Mammalian models for integrated metabolic and molecular profiling of malignant glioma

项目总结/摘要 转化性癌症研究需要强大的临床前模型，以最有效地研究潜在的癌症。 研究疾病生物学并开发新的治疗方法。虽然所有的模型都是不完美的，但必须了解 每个模型系统（例如，细胞培养、异种移植）概括了特定的分子和 人类肿瘤的功能特征。这可能与研究代谢改变特别相关， 这是癌症的标志，因为即使是环境的细微变化也会极大地影响癌症的代谢表型。 肿瘤此外，由于癌症代谢受致癌信号传导的严格调节，因此， 给定恶性肿瘤内的改变可能引起独特的代谢特征;这可能极大地影响 肿瘤增殖和生长的代谢途径依赖性。为了最好地确定临床前 为了保留人类癌症的代谢特征，这需要交叉比较匹配的患者 组织和临床前肿瘤模型与各种遗传改变。然而，如此全面的 调查仍有待进行。该提案将执行一个综合的代谢和分子 匹配的人肿瘤、直接来自患者的原位异种移植物（GliomaPDOX）和细胞的表征 胶质母细胞瘤（GBM）-最致命的人类恶性肿瘤之一，也存在于 独特的大脑代谢环境在目标1中，稳定同位素标记的代谢示踪和液相色谱- 将使用质谱法（LC-MS）交叉比较前瞻性匹配的代谢表型 GBM患者肿瘤、GliomaPDOX和细胞系，以确定保留的代谢特征 和/或从患者到临床前模型的丢失。目的2建议确定，在遗传多样性的临床前 GliomaPDOX模型，无论特定的代谢表型是否与不同的分子特征一致。最后在 目的3，将进行体内基因敲低实验以评估是否测量代谢产物。 表型代表胶质瘤PDOX生长、侵袭和存活的可靶向依赖性。统称 本申请中提出的研究将为临床前GBM模型的可翻译性提供重要的见解 用于研究肿瘤代谢;这最终可能对开发新的 针对GBM中的代谢依赖性的治疗剂，以及潜在的其他恶性肿瘤。

PROJECT SUMMARY/ABSTRACT Translational cancer research requires robust preclinical models to most effectively investigate the underlying biology of disease and develop new therapeutics. While all models are imperfect, it is essential to understand the degree by which each model system (e.g., cell culture, xenograft) recapitulates specific molecular and functional characteristics of human tumors. This may be particularly relevant for studying altered metabolism, a hallmark of cancer, as even subtle changes to the environment can greatly impact the metabolic phenotype of a tumor. Moreover, as cancer metabolism is tightly regulated by oncogenic signaling, the diversity of molecular alterations within a given malignancy may elicit unique metabolic characteristics; which, may greatly influence metabolic pathway dependencies for tumor proliferation and growth. To best determine the fidelity of preclinical models in preserving the metabolic features of human cancer, this requires cross-comparing matched patient tissue and preclinical models across tumors with various genetic alterations. However, such a comprehensive investigation has yet to be undertaken. This proposal will perform an integrated metabolic and molecular characterization of matched human tumors, direct-from-patient orthotopic xenografts (GliomaPDOX), and cell lines from patients with glioblastoma (GBM) – one of the most lethal human malignancies that also reside within the unique brain metabolic milieu. In Aim 1, stable isotope-labeled metabolic tracing and liquid chromatography- mass spectrometry (LC-MS) will be used to cross-compare the metabolic phenotypes of prospectively matched GBM patient tumors, GliomaPDOX, and cell lines to determine the metabolic characteristics that are preserved and/or lost from patient to preclinical model. Aim 2 proposes to determine, in genetically diverse preclinical GliomaPDOX models, whether specific metabolic phenotypes align with distinct molecular signatures. Finally, in Aim 3, in vivo genetic knockdown experiments will be performed to assess whether measured metabolic phenotypes represent targetable dependencies for GliomaPDOX growth, invasion, and survival. Collectively, the studies proposed in this application will provide critical insight into the translatability of preclinical GBM models for studying tumor metabolism; which, may ultimately have important implications for developing new therapeutics against metabolic dependencies in GBM, and potentially, other malignancies.