Grace Y. Q. Han, Monica Alexander, Julia Gattozzi, Marilyn Day, Elayna Kirsch, Narges Tafreshi, Raafat Chalar, Soraya Rahni, Gabrielle Gossner, William Burke, Mehdi Damaghi
{"title":"利用生态和进化动力学设计和改进卵巢癌治疗方法","authors":"Grace Y. Q. Han, Monica Alexander, Julia Gattozzi, Marilyn Day, Elayna Kirsch, Narges Tafreshi, Raafat Chalar, Soraya Rahni, Gabrielle Gossner, William Burke, Mehdi Damaghi","doi":"10.1002/ctm2.70012","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Key points/Highlights</h3>\n \n <div>\n <ul>\n \n <li>\n <p>Tumours are ecosystems in which cancer and non-cancer cells interact and evolve in complex and dynamic ways.</p>\n </li>\n \n <li>\n <p>Conventional therapies for ovarian cancer inevitably lead to the development of resistance because they fail to consider tumours’ heterogeneity and cellular plasticity.</p>\n </li>\n \n <li>\n <p>Eco-evolutionarily designed therapies should consider cancer cell plasticity and patient-specific characteristics to improve clinical outcome and prevent relapse.</p>\n </li>\n </ul>\n </div>\n </section>\n </div>","PeriodicalId":10189,"journal":{"name":"Clinical and Translational Medicine","volume":"14 9","pages":""},"PeriodicalIF":7.9000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ctm2.70012","citationCount":"0","resultStr":"{\"title\":\"Ecological and evolutionary dynamics to design and improve ovarian cancer treatment\",\"authors\":\"Grace Y. Q. Han, Monica Alexander, Julia Gattozzi, Marilyn Day, Elayna Kirsch, Narges Tafreshi, Raafat Chalar, Soraya Rahni, Gabrielle Gossner, William Burke, Mehdi Damaghi\",\"doi\":\"10.1002/ctm2.70012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Key points/Highlights</h3>\\n \\n <div>\\n <ul>\\n \\n <li>\\n <p>Tumours are ecosystems in which cancer and non-cancer cells interact and evolve in complex and dynamic ways.</p>\\n </li>\\n \\n <li>\\n <p>Conventional therapies for ovarian cancer inevitably lead to the development of resistance because they fail to consider tumours’ heterogeneity and cellular plasticity.</p>\\n </li>\\n \\n <li>\\n <p>Eco-evolutionarily designed therapies should consider cancer cell plasticity and patient-specific characteristics to improve clinical outcome and prevent relapse.</p>\\n </li>\\n </ul>\\n </div>\\n </section>\\n </div>\",\"PeriodicalId\":10189,\"journal\":{\"name\":\"Clinical and Translational Medicine\",\"volume\":\"14 9\",\"pages\":\"\"},\"PeriodicalIF\":7.9000,\"publicationDate\":\"2024-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ctm2.70012\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical and Translational Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/ctm2.70012\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical and Translational Medicine","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ctm2.70012","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Ecological and evolutionary dynamics to design and improve ovarian cancer treatment
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.
期刊介绍：
Clinical and Translational Medicine (CTM) is an international, peer-reviewed, open-access journal dedicated to accelerating the translation of preclinical research into clinical applications and fostering communication between basic and clinical scientists. It highlights the clinical potential and application of various fields including biotechnologies, biomaterials, bioengineering, biomarkers, molecular medicine, omics science, bioinformatics, immunology, molecular imaging, drug discovery, regulation, and health policy. With a focus on the bench-to-bedside approach, CTM prioritizes studies and clinical observations that generate hypotheses relevant to patients and diseases, guiding investigations in cellular and molecular medicine. The journal encourages submissions from clinicians, researchers, policymakers, and industry professionals.
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