Lucy Wang , Oluwatomilayo Ejedenawe , Stephanie Lheureux , Danielle Rodin , Christine Allen
{"title":"纳米医学研究中的癌症模型:对转化纳米医学体外模型的再思考","authors":"Lucy Wang , Oluwatomilayo Ejedenawe , Stephanie Lheureux , Danielle Rodin , Christine Allen","doi":"10.1016/j.nantod.2025.102911","DOIUrl":null,"url":null,"abstract":"<div><div>The U.S. FDA’s recent move to ease mandatory animal testing requirements has renewed scrutiny of in vitro models used in preclinical drug development. In nanomedicine, platforms such as spheroids, organoids, and organ-on-chip have advanced mechanistic modeling, yet the predictive validity of these systems remains limited by the biological relevance of the cell lines they incorporate. This Perspective critically evaluates the translational implications of using a narrow set of immortalized cancer cell lines in nanomedicine research – many of which lack genetic, phenotypic, or demographic alignment with cancer disease biology. Through a literature review of the 50 most cited studies in gynecologic cancer nanomedicine, we reveal an overreliance on just three cell lines in over 60–80 % of surveyed publications. We further show that most available gynecologic cancer cell lines are of European ancestry, with limited representation of global populations, despite growing evidence of population-specific differences in nanomedicine clinical efficacy and toxicity. These findings underscore a critical bottleneck in the development pipeline: the overuse of preclinical models that lack the biological variability necessary for robust clinical translation. As regulatory frameworks increasingly prioritize in vitro data in preclinical evaluation, the need to widen our cancer cell model repertoire becomes increasingly urgent. We propose actionable strategies to improve model representativeness and foster early stakeholder engagement in preclinical research. By embedding these practices into nanomedicine development, the field can strengthen translational outcomes, potentially reducing late-stage failures while better meeting the needs of the global oncology market.</div></div>","PeriodicalId":395,"journal":{"name":"Nano Today","volume":"66 ","pages":"Article 102911"},"PeriodicalIF":10.9000,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cancer models in nanomedicine research: Rethinking in vitro models for translational nanomedicine\",\"authors\":\"Lucy Wang , Oluwatomilayo Ejedenawe , Stephanie Lheureux , Danielle Rodin , Christine Allen\",\"doi\":\"10.1016/j.nantod.2025.102911\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The U.S. FDA’s recent move to ease mandatory animal testing requirements has renewed scrutiny of in vitro models used in preclinical drug development. In nanomedicine, platforms such as spheroids, organoids, and organ-on-chip have advanced mechanistic modeling, yet the predictive validity of these systems remains limited by the biological relevance of the cell lines they incorporate. This Perspective critically evaluates the translational implications of using a narrow set of immortalized cancer cell lines in nanomedicine research – many of which lack genetic, phenotypic, or demographic alignment with cancer disease biology. Through a literature review of the 50 most cited studies in gynecologic cancer nanomedicine, we reveal an overreliance on just three cell lines in over 60–80 % of surveyed publications. We further show that most available gynecologic cancer cell lines are of European ancestry, with limited representation of global populations, despite growing evidence of population-specific differences in nanomedicine clinical efficacy and toxicity. These findings underscore a critical bottleneck in the development pipeline: the overuse of preclinical models that lack the biological variability necessary for robust clinical translation. As regulatory frameworks increasingly prioritize in vitro data in preclinical evaluation, the need to widen our cancer cell model repertoire becomes increasingly urgent. We propose actionable strategies to improve model representativeness and foster early stakeholder engagement in preclinical research. By embedding these practices into nanomedicine development, the field can strengthen translational outcomes, potentially reducing late-stage failures while better meeting the needs of the global oncology market.</div></div>\",\"PeriodicalId\":395,\"journal\":{\"name\":\"Nano Today\",\"volume\":\"66 \",\"pages\":\"Article 102911\"},\"PeriodicalIF\":10.9000,\"publicationDate\":\"2025-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nano Today\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S174801322500283X\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nano Today","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S174801322500283X","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Cancer models in nanomedicine research: Rethinking in vitro models for translational nanomedicine
The U.S. FDA’s recent move to ease mandatory animal testing requirements has renewed scrutiny of in vitro models used in preclinical drug development. In nanomedicine, platforms such as spheroids, organoids, and organ-on-chip have advanced mechanistic modeling, yet the predictive validity of these systems remains limited by the biological relevance of the cell lines they incorporate. This Perspective critically evaluates the translational implications of using a narrow set of immortalized cancer cell lines in nanomedicine research – many of which lack genetic, phenotypic, or demographic alignment with cancer disease biology. Through a literature review of the 50 most cited studies in gynecologic cancer nanomedicine, we reveal an overreliance on just three cell lines in over 60–80 % of surveyed publications. We further show that most available gynecologic cancer cell lines are of European ancestry, with limited representation of global populations, despite growing evidence of population-specific differences in nanomedicine clinical efficacy and toxicity. These findings underscore a critical bottleneck in the development pipeline: the overuse of preclinical models that lack the biological variability necessary for robust clinical translation. As regulatory frameworks increasingly prioritize in vitro data in preclinical evaluation, the need to widen our cancer cell model repertoire becomes increasingly urgent. We propose actionable strategies to improve model representativeness and foster early stakeholder engagement in preclinical research. By embedding these practices into nanomedicine development, the field can strengthen translational outcomes, potentially reducing late-stage failures while better meeting the needs of the global oncology market.
期刊介绍:
Nano Today is a journal dedicated to publishing influential and innovative work in the field of nanoscience and technology. It covers a wide range of subject areas including biomaterials, materials chemistry, materials science, chemistry, bioengineering, biochemistry, genetics and molecular biology, engineering, and nanotechnology. The journal considers articles that inform readers about the latest research, breakthroughs, and topical issues in these fields. It provides comprehensive coverage through a mixture of peer-reviewed articles, research news, and information on key developments. Nano Today is abstracted and indexed in Science Citation Index, Ei Compendex, Embase, Scopus, and INSPEC.