PT  - JOURNAL ARTICLE
AU  - Yin, Shenyi
AU  - Xi, Ruibin
AU  - Wu, Aiwen
AU  - Wang, Shu
AU  - Li, Yingjie
AU  - Wang, Chaobin
AU  - Tang, Lei
AU  - Xia, Yuchao
AU  - Yang, Di
AU  - Li, Juan
AU  - Ye, Buqing
AU  - Yu, Ying
AU  - Wang, Junyi
AU  - Zhang, Hanshuo
AU  - Ren, Fei
AU  - Zhang, Yuanyuan
AU  - Shen, Danhua
AU  - Wang, Lin
AU  - Ying, Xiangji
AU  - Li, Zhongwu
AU  - Bu, Zhaode
AU  - Ji, Xin
AU  - Gao, Xiangyu
AU  - Jia, Yongning
AU  - Jia, Ziyu
AU  - Li, Nan
AU  - Li, Ziyu
AU  - Ji, Jia-Fu
AU  - Xi, Jianzhong Jeff
TI  - Patient-derived tumor-like cell clusters for drug testing in cancer therapy
AID  - 10.1126/scitranslmed.aaz1723
DP  - 2020 Jun 24
TA  - Science Translational Medicine
PG  - eaaz1723
VI  - 12
IP  - 549
4099  - http://stm.sciencemag.org/content/12/549/eaaz1723.short
4100  - http://stm.sciencemag.org/content/12/549/eaaz1723.full
AB  - Despite recent advances in medicine, identifying the optimal treatment regimen for each patient with cancer remains difficult and often imprecise. There are now multiple methods for analyzing a tumor’s drug sensitivity, including tumor organoids and patient-derived xenografts, but each has its own drawbacks such as a lack of tumor stroma or the time required to obtain results. The approach designed by Yin et al., patient-derived tumor-like cell clusters, aims to overcome some of these shortcomings by using ex vivo culture of tumor cells together with their stroma. Initial testing of this method has shown promising results when applied to patients with several different tumor types.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.