Systems biology of HIF metabolism in cancer
Systems biology of HIF metabolism in cancer
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发表时间：
2012-10
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影响因子：
2.7
通讯作者：
Emily G. Armitage;H. Westerhoff;Helen L. Kotze;R. Goodacre;N. Lockyer;K. Williams
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作者：
Emily G. Armitage;H. Westerhoff;Helen L. Kotze;R. Goodacre;N. Lockyer;K. Williams
2012年9月，曼彻斯特大学工程与物理科学学院向哲学博士艾米丽·格雷斯·阿米蒂奇提交的题为《HIF代谢在癌症中的系统生物学》的论文摘要癌症是每年在全球范围内造成大量死亡的最具破坏性的人类疾病之一。癌症研究是生命科学中最大的领域之一，尽管在过去的几十年里取得了许多令人震惊的突破和贡献，但关于癌症的功能仍有相当多的东西需要揭示，这将改善诊断、预后和治疗。由于已知癌症涉及广泛的过程，从系统的角度应用方法来研究它可能会揭示癌症的新特性。系统生物学正在成为生命科学中越来越受欢迎的工具。该方法已被应用于许多生物和生物医学分析，利用最近的技术进步，使样品的高通量分析和计算建模成为可能。本论文研究了低氧诱导因子-1(HIF-1)对肿瘤代谢的影响，HIF-1被认为是与表型关系最密切的实体。众所周知，这种转录因子调节多种基因和蛋白质，以促进在低氧环境中的生存，这种低氧环境在固体肿瘤中很普遍。然而，它对代谢组的影响还没有得到很好的描述。通过揭示HIF-1作为一个系统对代谢组的影响，人们希望能够揭示表型特征、指示癌症功能的关键代谢途径以及未来癌症治疗的潜在靶点。该系统已使用两个细胞模型进行研究：小鼠肝细胞癌和人结肠癌，其中代谢已使用一系列分析平台进行了描述。在每个模型中，野生型细胞与缺乏HIF-1的细胞进行比较，以揭示其对细胞代谢的影响。气相色谱-质谱法(GC-MS)和超高效液-质联用法(UHPLCMS)已被用于研究暴露在各种氧气条件下的细胞的代谢特征。此外，飞行时间二次离子质谱仪(ToF SIMS)已被用于从野生型细胞和HIF-1功能障碍的细胞培养的多细胞肿瘤球体的成像质谱分析，以代表小的起始肿瘤。在代谢谱中使用这些技术，已经有可能揭示与氧和HIF-1对癌症代谢的影响有关的代谢物，以及可能在未来的治疗中靶向的关键途径和枢纽。使用成像质谱学，已经有可能在原位定位代谢物，揭示肿瘤结构如何与功能有关。最后，为了更好地理解癌症代谢的系统特性，采用了一种新的方法来考虑代谢物在氧气水平或功能HIF-1的存在或不存在时如何相互关联。已发现与氧和/或HIF-1有不同相关性的代谢物已被映射到人类代谢网络上，以确定其基于网络的来源。这使得可以模拟受氧和HIF-1影响最大的新陈代谢网络，突出了HIF-1介导的癌细胞存活的关键机制。
AbstractThe University of ManchesterFaculty of Engineering and Physical SciencesAbstract of thesis entitled ?Systems Biology of HIF Metabolism in Cancer?Submitted by Emily Grace Armitage for the degree of Doctor of Philosophy, September 2012Cancer is one of the most devastating human diseases that cause a vast number of mortalities worldwide each year. Cancer research is one of the largest fields in the life sciences and despite many astounding breakthroughs and contributions over the past few decades, there is still a considerable amount to unveil on the function of cancer that would improve diagnostics, prognostics and therapy. Since cancer is known to involve a wide range of processes, applying methods to study it from a systems perspective could reveal new properties of cancer. Systems biology is becoming an increasingly popular tool in the life sciences. The approach has been applied to many biological and biomedical analyses drawing upon recent advancements in technology that make high throughput analyses of samples and computational modelling possible. In this thesis, the effect of hypoxia inducible factor-1 (HIF-1) on cancer metabolism, the entity considered most closely related to phenotype has been investigated. This transcription factor is known to regulate a multitude of genes and proteins to promote survival in a low oxygen environment that is prevalent in solid tumours. However its effect on the metabolome is less well characterised. By revealing the effect of HIF-1 on the metabolome as a system it is hoped that phenotypic signatures, key metabolic pathways indicative of cancer function and potential targets for future cancer therapy, can be revealed.The system has been studied using two cell models: mouse hepatocellular carcinoma and human colon carcinoma, whereby metabolism has been profiled using a range of analytical platforms. In each model, wild type cells have been compared to cells deficient in HIF-1 to reveal its effect on cellular metabolism. Gas chromatography mass spectrometry (GC MS) and ultra high performance liquid chromatography - mass spectrometry (UHPLC MS) have been employed for metabolic profiling of cells exposed to a range of oxygen conditions. Additionally, time-of-flight secondary ion mass spectrometry (ToF SIMS) has been employed for imaging mass spectrometric analysis of multicellular tumour spheroids cultured from wild type cells and cells with dysfunctional HIF-1 to represent small initiating tumours. Using these techniques in metabolic profiling it has been possible to reveal metabolites associated with the effect of oxygen and HIF-1 on cancer metabolism along with key pathways and hubs that could be targeted in future therapy. Using imaging mass spectrometry it has been possible to localise metabolites in situ revealing how tumour structure relates to function. Finally, a novel approach to consider how metabolites are correlated with one another in the response to oxygen level or presence or absence of functional HIF-1 has been undertaken to better understand the systems properties of cancer metabolism. Metabolites found to be differently correlated with respect to oxygen and/or HIF-1 have been mapped onto a human metabolic network to determine their network-based origins. This allowed the simulation of sub-networks of metabolism most affected by oxygen and HIF-1, highlighting the key mechanisms in HIF 1 mediated cancer cell survival.