代谢组学方法鉴定阿霉素诱导的心脏毒性生物标志物的叙述性回顾。

IF 3.5 3区 医学 Q2 ENDOCRINOLOGY & METABOLISM
Amarnath Singh, Maham Bakhtyar, Se-Ran Jun, Marjan Boerma, Renny S Lan, L Joseph Su, Sam Makhoul, Ping-Ching Hsu
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引用次数: 0

摘要

背景:众所周知,常用于癌症治疗的蒽环类药物会引起心脏毒性,但目前还没有经过验证的生物标志物可以预测阿霉素诱导的心脏毒性(DIC)的早期发展。因此,迫切需要识别DIC的早期生物标志物。代谢组学方法已被用来阐明这种关系,并鉴定出相关的代谢物标记物。然而,临床前模型系统的差异使得从发现中得出明确的结论并将发现转化为临床应用具有挑战性。综述目的:对DIC代谢组学研究进行了系统的文献检索,目的是识别和比较体外模型、动物模型和临床患者研究报告的研究结果。所有研究中发现的代谢物被汇总起来,以发现数据中显著丰富的具有生物学意义的模式。最后,被DIC干扰的代谢产物被映射到代谢途径,以探索潜在的病理意义。结果:我们回顾了2000年至2024年间发表的28项利用代谢组学方法研究DIC的研究。纳入的研究使用了多种分析技术,包括LC-MS, GC-MS和NMR。分析显示,在所有研究模型中,肌苷、苯丙氨酸、精氨酸和色氨酸等代谢物通常受到干扰,其中肉碱代谢、嘌呤和嘧啶代谢是受影响最大的途径。使用MetaboAnalyst的代谢物集富集分析(MSEA)发现精氨酸生物合成、柠檬酸循环、丙氨酸、天冬氨酸和谷氨酸代谢途径显著富集。结论:这些发现强调了代谢组学在识别DIC早期生物标志物方面的潜力,为未来的研究提供了基础,旨在预防心脏毒性和改善接受含dox治疗的癌症患者的治疗策略。综述的关键科学概念:总的来说,代谢组学研究提示DIC的代谢改变,尽管研究之间很少重叠,特别是动物和人类研究。阻断这些通路的尝试表明干预DIC是可能的。未来的研究应侧重于开发包含癌症代谢的精确心脏毒性模型,因为这些模型对于弥合实验室(体外和动物模型)和临床研究之间的差距至关重要,以确定DIC早期的亚临床生物标志物,从而有效地确定干预的新靶点,以降低致死性心血管疾病的风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A narrative review of metabolomics approaches in identifying biomarkers of doxorubicin-induced cardiotoxicity.

Background: While anthracyclines, commonly used in cancer treatment, are well known to cause cardiotoxicity, no validated biomarkers currently exist that can predict the early development of doxorubicin-induced cardiotoxicity (DIC). Therefore, identifying early biomarkers of DIC is urgently needed. Metabolomics approaches have been used to elucidate this relationship and identified related metabolite markers. However, differences in pre-clinical model systems make it challenging to draw definitive conclusions from the discoveries and translate findings into clinical applications.

Aim of review: A systematic literature search on metabolomics studies of DIC was conducted with the goal to identify and compare study results reported using in vitro models, animal models, and studies from clinical patients. Metabolites identified across all studies were pooled to uncover biologically meaningful patterns that are significantly enriched in the data. Finally, pooled metabolites perturbed by DIC were mapped to metabolic pathways to explore potential pathological implications.

Results: We reviewed 28 studies published between 2000 and 2024 that utilized metabolomics approaches to investigate DIC. The included studies used a variety of analytical techniques, including LC-MS, GC-MS, and NMR. The analysis revealed that metabolites such as inosine, phenylalanine, arginine, and tryptophan were commonly perturbed across all study models, with carnitine metabolism and purine and pyrimidine metabolism being the most affected pathways. Metabolite Set Enrichment Analysis (MSEA) using MetaboAnalyst identified the arginine biosynthesis, citrate cycle, and alanine, aspartate, and glutamate metabolism pathways as significantly enriched.

Conclusion: These findings underscore the potential of metabolomics in identifying early biomarkers for DIC, providing a foundation for future studies aimed at preventing cardiotoxicity and improving treatment strategies for cancer patients receiving DOX-containing therapies.

Key scientific concepts of review: Altogether, metabolomics studies suggest metabolic alterations in DIC, albeit little overlap between studies especially with animal and human studies. Attempts at intercepting these pathways have shown that intervention in DIC may be possible. Future research should focus on developing precise cardiotoxicity models that incorporate cancer metabolism, as these will be crucial in bridging the gap between laboratories (in vitro and animal models) and clinical studies to identify subclinical biomarkers in the early stage of DIC that can effectively identify new targets for interventions to reduce lethal cardiovascular disease risk.

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来源期刊
Metabolomics
Metabolomics 医学-内分泌学与代谢
CiteScore
6.60
自引率
2.80%
发文量
84
审稿时长
2 months
期刊介绍: Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to: metabolomic applications within man, including pre-clinical and clinical pharmacometabolomics for precision medicine metabolic profiling and fingerprinting metabolite target analysis metabolomic applications within animals, plants and microbes transcriptomics and proteomics in systems biology Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.
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