Exploring O-glycoproteomics to prevent metabolic radioresistance in the tumor microenvironment

探索O-糖蛋白组学以预防肿瘤微环境中的代谢放射抗性

基本信息

批准号：
10684199
负责人：
Gina Bouchard
金额：
$ 15.78万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10684199
关键词：
3-Dimensional Affect Anabolism Cancer Etiology Cancer Patient Caring Cells Cessation of life Clinical Coculture Techniques Data Development Plans Diagnosis Disease Endothelium Event Faculty Fibroblasts Fluorescence Fractionated radiotherapy Glucose Glycobiology Glycoproteins Goals Harvest Hexosamines Immune Impairment In Situ In Vitro Lead Lung Adenocarcinoma Lung Neoplasms Machine Learning Malignant - descriptor Malignant Neoplasms Malignant neoplasm of lung Maps Mass Spectrum Analysis Measures Mentors Mesenchymal Metabolic Metabolic Marker Metabolic Pathway Modeling Modification Molecular Target Neighborhoods Organoids Outcome Outcome Measure Pathway interactions Patients Pattern Phenotype Phosphorylation Polysaccharides Post-Translational Protein Processing Primary Neoplasm Protein Glycosylation Protein Region Proteins Radiation Radiation Tolerance Radiation therapy Radiobiology Refractory Research Personnel Resolution Resources Role Signal Transduction Stromal Cells Stromal Neoplasm Structure Systems Biology Techniques Testing Therapeutic Thoracic Oncology Time Tissues Treatment Failure Visualization Work biocomputing cancer cell cancer survival cell behavior cell dimension cell type glycoproteomics glycosylation imaging modality improved in vivo innovation insight multiplexed imaging new therapeutic target novel strategies preservation prevent radiation resistance radioresistant sugar survival outcome tenure track tool treatment response tumor tumor heterogeneity tumor metabolism tumor microenvironment tumorigenesis

3-Dimensional Affect Anabolism Cancer Etiology Cancer Patient Caring Cells Cessation of life Clinical Coculture Techniques Data Development Plans Diagnosis Disease Endothelium Event Faculty Fibroblasts Fluorescence Fractionated radiotherapy Glucose Glycobiology Glycoproteins Goals Harvest Hexosamines Immune Impairment In Situ In Vitro Lead Lung Adenocarcinoma Lung Neoplasms Machine Learning Malignant - descriptor Malignant Neoplasms Malignant neoplasm of lung Maps Mass Spectrum Analysis Measures Mentors Mesenchymal Metabolic Metabolic Marker Metabolic Pathway Modeling Modification Molecular Target Neighborhoods Organoids Outcome Outcome Measure Pathway interactions Patients Pattern Phenotype Phosphorylation Polysaccharides Post-Translational Protein Processing Primary Neoplasm Protein Glycosylation Protein Region Proteins Radiation Radiation Tolerance Radiation therapy Radiobiology Refractory Research Personnel Resolution Resources Role Signal Transduction Stromal Cells Stromal Neoplasm Structure Systems Biology Techniques Testing Therapeutic Thoracic Oncology Time Tissues Treatment Failure Visualization Work biocomputing cancer cell cancer survival cell behavior cell dimension cell type glycoproteomics glycosylation imaging modality improved in vivo innovation insight multiplexed imaging new therapeutic target novel strategies preservation prevent radiation resistance radioresistant sugar survival outcome tenure track tool treatment response tumor tumor heterogeneity tumor metabolism tumor microenvironment tumorigenesis

