受刺激的 Beta 细胞与癌细胞有什么共同之处?

IF 2 4区 生物学 Q2 BIOLOGY Biosystems Pub Date : 2024-06-12 DOI:10.1016/j.biosystems.2024.105257
Marko Marhl
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引用次数: 0

摘要

这项研究调查了受刺激的胰腺β细胞和癌细胞之间的代谢相似性,重点是葡萄糖和谷氨酰胺代谢。为了应对 2 型糖尿病(T2D)和癌症这一重大公共卫生挑战,我们旨在加深对胰岛素分泌和细胞增殖驱动机制的理解。我们对无凋亡周期和 NADPH 在生物合成中的作用进行了分析,阐明了它们在这两个过程中的重要功能。此外,我们还指出,两种细胞类型都具有由 Nrf2 信号通路、谷胱甘肽合成和 UCP2 上调介导的抗氧化反应。值得注意的是,UCP2 促进了 C4 代谢物的转移,增强了还原性 TCA 循环代谢。此外,我们还观察到,缺氧反应在刺激后的β细胞中是短暂的,但在癌细胞中却是持续的。通过综合这些见解,这项研究可为治疗 T2D 提出新的治疗目标,同时强调受刺激的 beta 细胞和癌细胞的共同代谢策略。这种比较分析不仅揭示了这些情况下代谢的复杂性,还强调了代谢途径在细胞功能和存活中的关键作用,为应对 T2D 和癌症挑战提供了新的视角。
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What do stimulated beta cells have in common with cancer cells?

This study investigates the metabolic parallels between stimulated pancreatic beta cells and cancer cells, focusing on glucose and glutamine metabolism. Addressing the significant public health challenges of Type 2 Diabetes (T2D) and cancer, we aim to deepen our understanding of the mechanisms driving insulin secretion and cellular proliferation. Our analysis of anaplerotic cycles and the role of NADPH in biosynthesis elucidates their vital functions in both processes. Additionally, we point out that both cell types share an antioxidative response mediated by the Nrf2 signaling pathway, glutathione synthesis, and UCP2 upregulation. Notably, UCP2 facilitates the transfer of C4 metabolites, enhancing reductive TCA cycle metabolism. Furthermore, we observe that hypoxic responses are transient in beta cells post-stimulation but persistent in cancer cells. By synthesizing these insights, the research may suggest novel therapeutic targets for T2D, highlighting the shared metabolic strategies of stimulated beta cells and cancer cells. This comparative analysis not only illuminates the metabolic complexity of these conditions but also emphasizes the crucial role of metabolic pathways in cell function and survival, offering fresh perspectives for tackling T2D and cancer challenges.

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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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