RT Journal Article SR Electronic T1 Patient-derived tumor-like cell clusters for drug testing in cancer therapy JF Science Translational Medicine FD American Association for the Advancement of Science SP eaaz1723 DO 10.1126/scitranslmed.aaz1723 VO 12 IS 549 A1 Yin, Shenyi A1 Xi, Ruibin A1 Wu, Aiwen A1 Wang, Shu A1 Li, Yingjie A1 Wang, Chaobin A1 Tang, Lei A1 Xia, Yuchao A1 Yang, Di A1 Li, Juan A1 Ye, Buqing A1 Yu, Ying A1 Wang, Junyi A1 Zhang, Hanshuo A1 Ren, Fei A1 Zhang, Yuanyuan A1 Shen, Danhua A1 Wang, Lin A1 Ying, Xiangji A1 Li, Zhongwu A1 Bu, Zhaode A1 Ji, Xin A1 Gao, Xiangyu A1 Jia, Yongning A1 Jia, Ziyu A1 Li, Nan A1 Li, Ziyu A1 Ji, Jia-Fu A1 Xi, Jianzhong Jeff YR 2020 UL http://stm.sciencemag.org/content/12/549/eaaz1723.abstract 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.