运动与肿瘤蛋白质组:神经母细胞瘤模型的启示

IF 2.5 4区 生物学 Q3 CELL BIOLOGY
Physiological genomics Pub Date : 2024-12-01 Epub Date: 2024-09-23 DOI:10.1152/physiolgenomics.00064.2024
Abel Plaza-Florido, Beatriz G Gálvez, Juan A López, Alejandro Santos-Lozano, Sandra Zazo, Cecilia Rincón-Castanedo, Asunción Martín-Ruiz, Jorge Lumbreras, Laura C Terron-Camero, Alejandro López-Soto, Eduardo Andrés-León, África González-Murillo, Federico Rojo, Manuel Ramírez, Alejandro Lucia, Carmen Fiuza-Luces
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引用次数: 0

摘要

背景/目的:运动对儿科肿瘤生物学的影响基本上是未知的。我们在最具侵袭性的儿童恶性肿瘤之一--高危神经母细胞瘤(HR-NB)的小鼠模型中研究了定期运动对肿瘤蛋白质组谱的影响(用液相色谱串联质谱法评估):方法:对14只雄性小鼠(6-8周龄)的肿瘤样本进行分析,这些小鼠被随机分配到运动组(5周的有氧和阻力训练组合)或非运动对照组(每组分别为6只和8只)。利用检索相互作用基因/蛋白数据库的搜索工具生成蛋白质-蛋白质相互作用(PPI)网络并进行富集分析。系统生物学三角(SBT)算法用于功能类别层面的分析:结果:与对照组相比,运动小鼠肿瘤中分别有 101 个和 150 个蛋白质的丰度较高和较低[错误发现率(FDR)]:定期运动改变了数百种肿瘤内蛋白质和分子通路的丰度,尤其是那些参与能量代谢、细胞凋亡和肿瘤抑制的蛋白质。这些发现提供了运动对 HR-NB 潜在影响的分子机制的初步证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exercise and tumor proteome: insights from a neuroblastoma model.

The impact of exercise on pediatric tumor biology is essentially unknown. We explored the effects of regular exercise on tumor proteome profile (as assessed with liquid chromatography with tandem mass spectrometry) in a mouse model of one of the most aggressive childhood malignancies, high-risk neuroblastoma (HR-NB). Tumor samples of 14 male mice (aged 6-8 wk) that were randomly allocated into an exercise (5-wk combined aerobic and resistance training) or nonexercise control group (6 and 8 mice/group, respectively) were analyzed. The Search Tool for the Retrieval of Interacting Genes/Proteins database was used to generate a protein-protein interaction (PPI) network and enrichment analyses. The Systems Biology Triangle (SBT) algorithm was applied for analyses at the functional category level. Tumors of exercised mice showed a higher and lower abundance of 101 and 150 proteins, respectively, than controls [false discovery rate (FDR) < 0.05]. These proteins were enriched in metabolic pathways, amino acid metabolism, regulation of hormone levels, and peroxisome proliferator-activated receptor signaling (FDR < 0.05). The SBT algorithm indicated that 184 and 126 categories showed a lower and higher abundance, respectively, in the tumors of exercised mice (FDR < 0.01). Categories with lower abundance were involved in energy production, whereas those with higher abundance were related to transcription/translation, apoptosis, and tumor suppression. Regular exercise altered the abundance of hundreds of intratumoral proteins and molecular pathways, particularly those involved in energy metabolism, apoptosis, and tumor suppression. These findings provide preliminary evidence of the molecular mechanisms underlying the potential effects of exercise in HR-NB.NEW & NOTEWORTHY We used liquid chromatography with tandem mass spectrometry to explore the impact of a 5-wk exercise intervention on the tumor proteome profile in a mouse model of one of the most aggressive childhood malignancies, high-risk neuroblastoma. Exercise altered the abundance of hundreds of proteins and pathways, particularly those involved in energy metabolism and tumor suppression. These molecular changes could mediate, at least partly, the potential antitumorigenic effects of exercise.

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来源期刊
Physiological genomics
Physiological genomics 生物-生理学
CiteScore
6.10
自引率
0.00%
发文量
46
审稿时长
4-8 weeks
期刊介绍: The Physiological Genomics publishes original papers, reviews and rapid reports in a wide area of research focused on uncovering the links between genes and physiology at all levels of biological organization. Articles on topics ranging from single genes to the whole genome and their links to the physiology of humans, any model organism, organ, tissue or cell are welcome. Areas of interest include complex polygenic traits preferably of importance to human health and gene-function relationships of disease processes. Specifically, the Journal has dedicated Sections focused on genome-wide association studies (GWAS) to function, cardiovascular, renal, metabolic and neurological systems, exercise physiology, pharmacogenomics, clinical, translational and genomics for precision medicine, comparative and statistical genomics and databases. For further details on research themes covered within these Sections, please refer to the descriptions given under each Section.
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