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.