卵巢癌生态系统极其复杂，由高度异质性的癌细胞组成。聚ADP核糖聚合酶（PARP）抑制剂、靶向疗法和免疫疗法等药物的开发为序贯或联合治疗提供了更多选择。然而，转移性卵巢癌患者的死亡率仍然很高，因为癌细胞不断对单一疗法和联合疗法产生耐药性，这迫切需要针对癌细胞进化性的治疗设计。导致耐药性的进化动态源于复杂的肿瘤微环境、异质群体和单个癌细胞的可塑性。我们认为，卵巢癌的成功治疗需要考虑该疾病的生态和进化动力学。在这里，我们回顾当前卵巢癌治疗的选择和挑战，并讨论肿瘤进化的原理。最后，我们提出了针对卵巢癌的进化设计策略，目标是将这些原则与纵向定量数据相结合，以改进治疗设计和耐药性管理。要点/要点：肿瘤是一个生态系统，癌细胞和非癌细胞在其中以复杂和动态的方式相互作用和进化。卵巢癌的传统疗法不可避免地导致耐药性的产生，因为它们没有考虑肿瘤的异质性和细胞可塑性。生态进化设计的疗法应考虑癌细胞的可塑性和患者的具体特征，以改善临床结果并防止复发。© 2024 作者。约翰·威利出版的《临床与转化医学》

Ovarian cancer ecosystems are exceedingly complex, consisting of a high heterogeneity of cancer cells. Development of drugs such as poly ADP-ribose polymerase (PARP) inhibitors, targeted therapies and immunotherapies offer more options for sequential or combined treatments. Nevertheless, mortality in metastatic ovarian cancer patients remains high because cancer cells consistently develop resistance to single and combination therapies, urging a need for treatment designs that target the evolvability of cancer cells. The evolutionary dynamics that lead to resistance emerge from the complex tumour microenvironment, the heterogeneous populations, and the individual cancer cell's plasticity. We propose that successful management of ovarian cancer requires consideration of the ecological and evolutionary dynamics of the disease. Here, we review current options and challenges in ovarian cancer treatment and discuss principles of tumour evolution. We conclude by proposing evolutionarily designed strategies for ovarian cancer, with the goal of integrating such principles with longitudinal, quantitative data to improve the treatment design and management of drug resistance. KEY POINTS/HIGHLIGHTS: Tumours are ecosystems in which cancer and non-cancer cells interact and evolve in complex and dynamic ways. Conventional therapies for ovarian cancer inevitably lead to the development of resistance because they fail to consider tumours' heterogeneity and cellular plasticity. Eco-evolutionarily designed therapies should consider cancer cell plasticity and patient-specific characteristics to improve clinical outcome and prevent relapse.© 2024 The Author(s). Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.