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项目摘要

PROJECT SUMMARY Radiotherapy (RT) is often the only curative option for patients with inoperable tumors. However, radiation is also known to impair tumor metabolism, leading to radioresistance, the main reason for RT failure. Metabolic reprogramming (MR) in cancer is defined as the ability of the tumor to rewire its energy to fulfill the needs for tumorigenesis and progression. Our group observed for the first time that MR toward the Hexosamine Biosynthesis Pathway (HBP), an understudied glucose pathway leading to protein glycosylation, is associated with poor survival in the lung adenocarcinoma. Precisely, we showed that this metabolic switch happens primarily in Cancer-Associated Fibroblasts (CAFs). This suggests that CAFs redirect their glucose toward HBP, which increases O-glycosylation, a Post-Translational Modification (PTM) known to modulate radioresistance. However, very little is known about 1) which proteins are O-glycosylated after MR toward HBP and 2) how these PTMs affect the cellular behavior and modulate radioresistance. My preliminary results show that metabolic cooperation between cancer and stromal cells alters protein O-glycosylation in both cell types. Therefore, I hypothesize that tumor-stroma crosstalk in the Tumor Microenvironment (TME), leading to changes in the O-glycoproteome, plays a role in radioresistance. To validate this hypothesis, we developed a novel approach that precisely measures the outcome of MR towards HBP (e.g., O-glycoproteome) in the context of tumor-stroma crosstalk. We propose to apply this technique to tumor-stroma organoids designated here as “assembloids” that recapitulate metabolically heterogeneous cell neighborhoods and characterize their O-glycoproteome before and after RT. First, to visualize HBP metabolic heterogeneity in the TME, I will construct an in-situ map of the primary tumor compartments (endothelial, malignant, fibroblast, and immune) enriched for HBP metabolic markers and glycoform structures, using CODEX. CODEX is a cutting- edge multiplexed imaging method that allows for single-cell quantification of up to 50 markers in situ (aim 1). Then, I will deconvolute cell neighborhoods using machine learning and clustering biocomputational approaches to quantify and inform which neighborhoods are active regions of protein O-glycosylation. In aim 2, I will recapitulate HBP-enriched cell neighborhoods using a 3D assembloid model, irradiate them, then characterize metabolic radioresistance patterns using CODEX. Lastly, in aim 3, I will analyze the O-glycoproteome and spatial information of radioresistant assembloids. The O-glycoproteins or upstream drivers to O-glycosylation involved in critical tumor-stroma interactions will be inhibited in an attempt to restore radiosensitivity. The resulting data will generate the first hypothesis synthesis tool exploring an understudied dimension of cell signaling, the O- glycoproteome. They will lead to the discovery of new molecular targets involved in both tumor metabolism and stromal interactions with the primary goal of improving RT response in cancer patients with inoperable tumors.

项目摘要放射疗法（RT）通常是无法手术肿瘤患者的唯一治疗选择。但是，辐射是也已知会损害肿瘤代谢，导致放射性，这是RT衰竭的主要原因。代谢癌症中的重编程（MR）定义为肿瘤重新连接能量满足需求的能力肿瘤发生和进展。我们的小组首次观察到己胺先生生物合成途径（HBP）是一种导致蛋白质糖基化的葡萄糖途径，是相关的在肺腺癌中生存不良。确切地说，我们表明这种代谢开关发生了主要在癌症相关的成纤维细胞（CAF）中。这表明CAFS将其葡萄糖重定向到HBP，这是增加O-糖基化，这是一种已知可调节辐射抗性的后翻译后修饰（PTM）。然而，关于1）MR朝向HBP和2的蛋白众所周知1）。这些PTM如何影响细胞行为并调节放射线。我的初步结果显示癌症和基质细胞之间的代谢合作改变了两种细胞类型的蛋白O-糖基化。因此，我假设肿瘤微环境（TME）中的肿瘤 - 细胞瘤串扰，导致 O-糖蛋白酶的变化在辐射抗性中起作用。为了验证这一假设，我们发展了一种精确衡量MR对HBP（例如O-糖蛋白酶）的结果的新方法肿瘤 - 基质串扰的背景。我们建议将此技术应用于肿瘤细节器官在此指定为“组装”，该“组装”概括了代谢上异质的细胞社区和在RT之前和之后表征其O-糖蛋白酶。首先，可视化HBP代谢异质性 TME，我将构建原发性肿瘤室的原位图（内皮，恶性，成纤维细胞和使用法典富含HBP代谢标记和糖型结构的免疫）。 codex是一种替代边缘多路复用成像方法，可允许单细胞量化多达50个原位标记（AIM 1）。然后，我将使用机器学习和聚类生物计算方法去涉及细胞社区量化和告知哪些邻居是蛋白O-糖基化的活性区域。在AIM 2中，我会使用3D装配模型概括了富含HBP的细胞邻域，然后进行照射，然后表征使用法典的代谢辐射模式。最后，在AIM 3中，我将分析O-糖蛋白酶和空间放射性组件的信息。涉及O-糖基化的O-糖蛋白或上游驱动器在关键的肿瘤中，将抑制肿瘤的相互作用，以恢复放射线敏感性。结果数据将生成第一个假设合成工具探索细胞信号传导的知识维度，即O- 糖蛋白酶。它们将导致发现与肿瘤代谢和基质相互作用与改善无法手术肿瘤癌症患者的RT反应的主要目标。