Single-Cell, Spatial and Functional Dissection of Cancer Cell States, Co-Evolving Ecosystems, and Vulnerabilities During Tumor Progression and Metastasis

癌细胞状态、共同进化生态系统以及肿瘤进展和转移过程中的脆弱性的单细胞、空间和功能剖析

• 批准号: 10729386
• 负责人: Benjamin Izar
• 金额: $ 38.49万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-19 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10729386
• 关键词: Address; Behavior; Binding; Biological; Biology; Brain; Brain Neoplasms; Cancer Center; Cancer Patient; Cell Communication; Cells; Cephalic; Chronology; Clinical; Complex; Coupled; Cues; Cutaneous Melanoma; Data; Dedications; Dependence; Disease; Disease Progression; Dissection; Drug Screening; Drug resistance; Ecosystem; Event; Fostering; Future; Gene Expression Profiling; Genetic Transcription; Genome; Genomics; Goals; Heterogeneity; Human; Immune checkpoint inhibitor; Immunosuppression; Immunotherapy; In Situ; Label; Ligands; Link; Logic; Malignant - descriptor; Malignant Neoplasms; Mediating; Metastatic malignant neoplasm to brain; Methods; Minority; Modeling; Molecular; Neoplasm Metastasis; Network-based; Non-Small-Cell Lung Carcinoma; Patients; Pharmaceutical Preparations; Pharmacotherapy; Phenotype; Primary Neoplasm; Printing; Process; Proteins; Publications; Research Personnel; Resistance; Resolution; Series; Signal Transduction; Site; Slice; Somatic Mutation; Stratification; System; Testing; Therapeutic; Time; Tissues; Validation; actionable mutation; analytical tool; cancer cell; cancer heterogeneity; cell behavior; checkpoint therapy; clinically relevant; computerized tools; design; genome editing; genome sequencing; human model; immune checkpoint blockade; improved; in vivo; innovation; insight; machine learning framework; malignant state; multimodality; multiple omics; novel; paracrine; pharmacologic; programs; receptor; recruit; response; spatiotemporal; targeted treatment; therapeutic development; tool; transcriptomics; treatment response; tumor; tumor microenvironment; tumor progression; tumor-immune system interactions; tumorigenic; whole genome

Aggressive cancers often lack pharmacologically actionable mutations and do not respond to immune checkpoint blockade, thus deriving only modest clinical benefit from targeted and immune therapy. The heterogeneity of both transformed and healthy cells in the Tumor Microenvironment (TME) represents a critical obstacle to achieving more durable response in cancer patients. Recent insights, using multi-omics approaches, have shown that cancer cells can exist in a variety of transcriptionally distinct, yet co-existing states, some of which are already primed for metastatic progression or drug resistance. The plasticity of these states—i.e., the ability of cancer cells to reprogram across multiple states, either spontaneously or because of drug perturbations—and their homeostatic coexistence with other TME subpopulation, via paracrine molecular interactions, creates a constant challenge to therapeutic approaches by fostering the emergence of drug-resistance, tumor progression, and the creation of a pro-malignant, immunosuppressive milieu. Malignant states and transitions are only partially explained by sequential acquisition of somatic mutations, suggesting that they result from integration of a variety of cell-intrinsic and -extrinsic molecular cues that determine their lineage attribution, establishment, and interconversion. To date, several technical, clinical, and analytical challenges have hampered a comprehensive understanding of the natural biology of these processes in patients. Project 2 is dedicated to resolving the variability and plasticity of malignant cells and of the healthy cells that define the TME by developing and applying a battery of technical and analytical tools for the dissection of cancer heterogeneity at the single-cell level, and for the nomination, validation and testing of novel drivers of tumor-progression and therapy response and resistance. We will delineate these concepts in a defined biological context, that is the progression from a primary tumor towards brain-metastatic disease. To this end, we will leverage a series of innovations from CaST investigators, including (a) multi-modal single-cell profiling from archival tissues, (b) simultaneous low-pass whole-genome sequencing (lpWGS) of the same cell pool, (c) integrated single-cell and spatial single-cell transcriptomics, (d) analytical approaches to integrate and model multi-modal single-cell data in space, time and context of interactions among cells, (e) tools to elucidate cell state stability and transitions, (f) combinations of genome-editing perturbations with single-cell read outs that can be linked to drug screens via gene expression profiling, and (g) network-based Master Regulator analyses to elucidate mechanistic determinants of transcriptional cell state. This will be extended by experimental innovations, that (h) accurately model tumor progression in vivo and recapitulate entire human ecosystems, (i) enable labeling of metastatic niches coupled with single-cell genomics, and (j) provide a platform to test pharmacological modulation of cancer cell intrinsic and tumor-microenvironmental features predicted from human studies and modeling. The presented innovative framework will be broadly application to other cancer contexts.

侵略性癌症通常缺乏药物可操作的突变，并且不对免疫检查点反应 封锁，因此仅从靶向和免疫治疗中获得适度的临床益处。异质性 肿瘤微环境（TME）中转化和健康细胞都代表了一个关键的障碍 在癌症患者中获得更耐用的反应。最近使用多词方法的见解显示了 癌细胞可以存在于各种转录不同但共存的状态中，其中一些状态是 已经用于转移性进展或耐药性。这些状态的可塑性 - 即 癌细胞要在多个州进行重新编程，无论是赞助还是由于药物扰动，并 它们与其他TME亚种群共存，通过旁分子分子相互作用创造了一个 通过促进抗药性，肿瘤进展的出现，对治疗方法的持续挑战， 以及创建亲理性的免疫抑制环境。恶性状态和过渡仅部分是 通过顺序获得体突变的解释，表明它们是由多样性的整合而引起的 确定其谱系属性，建立和 互换。迄今为止，一些技术，临床和分析挑战阻碍了全面的 了解患者这些过程的自然生物学。项目2致力于解决 恶性细胞的可变性和可塑性以及通过开发和应用来定义TME的健康细胞的可变性和可塑性 一系列技术和分析工具，用于在单细胞水平上解剖癌症异质性，以及 为提名，验证和测试肿瘤产生和治疗反应的新驱动因素以及 反抗。我们将在定义的生物学环境中描述这些概念，这是主要的进展 肿瘤朝向脑部转移性疾病。为此，我们将利用演员的一系列创新 研究人员，包括（a）来自档案组织的多模式单细胞分析，（b）简单的低通 同一细胞池的全基因组测序（LPWG），（c）集成的单细胞和空间单细胞 转录组学，（d）在时空，时间和 细胞之间相互作用的背景，（e）阐明细胞状态稳定性和过渡的工具，（f）组合 具有单细胞读取的基因组编辑扰动，可以通过基因表达链接到药物筛选 分析和（g）基于网络的主调控器分析，以阐明机械确定器 转录细胞状态。这将通过实验创新来扩展，该创新（H）准确地对肿瘤进行了建模 体内进展并概括了整个人类生态系统，（i）启用转移壁ches的标签 使用单细胞基因组学，（J）提供了一个测试癌细胞内在的药物调节的平台 和人类研究和建模所预测的肿瘤微环境特征。提出的创新 框架将广泛应用于其他癌症环境。