表观遗传时钟和神经胶质瘤:揭示衰老和肿瘤发展之间的分子相互作用。
Epigenetic clocks and gliomas: unveiling the molecular interactions between aging and tumor development.
发表日期:2024
作者:
Shiliang Chen, Yi Jiang, Cong Wang, Shiyuan Tong, Yibo He, Wenqiang Lu, Zhezhong Zhang
来源:
Frontiers in Molecular Biosciences
摘要:
神经胶质瘤是最常见和最具侵袭性的原发性脑肿瘤,代表了起源于神经胶质细胞的多种恶性肿瘤。这些肿瘤是脑肿瘤相关发病率和死亡率的重要组成部分,与亚洲和非洲相比,北美和欧洲的发病率更高。遗传倾向和环境因素,特别是电离辐射,严重影响神经胶质瘤的风险。表观遗传学,特别是 DNA 甲基化,在神经胶质瘤研究中发挥着关键作用,IDH 突变神经胶质瘤表现出异常的甲基化模式,有助于肿瘤发生。表观遗传时钟是基于 DNA 甲基化模式预测生物年龄的生物标记,揭示了对衰老和肿瘤发展的重要见解。最近的研究表明,神经胶质瘤的表观遗传老化加速,与癌症风险增加和预后较差相关。本文探讨了表观遗传时钟的机制、其生物学意义及其在神经胶质瘤研究中的应用。此外,还讨论了表观遗传时钟在诊断、预测和治疗神经胶质瘤中的临床意义。将表观遗传时钟数据整合到个性化医疗方法中有望增强神经胶质瘤治疗的治疗策略和患者结果。版权所有 © 2024 Chen、Jiang、Wang、Tong、He、Lu 和 Zhang。
Gliomas, the most prevalent and aggressive primary brain tumors, represent a diverse group of malignancies originating from glial cells. These tumors account for significant brain tumor-related morbidity and mortality, with higher incidence rates in North America and Europe compared to Asia and Africa. Genetic predispositions and environmental factors, particularly ionizing radiation, critically impact glioma risk. Epigenetics, particularly DNA methylation, plays a pivotal role in glioma research, with IDH-mutant gliomas showing aberrant methylation patterns contributing to tumorigenesis. Epigenetic clocks, biomarkers based on DNA methylation patterns predicting biological age, have revealed significant insights into aging and tumor development. Recent studies demonstrate accelerated epigenetic aging in gliomas, correlating with increased cancer risk and poorer outcomes. This review explores the mechanisms of epigenetic clocks, their biological significance, and their application in glioma research. Furthermore, the clinical implications of epigenetic clocks in diagnosing, prognosticating, and treating gliomas are discussed. The integration of epigenetic clock data into personalized medicine approaches holds promise for enhancing therapeutic strategies and patient outcomes in glioma treatment.Copyright © 2024 Chen, Jiang, Wang, Tong, He, Lu and Zhang.