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npj Metabolic Health and Disease:超越葡萄糖和Warburg——在癌症代谢模型中找到最佳点

npj Metabolic Health and Disease:Beyond glucose and Warburg——finding the sweet spot in cancer metabolism models

Nature 等信源发布 2024-09-02 18:50

可切换为仅中文


AbstractAdvances in cancer biology have highlighted metabolic reprogramming as an essential aspect of tumorigenesis and progression. However, recent efforts to study tumor metabolism in vivo have identified some disconnects between in vitro and in vivo biology. This is due, at least in part, to the simplified nature of cell culture models and highlights a growing need to utilize more physiologically relevant approaches to more accurately assess tumor metabolism.

摘要癌症生物学的进展突出了代谢重编程作为肿瘤发生和发展的重要方面。然而,最近研究体内肿瘤代谢的努力已经确定了体外和体内生物学之间的一些脱节。这至少部分是由于细胞培养模型的简化性质,并强调越来越需要利用更生理相关的方法来更准确地评估肿瘤代谢。

In this review, we outline the evolution of our understanding of cancer metabolism and discuss some discrepancies between in vitro and in vivo conditions. We describe how the development of physiological media, in combination with advanced culturing methods, can bridge the gap between in vitro and in vivo metabolism..

在这篇综述中,我们概述了我们对癌症代谢理解的演变,并讨论了体外和体内条件之间的一些差异。我们描述了生理培养基的发展如何与先进的培养方法相结合,可以弥合体外和体内代谢之间的差距。。

IntroductionAltered metabolism is a pivotal feature of cancer cells. Cancer cells reprogram metabolic pathways to support dysregulated cell growth and proliferation compared to non-malignant cells. Examples of altered metabolic pathways in cancer include reprogrammed aerobic glycolysis, glutamine catabolism, redox homeostasis, and numerous biosynthetic processes, all of which support the energetic and biosynthetic demands of deregulated cell growth1,2.

引言改变的代谢是癌细胞的关键特征。与非恶性细胞相比,癌细胞重新编程代谢途径以支持失调的细胞生长和增殖。癌症中代谢途径改变的例子包括重编程的有氧糖酵解,谷氨酰胺分解代谢,氧化还原稳态和许多生物合成过程,所有这些都支持失调细胞生长的能量和生物合成需求1,2。

Metabolic rewiring can support other hallmarks of cancer, such as proliferative capacity, immune response, and metastasis3,4,5. Thus, understanding metabolic reprogramming in cancer can lead to important insights into the underlying pathophysiology of this disease.The origins of metabolic alterations in cancer can be traced back over a century.

代谢重新布线可以支持癌症的其他标志,例如增殖能力,免疫反应和转移3,4,5。因此,了解癌症中的代谢重编程可以导致对这种疾病的潜在病理生理学的重要见解。癌症代谢改变的起源可以追溯到一个多世纪。

In 1924, Otto Warburg made a discovery that has now become synonymous with the modern concept of metabolic reprogramming in cancer (several excellent reviews detailing his work are available6,7,8,9). Warburg’s seminal observation, now referred to as the “Warburg Effect”, was that cultured tumor tissues displayed high rates of glucose uptake and lactate secretion, even in the presence of adequate oxygen.

1924年,奥托·沃伯格(OttoWarburg)发现了一个与现代癌症代谢重编程概念同义的发现(有几篇详细介绍他的工作的优秀评论6,7,8,9)。Warburg的开创性观察(现在称为“Warburg效应”)是,培养的肿瘤组织即使在氧气充足的情况下也显示出较高的葡萄糖摄取率和乳酸分泌率。

This starkly contrasts the metabolism of the non-malignant cells studied by Warburg’s contemporaries Herbert Crabtree and Louis Pasteur. In non-malignant cells, Crabtree and Pasteur observed a metabolic balance between glycolysis and oxidative phosphorylation (OXPHOS). Increasing glucose levels could impair OXPHOS, while inversely, high oxygen levels could impair glycolysis10,11.

这与Warburg同时代的HerbertCrabtree和LouisPasteur研究的非恶性细胞的代谢形成了鲜明对比。在非恶性细胞中,Crabtree和Pasteur观察到糖酵解和氧化磷酸化(OXPHOS)之间的代谢平衡。增加葡萄糖水平可能会损害OXPHOS,而相反,高氧水平可能会损害糖酵解10,11。

Thus, an important aspect of the Warburg Effect is the disproportion between glycolysis and respiration. To this day there are still misconceptions about Warburg’s work, or more specifically, Warburg’s inte.

。直到今天,人们仍然对沃伯格的工作,或者更具体地说,对沃伯格的inte有误解。

Advancing spatial techniques to better understand intratumoral heterogeneity and cell-cell crosstalk.

推进空间技术以更好地了解肿瘤内异质性和细胞间串扰。

Continuing development of additional physiologic media to better characterize the effects of different in vivo environments such as metastatic organs, diets, and tumor microenvironments.

继续开发其他生理介质,以更好地表征不同体内环境(如转移器官,饮食和肿瘤微环境)的影响。

Investigating cancer metabolism directly in patients, expanding to additional cancer types, metastatic sites, and other stable isotope tracers.

直接研究患者的癌症代谢,扩展到其他癌症类型,转移部位和其他稳定同位素示踪剂。

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Download referencesAcknowledgementsWe want to thank Aslan Tasdogan, Kristina Cameron, and members of the Faubert Laboratory for their comments and critiques. Figures were generated using BioRender, under the University of Chicago license.Author informationAuthors and AffiliationsDepartment of Medicine, Section of Hematology/Oncology, University of Chicago, Chicago, IL, USANia G.

下载参考文献致谢我们要感谢Aslan Tasdogan,Kristina Cameron和Faubert实验室成员的评论和批评。数字是使用芝加哥大学许可证下的BioRender生成的。作者信息作者和附属机构芝加哥大学血液学/肿瘤学系医学系,伊利诺伊州芝加哥,USANia G。

Hammond, Robert B. Cameron & Brandon FaubertAuthorsNia G. HammondView author publicationsYou can also search for this author in.

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PubMed Google ScholarContributionsN.G.H., R.B.C. and B.F. conceived this review. N.G.H. and R.B.C. wrote the manuscript, B.F., supervised and revised the manuscript. All authors prepared the Figures.Corresponding authorCorrespondence to

PubMed谷歌学术贡献。G、 H.,R.B.C.和B.F.构思了这篇评论。N、 G.H.和R.B.C.撰写了手稿B.F.,监督并修改了手稿。所有作者都准备了这些数字。对应作者对应

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