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表观遗传合成致死作为一种癌症治疗策略:实验方法与计算方法的协同作用

Epigenetic synthetic lethality as a cancer therapeutic strategy: synergy of experimental and computational approaches.

作者信息

Farina-Morillas Maria, Ollé-Monràs Laia, Maas Silvana Ce, de Rojas-P Isabel, Segura Miguel F, Seoane Jose A

机构信息

Cancer Computational Biology Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain.

Childhood Cancer and Blood Disorders Group, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain.

出版信息

Epigenomics. 2025 Aug 25:1-13. doi: 10.1080/17501911.2025.2548756.

Abstract

Cancer treatment is an ongoing challenge, as directly targeting oncogenic drivers is often unfeasible in many patients due to the lack of druggable targets. This has led to the exploration of alternative strategies, such as exploiting synthetic lethality (SL) relationships between genes. SL facilitates the indirect targeting of oncogenic drivers, as exemplified by the clinical success of PARP inhibitors against BRCA-mutated tumors. Advances in high-throughput perturbation screens and multi-omics technologies have deepened our understanding of SL relationships, while computational models enhance SL predictions to better reflect biological complexity. However, while numerous experimental and computational methods have been developed to identify SL interactions, difficulties remain in translating these findings into clinical applications.This review combines recent progress on SL relationships in cancer with emerging insights into epigenetic regulation, highlighting how epigenetic drugs (epidrugs) can provide new opportunities for targeted interventions, offering a way to minimize off-target effects and enhance therapeutic precision. To advance SL-based therapies, efforts must focus not only on identifying new SL interactions but also on consolidating existing knowledge and integrating experimental and computational approaches to characterize the vulnerabilities of cancer cells. Strengthening this foundation will be critical for the effective development of SL-based cancer treatments.

摘要

癌症治疗是一项持续的挑战,因为在许多患者中,由于缺乏可成药靶点,直接靶向致癌驱动因子往往不可行。这促使人们探索替代策略,例如利用基因之间的合成致死(SL)关系。SL有助于间接靶向致癌驱动因子,PARP抑制剂针对BRCA突变肿瘤的临床成功就是例证。高通量扰动筛选和多组学技术的进展加深了我们对SL关系的理解,而计算模型则增强了SL预测,以更好地反映生物学复杂性。然而,尽管已经开发了许多实验和计算方法来识别SL相互作用,但将这些发现转化为临床应用仍然存在困难。本综述结合了癌症中SL关系的最新进展以及对表观遗传调控的新见解,强调表观遗传药物(表型药物)如何能够为靶向干预提供新机会,提供一种将脱靶效应降至最低并提高治疗精准度的方法。为了推进基于SL的疗法,不仅必须专注于识别新的SL相互作用,还必须巩固现有知识,并整合实验和计算方法来表征癌细胞的脆弱性。加强这一基础对于基于SL的癌症治疗的有效开发至关重要。

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