类有机物
公制(单位)
药物反应
生物
药物发现
生物医学工程
药品
计算生物学
生物信息学
医学
药理学
细胞生物学
运营管理
经济
作者
Christophe Deben,Edgar Cardenas De La Hoz,Felicia Rodrigues Fortes,Maxim Le Compte,Sofie Seghers,Steve Vanlanduit,H. Vercammen,Bert Van Den Bogert,Nelson Dusetti,Abraham Lin,Geert Roeyen,Marc Peeters,Hans Prenen,Filip Lardon,Evelien Smits
标识
DOI:10.1038/s42003-024-07329-5
摘要
This study focuses on refining growth-rate-based drug response metrics for patient-derived tumor organoid screening using brightfield live-cell imaging. Traditional metrics like Normalized Growth Rate Inhibition (GR) and Normalized Drug Response (NDR) have been used to assess organoid responses to anticancer treatments but face limitations in accurately quantifying cytostatic and cytotoxic effects across varying growth rates. Here, we introduce the Normalized Organoid Growth Rate (NOGR) metric, specifically developed for brightfield imaging-based assays. A label-free image analysis model was applied to segment organoids precisely, track their growth rates over time, and classify viable and dead organoids. Testing eleven phenotypically distinct pancreatic cancer organoid models with five chemotherapeutics demonstrates that the NOGR metric more effectively captures cytostatic and cytotoxic drug effects compared to existing methods. This approach enhances the biological relevance of drug sensitivity assessments on organoids and offers a valuable tool for advancing personalized cancer treatment strategies.
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