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

项目摘要 放射治疗（RT）通常是无法手术的肿瘤患者的唯一治疗选择。辐射是 也已知会损害肿瘤代谢，导致放射抗性，这是RT失败的主要原因。代谢 癌症中的重编程（MR）被定义为肿瘤重新连接其能量以满足肿瘤细胞的需要的能力。 肿瘤的发生和发展。我们的小组首次观察到， 生物合成途径（HBP）是一种未充分研究的导致蛋白质糖基化的葡萄糖途径， 肺腺癌的存活率很低。准确地说，我们发现这种代谢转换主要发生在 癌症相关成纤维细胞（CAFs）这表明CAFs将其葡萄糖重定向到HBP， 增加O-糖基化，这是一种已知可调节辐射抗性的翻译后修饰（PTM）。 然而，人们对1）哪些蛋白质在MR后被O-糖基化为HBP和2）知之甚少 这些PTM如何影响细胞行为和调节辐射抗性。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中的蛋白质O-糖基化。 因此，我假设肿瘤微环境（TME）中的肿瘤-间质串扰，导致 O-糖蛋白质组的变化在辐射抗性中起作用。为了验证这一假设，我们开发了 一种精确测量MR对HBP的结果的新方法（例如，O-糖蛋白组） 肿瘤间质串扰的背景。我们建议将这项技术应用于肿瘤间质类器官 在此称为“类胡萝卜素”，其概括了代谢异质的细胞邻域， 在RT前后表征它们的O-糖蛋白质组。首先，为了可视化HBP代谢异质性， TME，我将构建一个原发性肿瘤区室（内皮，恶性，成纤维细胞， 免疫）富集HBP代谢标志物和糖型结构。CODEX是一种切割- 边缘多路复用成像方法，允许单细胞定量多达50个标记物原位（目标1）。 然后，我将使用机器学习和聚类生物计算方法去卷积细胞邻域 以量化和告知哪些邻域是蛋白质O-糖基化的活性区域。在目标2中，我将 使用3D仿人模型概括HBP富集的细胞邻域，照射它们，然后表征 代谢辐射抗性模式使用CODEX。最后，在目标3中，我将分析O-糖蛋白质组和空间结构， 关于抗辐射类风湿的信息。参与O-糖蛋白或O-糖基化的上游驱动因素 在关键的肿瘤-间质相互作用中，将被抑制以试图恢复放射敏感性。结果数据 将产生第一个假设合成工具，探索细胞信号传导的一个未充分研究的维度，O- 糖蛋白质组它们将导致发现新的分子靶点，这些靶点涉及肿瘤代谢和 间质相互作用，主要目标是改善患有不可手术肿瘤的癌症患者的RT反应。

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.