Head and neck cancer organoids established by modification of the CTOS method can be used to predict in vivo drug sensitivity

通过改进CTOS方法构建的头颈癌类器官可用于预测体内药物敏感性。

阅读:1

Abstract

OBJECTIVES: Currently there are no standard biomarkers of head and neck squamous cell carcinoma (HNSCC) response to therapy. This is, due to a lack of adequate predictive tumor models. To this end, we established cancer organoid lines from individual patient's tumors, and characterized their growth characteristics and response to different drug treatments with the objective of using these models for prediction of treatment response. MATERIALS AND METHODS: Forty-three patients' samples were processed to establish organoids. To analyze the character of these organoids, immunohistochemistry, Western blotting, drug sensitivity assays, clonogenic survival assays, and animal experiments were performed. The HPV status and TP53 mutational status were also confirmed in these lines. RESULTS: HNSCC organoids were successfully established with success rate of 30.2%. Corresponding two-dimensional cell lines were established from HNSCC organoids at higher success rate (53.8%). These organoids showed similar histological features and stem cell, epithelial and mesenchymal marker expression to the original tumors, thus recapitulating many of the characteristics of the original tumor cells. The cisplatin and docetaxel IC50 were determined for HNSCC organoids and the corresponding 2D cell lines using drug sensitivity and clonogenic survival assays. Responses to drug treatment in vivo were found to be similar to the IC(50) calculated from organoids by drug sensitivity assays in vitro. CONCLUSION: We established novel in vitro HNSCC cancer organoid lines retaining many properties of the original tumors from they were derived. These organoids can predict in vivo drug sensitivity and may represent useful tools to develop precision treatments for HNSCC.

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。