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

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. Synthetic Lethality (SL) describes a relationship between a pair of genes where cells remain viable if at least one gene of the pair functions normally, but die if both genes are altered (e.g. mutated) at the same time. These alterations may occur naturally or can be drug-induced. Genes are often mutated in cancer cells, so therapeutically altering the SL partner of a gene already mutated in the cancer cells leads to cell death, as both partner genes are now altered, while normal cells lacking the initial mutation are spared. As gene function can be affected by diverse alterations besides DNA mutations, the mechanisms that control gene regulation without changing the DNA sequence, referred to as epigenetics, also need to be considered. In this Perspective, we highlight the importance of integrating both genetic and epigenetic alterations while studying SL relationships, and we explore how these SL relationships can be better identified by integrating experimental and computational approaches, to understand gene-gene interactions in order to broaden the treatment possibilities.

癌症治疗始终是一项极具挑战的课题：由于多数患者缺乏可药用靶点，直接靶向致癌驱动因子往往难以实现。这促使学界探索替代性治疗策略，例如利用基因间的合成致死（Synthetic Lethality，SL）关系。合成致死可实现致癌驱动因子的间接靶向，PARP抑制剂针对BRCA突变肿瘤的临床成功便是典型例证。高通量扰动筛选与多组学技术的进步加深了我们对合成致死关系的认知，而计算模型则优化了合成致死预测能力，使其更贴合生物学复杂性。然而，尽管已开发出诸多实验与计算方法用于识别合成致死相互作用，但将这些研究成果转化至临床应用仍存在诸多障碍。
本综述整合了癌症中合成致死关系的最新研究进展与表观遗传调控领域的新兴认知，着重阐明表观遗传药物（epidrugs）如何为靶向干预提供全新机遇，从而实现脱靶效应的最小化与治疗精准性的提升。为推动基于合成致死的治疗方案发展，相关研究不仅需聚焦于识别新型合成致死相互作用，还应整合现有研究成果，并结合实验与计算方法以刻画癌细胞的脆弱性特征。夯实这一研究基础，对于高效开发基于合成致死的癌症治疗方案至关重要。
合成致死（SL）指的是一对基因间的相互作用关系：若该基因对中至少一个基因功能正常，则细胞仍可存活；但若二者同时发生改变（例如突变），细胞则会死亡。这类基因改变既可能自然发生，也可由药物诱导产生。癌细胞中常存在基因突变，因此通过治疗性手段改变癌细胞中已发生突变的基因的合成致死搭档基因，可导致癌细胞死亡——此时二者搭档基因均已发生改变，而未携带初始突变的正常细胞则可免受影响。
除DNA突变外，基因功能还可受多种其他改变的影响，因此那些无需改变DNA序列即可调控基因表达的机制（即表观遗传学）也需纳入考量范围。在本展望综述中，我们着重强调了在研究合成致死关系时整合遗传与表观遗传改变的重要性，并探讨了如何通过结合实验与计算方法更好地识别合成致死关系，以解析基因间的相互作用，从而拓展癌症治疗的可选方案。