{"title":"建模转移-利用新工具来简化晚期癌症的发现。","authors":"Nicole M Eskow, Eva Hernando","doi":"10.1242/dmm.052449","DOIUrl":null,"url":null,"abstract":"<p><p>Metastasis remains a leading cause of morbidity and mortality in patients diagnosed with cancer. A variety of in vitro and in vivo approaches have been employed to study the individual steps of the metastatic cascade. However, these methodologies are sometimes limited in their ability to recapitulate the biological complexity and heterogeneity of human tumor biology. As a result, significant knowledge gaps still exist regarding the development, growth and evolution of treatment resistance in metastatic tumors. In this Perspective, we discuss the benefits and drawbacks of current, widely used techniques to model metastatic disease. We also highlight novel approaches utilized in recent studies to confront the limitations posed by classic modeling techniques. Ultimately, we provide suggestions for ensuring scientific rigor and reproducibility in metastasis studies, and we propose key areas of focus for developing next-generation models of metastasis.</p>","PeriodicalId":11144,"journal":{"name":"Disease Models & Mechanisms","volume":"18 8","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12452062/pdf/","citationCount":"0","resultStr":"{\"title\":\"Modeling metastasis - leveraging novel tools to streamline discovery in advanced cancer.\",\"authors\":\"Nicole M Eskow, Eva Hernando\",\"doi\":\"10.1242/dmm.052449\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Metastasis remains a leading cause of morbidity and mortality in patients diagnosed with cancer. A variety of in vitro and in vivo approaches have been employed to study the individual steps of the metastatic cascade. However, these methodologies are sometimes limited in their ability to recapitulate the biological complexity and heterogeneity of human tumor biology. As a result, significant knowledge gaps still exist regarding the development, growth and evolution of treatment resistance in metastatic tumors. In this Perspective, we discuss the benefits and drawbacks of current, widely used techniques to model metastatic disease. We also highlight novel approaches utilized in recent studies to confront the limitations posed by classic modeling techniques. Ultimately, we provide suggestions for ensuring scientific rigor and reproducibility in metastasis studies, and we propose key areas of focus for developing next-generation models of metastasis.</p>\",\"PeriodicalId\":11144,\"journal\":{\"name\":\"Disease Models & Mechanisms\",\"volume\":\"18 8\",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12452062/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Disease Models & Mechanisms\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1242/dmm.052449\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/9/3 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Disease Models & Mechanisms","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1242/dmm.052449","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/9/3 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
Modeling metastasis - leveraging novel tools to streamline discovery in advanced cancer.
Metastasis remains a leading cause of morbidity and mortality in patients diagnosed with cancer. A variety of in vitro and in vivo approaches have been employed to study the individual steps of the metastatic cascade. However, these methodologies are sometimes limited in their ability to recapitulate the biological complexity and heterogeneity of human tumor biology. As a result, significant knowledge gaps still exist regarding the development, growth and evolution of treatment resistance in metastatic tumors. In this Perspective, we discuss the benefits and drawbacks of current, widely used techniques to model metastatic disease. We also highlight novel approaches utilized in recent studies to confront the limitations posed by classic modeling techniques. Ultimately, we provide suggestions for ensuring scientific rigor and reproducibility in metastasis studies, and we propose key areas of focus for developing next-generation models of metastasis.
期刊介绍:
Disease Models & Mechanisms (DMM) is an online Open Access journal focusing on the use of model systems to better understand, diagnose and treat human disease.