Metabolic Regulators of Tumor Growth and Progression

项目摘要/摘要 代谢重编程是恶性肿瘤的一个标志，也是治疗靶点的来源。取得的进展 将重新编程的活动转化为新的疗法受到以下事实的限制：绝大多数知识 对肿瘤代谢的研究源于对培养细胞的研究，但与疾病生物学的相关性尚不清楚。我们 开发了直接从受试者和小鼠的肿瘤中评估代谢流量的方法，从而 消除文化遗物。我们的方法将肿瘤的多参数成像与内部成像相结合 手术输注同位素标记的营养物质，如13C-葡萄糖。我们使用来自手术前成像的信息 以指导组织采样，以便我们可以评估相关生物学特征(葡萄糖摄取， 灌注量、组织密度)对肿瘤代谢的影响。手术后，我们进行一段又一段的分析 测量肿瘤和邻近肺的流量，并研究其与组织学、遗传学和基因的关系 表情。我们在人类非小细胞肺癌(NSCLC)上发表的工作表明，a)与 长期以来的预期是，与邻近肺相比，这些肿瘤氧化了过量的葡萄糖；b)肿瘤氧化 除葡萄糖外，其他燃料和区域燃料的选择通过术前成像进行预测；以及c)广泛 人类肺部肿瘤之间存在代谢异质性，甚至在同一肿瘤的不同区域内也存在代谢异质性。 据我们所知，我们将临床成像与代谢流量分析相结合的多学科方法， 定量组织病理学和分子特征是独一无二的。在这里，我们建议将我们的计划扩展到 人类非小细胞肺癌新陈代谢，以解决未来几年新出现的紧迫问题。我们是 建立新的计算方法以更好地报告复杂代谢过程中发生变化的通量 人类非小细胞肺癌网络。我们正在建立一系列非小细胞肺癌患者的异种移植 研究，为我们在临床上观察到的假说提供了一个生物学试验台 学习。在患者和小鼠身上，我们将研究癌症期间代谢表型的演变。 进展，包括通过在常规和靶向治疗前后对代谢流量进行采样。我们 已经确定了一些候选燃料，现在正在给患者注射一系列13C和15N标记的燃料 以测试哪些营养物质被肿瘤消耗，以及它们的新陈代谢在体内是如何调节的。最后，我们 正在建立方法来解开构成肿瘤的不同细胞类型的代谢贡献 患者和小鼠的微环境。我们认为，了解癌症与癌症之间的代谢串扰 在完整的肿瘤微环境中，基质细胞是最艰巨的技术挑战之一 领域，但也是最好的机会，作出根本的新发现。总之，这些努力将 生成非小细胞肺癌代谢的独特视图，其细节、生物学准确性和 与人类疾病的相关性。它们有可能建立代谢调节的新范式 肿瘤的异质性，并预测哪些患者将对代谢治疗有反应。

Project Summary/Abstract Metabolic reprogramming is a hallmark of malignancy and a source of therapeutic targets. Progress in translating reprogrammed activities into new therapies is limited by the fact that the vast majority of knowledge in tumor metabolism is derived from studies in cultured cells with unknown relevance to disease biology. We developed methods to assess metabolic flux directly in tumors from human subjects and mice, thereby eliminating artifacts of culture. Our approach integrates multi-parametric imaging of the tumor with intra- operative infusions of isotope labeled nutrients like 13C-glucose. We use information from pre-surgical imaging to guide tissue sampling, so that we can assess the effects of relevant biological features (glucose uptake, perfusion, tissue density) on tumor metabolism. After surgery, we perform a fragment-by-fragment analysis of tumor and adjacent lung to measure fluxes and examine their relationship to histology, genetics and gene expression. Our published work in human non-small cell lung cancer (NSCLC) demonstrated that a) contrary to long-held expectations, these tumors oxidize glucose in excess compared to adjacent lung; b) tumors oxidize other fuels in addition glucose, and regional fuel choice is predicted by pre-surgical imaging; and c) extensive metabolic heterogeneity exists among human lung tumors and even within distinct regions of the same tumor. As far as we know, our multidisciplinary approach integrating clinical imaging with metabolic flux analysis, quantitative histopathology and molecular features is unique. Here we propose to expand our program in human NSCLC metabolism to address emerging, pressing questions over the next several years. We are establishing novel computational methods to better report altered fluxes throughout the complex metabolic networks of human NSCLC. We are establishing a series of NSCLC xenografts from patients recruited to the study, providing us with a biological test bed for hypotheses stimulated by observations made in the clinical studies. In patients and mice, we will examine the evolution of metabolic phenotypes during cancer progression, including by sampling metabolic flux before and after conventional and targeted therapies. We have identified a number of candidate fuels and are now infusing patients with a series of 13C and 15N-labeled nutrients to test which ones are consumed by tumors and how their metabolism is regulated in vivo. Finally, we are establishing methods to disentangle the metabolic contributions of distinct cell types comprising the tumor microenvironment in patients and mice. We believe that understanding metabolic crosstalk between cancer and stromal cells in the intact tumor microenvironment is one of the most daunting technical challenges in the field, but also the best opportunity to make fundamentally new discoveries. Altogether, these efforts will generate a unique view of NSCLC metabolism with an unprecedented level of detail, biological accuracy and relevance to human disease. They have the potential to establish new paradigms in metabolic regulation and tumor heterogeneity and to predict which patients will respond to metabolic therapies.