Project 2 Human Tumor Analysis

项目2 人类肿瘤分析

• 批准号: 10729467
• 负责人: SYLVIA KATINA PLEVRITIS
• 金额: $ 52.27万
• 依托单位: STANFORD UNIVERSITY
• 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/10729467
• 关键词: Architecture; Awareness; Biological Markers; Biology; Cancer Etiology; Cancer Patient; Cell Communication; Cell model; Cells; Cessation of life; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Complex; Data; Disseminated Malignant Neoplasm; Drug Targeting; Ecosystem; Endothelial Cells; Environment; Epithelium; Extracellular Matrix; Formalin; Freezing; Genes; Genetic Transcription; Growth; Head and Neck Squamous Cell Carcinoma; Heterogeneity; Host Defense Mechanism; Human; Immune; Immune Tolerance; Immune system; Link; Lung Adenocarcinoma; Lymph Node Involvement; Lymph Node Tissue; Malignant - descriptor; Malignant Neoplasms; Maps; Metastatic Neoplasm to Lymph Nodes; Modeling; Molecular Analysis; Neoplasm Metastasis; Organ; Organoids; Paraffin Embedding; Patients; Pattern; Positive Lymph Node; Primary Neoplasm; Process; Property; Proteomics; Research; Role; Sampling; Sentinel Lymph Node; Series; Site; Solid; Specimen; Stromal Cells; Stromal Neoplasm; Systems Biology; Technology; Testing; Time; Tissues; Tumor Biology; biocomputing; cancer cell; cell type; cohort; human model; human tissue; imaging platform; in situ imaging; insight; lymph nodes; markov model; mouse model; neoplastic cell; novel; pre-clinical; single cell sequencing; single-cell RNA sequencing; spatial integration; spatiotemporal; temporal measurement; treatment strategy; tumor; tumor microenvironment

SUMMARY/ABSTRACT: PROJECT 2 Metastasis is the primary cause of cancer-related death. Our recent evidence establishes a new paradigm, “lymph node tolerization,” in which the lymph node (LN) tissue environment creates a conditioned, systemic metastatic state across tissues and organs. This proposal aims to identify and characterize unidentified changes that create tolerize LNs, leading to the discovery of new biomarkers, drug targets, and treatment strategies. Using a spatial systems biology approach that combines multiplexed in situ imaging with single-cell RNA sequencing technologies, we will characterize tumor microenvironments across the host metastatic ecosystem, in HNSCC and LUAD. We hypothesize that spatially resolved stromal-immune interactions in LNs together with stromal-malignant properties in a primary tumor set the stage for metastasis. We will explore mechanistic properties of these processes using organoid models of human-derived cells and mouse models. In Aim 1, we will use using single-cell spatial proteomics to identify a pro-metastatic microenvironment in uninvolved LNs of HNSCC and LUAD cancer patients by reconstructing and comparing spatially resolved tumor-stroma-immune colocalization patterns of patient-derived uninvolved LNs, involved LNs, and primary tumors. These analyses will compare cell types and cell-cell co-localization patterns in the tissue environments of N0 and N+ patients. In addition, we will probe cell composition and colocalization patterns together with extracellular matrix architecture to ascertain the role of ECM in establishing and maintaining the pro-metastatic microenvironment in uninvolved LNs. In Aim 2, we will discover cell-cell interactions in uninvolved LNs that predispose them to colonization by malignant cells by reconstructing and comparing cell-cell interactions uninvolved LNs, involved LNs, and primary tumors inferred through integrative analysis of spatial information with single-cell RNA-sequencing. We will develop novel biocomputational approaches to integrate spatial features from CODEX with single cell RNA sequencing data to identify proximal cell-cell interactions among tumor-stromal and stromal-immune cell types associated with LN metastases. We will then evaluate selected cell-cell interactions in organoid models of human-derived cells, including perturbation with CRISPR-facilitated gene editing to reveal mechanistic insights. In Aim 3, we will predict spatiotemporal progression in tumor- stromal and stromal-immune colocalization patterns through spatially-aware Markov modeling and relate these patterns to changes in human-derived LNs and primary tumors associated with metastatic progression. We will build a spatially aware Markov model using spatially resolved time series data generated using tumor-stromal and immune-stromal organoids generated from human-derived cells, to identify spatial motifs of tumor-stromal and immune-stromal spatial patterning. This approach will illuminate spatiotemporal features of human LN metastasis, toward defining mechanistic features of the metastatic cascade.

总结/摘要：项目2 转移是癌症相关死亡的主要原因。我们最近的证据建立了一个新的范例， “淋巴结耐受化”，其中淋巴结（LN）组织环境产生条件性、全身性耐受。 在组织和器官中转移。这项建议旨在查明和描述未查明的 产生耐受性LN的变化，导致发现新的生物标志物，药物靶点和治疗方法 战略布局使用空间系统生物学方法，将多路复用原位成像与单细胞 RNA测序技术，我们将表征整个宿主的肿瘤微环境转移 生态系统，在HNSCC和LUAD。我们假设LN中空间分辨的基质-免疫相互作用 与原发性肿瘤中的间质恶性性质一起为转移奠定了基础。我们将探讨 使用人源细胞的类器官模型和小鼠模型研究这些过程的机械性质。 在目标1中，我们将使用单细胞空间蛋白质组学来鉴定肿瘤细胞中的促转移微环境。 HNSCC和LUAD癌症患者的未受累淋巴结的空间分辨重建和比较 患者来源的未受累淋巴结、受累淋巴结和原发性淋巴结的肿瘤-间质-免疫共定位模式 肿瘤的这些分析将比较组织环境中的细胞类型和细胞-细胞共定位模式 N 0和N+患者。此外，我们将探测细胞组成和共定位模式， 细胞外基质的结构，以确定ECM在建立和维持促转移性细胞因子中的作用。 微环境中不参与的LN。在目标2中，我们将发现未参与的LN中的细胞-细胞相互作用， 通过重建和比较细胞-细胞相互作用， 通过空间信息的综合分析推断未受累淋巴结、受累淋巴结和原发性肿瘤 单细胞RNA测序。我们将开发新的生物计算方法来整合空间 来自CODEX的功能与单细胞RNA测序数据，以识别其中的近端细胞间相互作用 与LN转移相关的肿瘤基质和基质免疫细胞类型。然后我们将评估选定的 人源细胞的类器官模型中的细胞-细胞相互作用，包括CRISPR促进的干扰 基因编辑来揭示机械的见解。在目标3中，我们将预测肿瘤的时空进展- 通过空间感知马尔可夫建模的基质和基质免疫共定位模式，并将这些 与转移进展相关的人源性LN和原发性肿瘤的变化模式。我们将 使用利用肿瘤间质细胞生成的空间分辨时间序列数据构建空间感知马尔可夫模型， 和从人源性细胞产生的免疫基质类器官，以鉴定肿瘤基质细胞的空间基序。 和免疫基质空间模式。这种方法将阐明人类LN的时空特征 转移，以确定转移级联机制的特点。