Patient-derived tumor-like cell clusters for drug testing in cancer therapy

药品 医学 癌症治疗 癌症研究 癌症 细胞 生物信息学 肿瘤科 内科学 药理学 生物 遗传学
作者
Shenyi Yin,Ruibin Xi,Aiwen Wu,Shu Wang,Yingjie Li,Chaobin Wang,Lei Tang,Yuchao Xia,Di Yang,Juan Li,Buqing Ye,Ying Yu,Junyi Wang,Hanshuo Zhang,Fei Ren,Yuanyuan Zhang,Danhua Shen,Lin Wang,Xiangji Ying,Zhongwu Li
出处
期刊:Science Translational Medicine [American Association for the Advancement of Science]
卷期号:12 (549) 被引量:102
标识
DOI:10.1126/scitranslmed.aaz1723
摘要

Several patient-derived tumor models emerged recently as robust preclinical drug-testing platforms. However, their potential to guide clinical therapy remained unclear. Here, we report a model called patient-derived tumor-like cell clusters (PTCs). PTCs result from the self-assembly and proliferation of primary epithelial, fibroblast, and immune cells, which structurally and functionally recapitulate original tumors. PTCs enabled us to accomplish personalized drug testing within 2 weeks after obtaining the tumor samples. The defined culture conditions and drug concentrations in the PTC model facilitate its clinical application in precision oncology. PTC tests of 59 patients with gastric, colorectal, or breast cancers revealed an overall accuracy of 93% in predicting their clinical outcomes. We implemented PTC to guide chemotherapy selection for a patient with mucinous rectal adenocarcinoma who experienced recurrence with metastases after conventional therapy. After three cycles of a nonconventional therapy identified by the PTC, the patient showed a positive response. These findings need to be validated in larger clinical trials, but they suggest that the PTC model could be prospectively implemented in clinical decision-making for therapy selection.
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