Lijing Yang, Xiaojuan Ma, Decao Yang, Jiagui Song, Jianling Yang, Yan Sun, Yan Wang, Lixiang Xue
{"title":"用于药物筛选的三维脑肿瘤球体代谢谱研究进展。","authors":"Lijing Yang, Xiaojuan Ma, Decao Yang, Jiagui Song, Jianling Yang, Yan Sun, Yan Wang, Lixiang Xue","doi":"10.3791/68833","DOIUrl":null,"url":null,"abstract":"<p><p>Brain tumors, especially gliomas, are challenging to treat because of their aggressive nature, complex tumor microenvironment, and resistance to conventional therapies. Traditional two-dimensional (2D) cell cultures often fail to replicate the true tumor environment, leading to inaccurate predictions of drug efficacy. Extracellular flux analysis technology, typically used for real-time metabolic analysis in 2D cultures, measures key metabolic parameters, such as the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR), providing insights into cellular metabolism. The use of 3D models represents a significant advancement, as they more accurately mimic the in vivo tumor environment. The extracellular flux analyzer was adapted to three-dimensional (3D) glioma cell models, enabling the analysis of critical metabolic pathways, including glycolysis and oxidative phosphorylation, in a more physiologically relevant context. U87 cells were seeded at appropriate densities in a 96-well low-attachment plate and cultured for 5 days. On day 5, 3D spheroid formation was observed via high-content imaging. The successfully formed spheroids were then transferred to a metabolic assay plate coated with poly-L-lysine for metabolic analysis. To improve the accuracy of these measurements, high-content imaging systems assess 3D cell size, allowing for precise normalization of extracellular flux data and minimizing metabolic variations due to differences in cell size. This integrated approach provides a more reliable analysis of glioma cell metabolic responses to drug treatments, revealing potential mechanisms of drug resistance. Ultimately, this methodology offers valuable insights into the metabolic dynamics of gliomas and supports the development of novel, clinically relevant therapeutic strategies.</p>","PeriodicalId":48787,"journal":{"name":"Jove-Journal of Visualized Experiments","volume":" 223","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advancements in the Metabolic Profiling of Three-Dimensional Brain Tumor Spheroids for Drug Screening.\",\"authors\":\"Lijing Yang, Xiaojuan Ma, Decao Yang, Jiagui Song, Jianling Yang, Yan Sun, Yan Wang, Lixiang Xue\",\"doi\":\"10.3791/68833\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Brain tumors, especially gliomas, are challenging to treat because of their aggressive nature, complex tumor microenvironment, and resistance to conventional therapies. Traditional two-dimensional (2D) cell cultures often fail to replicate the true tumor environment, leading to inaccurate predictions of drug efficacy. Extracellular flux analysis technology, typically used for real-time metabolic analysis in 2D cultures, measures key metabolic parameters, such as the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR), providing insights into cellular metabolism. The use of 3D models represents a significant advancement, as they more accurately mimic the in vivo tumor environment. The extracellular flux analyzer was adapted to three-dimensional (3D) glioma cell models, enabling the analysis of critical metabolic pathways, including glycolysis and oxidative phosphorylation, in a more physiologically relevant context. U87 cells were seeded at appropriate densities in a 96-well low-attachment plate and cultured for 5 days. On day 5, 3D spheroid formation was observed via high-content imaging. The successfully formed spheroids were then transferred to a metabolic assay plate coated with poly-L-lysine for metabolic analysis. To improve the accuracy of these measurements, high-content imaging systems assess 3D cell size, allowing for precise normalization of extracellular flux data and minimizing metabolic variations due to differences in cell size. This integrated approach provides a more reliable analysis of glioma cell metabolic responses to drug treatments, revealing potential mechanisms of drug resistance. Ultimately, this methodology offers valuable insights into the metabolic dynamics of gliomas and supports the development of novel, clinically relevant therapeutic strategies.</p>\",\"PeriodicalId\":48787,\"journal\":{\"name\":\"Jove-Journal of Visualized Experiments\",\"volume\":\" 223\",\"pages\":\"\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2025-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jove-Journal of Visualized Experiments\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.3791/68833\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jove-Journal of Visualized Experiments","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.3791/68833","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Advancements in the Metabolic Profiling of Three-Dimensional Brain Tumor Spheroids for Drug Screening.
Brain tumors, especially gliomas, are challenging to treat because of their aggressive nature, complex tumor microenvironment, and resistance to conventional therapies. Traditional two-dimensional (2D) cell cultures often fail to replicate the true tumor environment, leading to inaccurate predictions of drug efficacy. Extracellular flux analysis technology, typically used for real-time metabolic analysis in 2D cultures, measures key metabolic parameters, such as the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR), providing insights into cellular metabolism. The use of 3D models represents a significant advancement, as they more accurately mimic the in vivo tumor environment. The extracellular flux analyzer was adapted to three-dimensional (3D) glioma cell models, enabling the analysis of critical metabolic pathways, including glycolysis and oxidative phosphorylation, in a more physiologically relevant context. U87 cells were seeded at appropriate densities in a 96-well low-attachment plate and cultured for 5 days. On day 5, 3D spheroid formation was observed via high-content imaging. The successfully formed spheroids were then transferred to a metabolic assay plate coated with poly-L-lysine for metabolic analysis. To improve the accuracy of these measurements, high-content imaging systems assess 3D cell size, allowing for precise normalization of extracellular flux data and minimizing metabolic variations due to differences in cell size. This integrated approach provides a more reliable analysis of glioma cell metabolic responses to drug treatments, revealing potential mechanisms of drug resistance. Ultimately, this methodology offers valuable insights into the metabolic dynamics of gliomas and supports the development of novel, clinically relevant therapeutic strategies.
期刊介绍:
JoVE, the Journal of Visualized Experiments, is the world''s first peer reviewed scientific video journal. Established in 2006, JoVE is devoted to publishing scientific research in a visual format to help researchers overcome two of the biggest challenges facing the scientific research community today; poor reproducibility and the time and labor intensive nature of learning new experimental techniques.