态， 广泛的肿瘤类型和疾病阶段。在这个项目中，我采取以基因模块为中心的观点来定义细胞 以严格和广泛适用的方式。在我的初步工作中，我已经确定了特定的癌细胞 这些状态在许多癌症类型中是保守的，以及某些特定肿瘤所特有的状态。这 该提案旨在进一步描述这些状态与肿瘤微环境的关系，目标是 进一步加深了我们对肿瘤作为复杂动力系统的理解，这些系统适合于治疗干预。在 为了系统地绘制肿瘤细胞群体在其天然背景下的相互作用，我将 整合在原始患者样品中获得配对的单细胞和空间转录组数据。这将使 我来确定在肿瘤内相互作用的细胞群，并描述基因表达的变化， 在这些互动中发生。为了进一步确定癌细胞状态功能与肿瘤的关系， 微环境，我将利用实验模型系统服从扰动。我会用 原位小鼠癌症模型作为耗尽免疫系统的特定群体的平台， 测量它们对癌细胞状态的影响。接下来，我将进行共培养实验， 转录组学和表型分析以测量一个细胞群对另一个细胞群的直接影响。 总的来说，提出的实验和算法将显着提高我们的理解 通过癌细胞状态的透镜的肿瘤内异质性。剖析了 癌细胞状态和免疫细胞群体将具有特别的翻译相关性，因为它可以使免疫细胞的功能和功能的改变成为可能。 合理设计免疫治疗方案。该研究计划利用了柳井的优势 实验室在尖端的分子技术，计算创新，并在体外和体内建模的癌症。 加上概述的培训计划，这项工作将使我走上独立研究的道路， 物理学家兼科学家

项目成果

Cancer cell states and emergent properties of the dynamic tumor system.

• DOI: 10.1101/gr.275308.121
• 发表时间: 2021-10
• 期刊: Genome research
• 影响因子: 7
• 作者: Barkley D;Rao A;Pour M;França GS;Yanai I
• 通讯作者: Yanai I

Cancer cell states recur across tumor types and form specific interactions with the tumor microenvironment.

• DOI: 10.1038/s41588-022-01141-9
• 发表时间: 2022-08
• 期刊: NATURE GENETICS
• 影响因子: 30.8
• 作者: Barkley, Dalia;Moncada, Reuben;Pour, Maayan;Liberman, Deborah A.;Dryg, Ian;Werba, Gregor;Wang, Wei;Baron, Maayan;Rao, Anjali;Xia, Bo;Franca, Gustavo S.;Weil, Alejandro;Delair, Deborah F.;Hajdu, Cristina;Lund, Amanda W.;Osman, Iman;Yanai, Itai
• 通讯作者: Yanai, Itai