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

IF 2.6 4区 医学 Q2 GENETICS & HEREDITY
Epigenomics Pub Date : 2025-10-01 Epub Date: 2025-08-25 DOI:10.1080/17501911.2025.2548756
Maria Farina-Morillas, Laia Ollé-Monràs, Silvana Ce Maas, Isabel de Rojas-P, Miguel F Segura, Jose A Seoane
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引用次数: 0

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.

表观遗传合成致死率作为一种癌症治疗策略:实验和计算方法的协同作用。
癌症治疗是一个持续的挑战,因为由于缺乏可药物靶点,直接针对致癌驱动因素在许多患者中往往是不可行的。这导致了对替代策略的探索,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抑制剂治疗brca突变肿瘤的临床成功就是例证。高通量微扰筛选和多组学技术的进步加深了我们对SL关系的理解,而计算模型增强了SL预测,以更好地反映生物复杂性。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,但在将这些发现转化为临床应用方面仍然存在困难。这篇综述结合了癌症中SL关系的最新进展和对表观遗传调控的新见解,强调了表观遗传药物(epiddrugs)如何为靶向干预提供新的机会,提供了一种最小化脱靶效应和提高治疗精度的方法。为了推进基于SL的治疗,努力不仅要集中在识别新的SL相互作用上,还要集中在巩固现有知识和整合实验和计算方法上,以表征癌细胞的脆弱性。加强这一基础对于有效开发基于sl的癌症治疗至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Epigenomics
Epigenomics GENETICS & HEREDITY-
CiteScore
5.80
自引率
2.60%
发文量
95
审稿时长
>12 weeks
期刊介绍: Epigenomics provides the forum to address the rapidly progressing research developments in this ever-expanding field; to report on the major challenges ahead and critical advances that are propelling the science forward. The journal delivers this information in concise, at-a-glance article formats – invaluable to a time constrained community. Substantial developments in our current knowledge and understanding of genomics and epigenetics are constantly being made, yet this field is still in its infancy. Epigenomics provides a critical overview of the latest and most significant advances as they unfold and explores their potential application in the clinical setting.
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