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解读铁死亡:从分子途径到机器学习引导的治疗创新

Deciphering Ferroptosis: From Molecular Pathways to Machine Learning-Guided Therapeutic Innovation.

作者信息

Mete Megha, Ojha Amiya, Dhar Priyanka, Das Deeplina

机构信息

Department of Bioengineering, National Institute of Technology Agartala, Agartala, Tripura, 799046, India.

CSIR-Indian Institute of Chemical Biology, Kolkata, 700032, India.

出版信息

Mol Biotechnol. 2025 Apr;67(4):1290-1309. doi: 10.1007/s12033-024-01139-0. Epub 2024 Apr 13.

DOI:10.1007/s12033-024-01139-0
PMID:38613722
Abstract

Ferroptosis is a unique form of cell death reliant on iron and lipid peroxidation. It disrupts redox balance, causing cell death by damaging the plasma membrane, with inducers acting through enzymatic pathways or transport systems. In cancer treatment, suppressing ferroptosis or circumventing it holds significant promise. Beyond cancer, ferroptosis affects aging, organs, metabolism, and nervous system. Understanding ferroptosis mechanisms holds promise for uncovering novel therapeutic strategies across a spectrum of diseases. However, detection and regulation of this regulated cell death are still mired with challenges. The dearth of cell, tissue, or organ-specific biomarkers muted the pharmacological use of ferroptosis. This review covers recent studies on ferroptosis, detailing its properties, key genes, metabolic pathways, and regulatory networks, emphasizing the interaction between cellular signaling and ferroptotic cell death. It also summarizes recent findings on ferroptosis inducers, inhibitors, and regulators, highlighting their potential therapeutic applications across diseases. The review addresses challenges in utilizing ferroptosis therapeutically and explores the use of machine learning to uncover complex patterns in ferroptosis-related data, aiding in the discovery of biomarkers, predictive models, and therapeutic targets. Finally, it discusses emerging research areas and the importance of continued investigation to harness the full therapeutic potential of targeting ferroptosis.

摘要

铁死亡是一种独特的细胞死亡形式,依赖于铁和脂质过氧化。它破坏氧化还原平衡,通过损伤质膜导致细胞死亡,诱导剂通过酶促途径或转运系统发挥作用。在癌症治疗中,抑制或规避铁死亡具有重大前景。除癌症外,铁死亡还影响衰老、器官、代谢和神经系统。了解铁死亡机制有望揭示一系列疾病的新型治疗策略。然而,这种程序性细胞死亡的检测和调控仍面临诸多挑战。细胞、组织或器官特异性生物标志物的缺乏限制了铁死亡在药理学上的应用。本综述涵盖了铁死亡的最新研究,详细阐述了其特性、关键基因、代谢途径和调控网络,强调了细胞信号传导与铁死亡性细胞死亡之间的相互作用。它还总结了铁死亡诱导剂、抑制剂和调节剂的最新研究成果,突出了它们在各种疾病中的潜在治疗应用。本综述探讨了铁死亡治疗应用中的挑战,并探索利用机器学习揭示铁死亡相关数据中的复杂模式,以辅助生物标志物、预测模型和治疗靶点的发现。最后,它讨论了新兴研究领域以及持续研究以充分发挥靶向铁死亡治疗潜力的重要性。

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Machine learning-based integration identifies the ferroptosis hub genes in nonalcoholic steatohepatitis.基于机器学习的整合鉴定出非酒精性脂肪性肝炎中的铁死亡枢纽基因。
Lipids Health Dis. 2024 Jan 23;23(1):23. doi: 10.1186/s12944-023-01988-9.
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A new ferroptosis-related signature model including messenger RNAs and long non-coding RNAs predicts the prognosis of gastric cancer patients.一种包含信使核糖核酸和长链非编码核糖核酸的新型铁死亡相关特征模型可预测胃癌患者的预后。
J Transl Int Med. 2023 Jul 5;11(2):145-155. doi: 10.2478/jtim-2023-0089. eCollection 2023 Jun.
3
Copper homeostasis-associated gene PRNP regulates ferroptosis and immune infiltration in breast cancer.
无义介导的mRNA衰变在人类健康与疾病中的研究:当前认识、调控机制及未来展望
Mol Biotechnol. 2024 Sep 12. doi: 10.1007/s12033-024-01267-7.
铜稳态相关基因 PRNP 调控乳腺癌中的铁死亡和免疫浸润。
PLoS One. 2023 Aug 3;18(8):e0288091. doi: 10.1371/journal.pone.0288091. eCollection 2023.
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CellDeathPred: a deep learning framework for ferroptosis and apoptosis prediction based on cell painting.细胞死亡预测:一种基于细胞成像的用于铁死亡和凋亡预测的深度学习框架。
Cell Death Discov. 2023 Jul 31;9(1):277. doi: 10.1038/s41420-023-01559-y.
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VDAC2 malonylation participates in sepsis-induced myocardial dysfunction via mitochondrial-related ferroptosis.VDAC2 琥珀酰化参与脓毒症诱导的心肌功能障碍通过线粒体相关的铁死亡。
Int J Biol Sci. 2023 Jun 14;19(10):3143-3158. doi: 10.7150/ijbs.84613. eCollection 2023.
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NADPH Oxidase Subunit CYBB Confers Chemotherapy and Ferroptosis Resistance in Mesenchymal Glioblastoma via Nrf2/SOD2 Modulation.NADPH 氧化酶亚基 CYBB 通过调节 Nrf2/SOD2 赋予间充质型胶质母细胞瘤对化疗和铁死亡的耐药性。
Int J Mol Sci. 2023 Apr 22;24(9):7706. doi: 10.3390/ijms24097706.
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Exploration and identification of six novel ferroptosis-related hub genes as potential gene signatures for peripheral nerve injury.探索并鉴定六个新的铁死亡相关枢纽基因作为周围神经损伤的潜在基因特征。
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