Comparison of Cell and Organoid-Level Analysis of Patient-Derived 3D Organoids to Evaluate Tumor Cell Growth Dynamics and Drug Response

比较患者来源的 3D 类器官的细胞和类器官水平分析,以评估肿瘤细胞生长动力学和药物反应

阅读:9
作者:Seungil Kim, Sarah Choung, Ren X Sun, Nolan Ung, Natasha Hashemi, Emma J Fong, Roy Lau, Erin Spiller, Jordan Gasho, Jasmine Foo, Shannon M Mumenthaler

Abstract

3D cell culture models have been developed to better mimic the physiological environments that exist in human diseases. As such, these models are advantageous over traditional 2D cultures for screening drug compounds. However, the practicalities of transitioning from 2D to 3D drug treatment studies pose challenges with respect to analysis methods. Patient-derived tumor organoids (PDTOs) possess unique features given their heterogeneity in size, shape, and growth patterns. A detailed assessment of the length scale at which PDTOs should be evaluated (i.e., individual cell or organoid-level analysis) has not been done to our knowledge. Therefore, using dynamic confocal live cell imaging and data analysis methods we examined tumor cell growth rates and drug response behaviors in colorectal cancer (CRC) PDTOs. High-resolution imaging of H2B-GFP-labeled organoids with DRAQ7 vital dye permitted tracking of cellular changes, such as cell birth and death events, in individual organoids. From these same images, we measured morphological features of the 3D objects, including volume, sphericity, and ellipticity. Sphericity and ellipticity were used to evaluate intra- and interpatient tumor organoid heterogeneity. We found a strong correlation between organoid live cell number and volume. Linear growth rate calculations based on volume or live cell counts were used to determine differential responses to therapeutic interventions. We showed that this approach can detect different types of drug effects (cytotoxic vs cytostatic) in PDTO cultures. Overall, our imaging-based quantification workflow results in multiple parameters that can provide patient- and drug-specific information for screening applications.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。