作者
Shenyi Yin,Ying Yu,Nan Wu,Minglei Zhuo,Yanmin Wang,Yanjie Niu,Yiqian Ni,Fang Hu,Cuiming Ding,Huan Liu,Xinghua Cheng,Jin Peng,Juan Li,Yang He,Jiaxin Li,Junyi Wang,Hanshuo Zhang,Xiaoyu Zhai,Bing Liu,Yaqi Wang,Yan Shi,Wei Ma,Wenqing Li,Jincui Peng,Fei Peng,Ruibin Xi,Buqing Ye,Liyan Jiang,Jianzhong Xi
摘要
Many patient-derived tumor models have emerged recently. However, their potential to guide personalized drug selection remains unclear. Here, we report patient-derived tumor-like cell clusters (PTCs) for non-small cell lung cancer (NSCLC), capable of conducting 100–5,000 drug tests within 10 days. We have established 283 PTC models with an 81% success rate. PTCs contain primary tumor epithelium self-assembled with endogenous stromal and immune cells and show a high degree of similarity to the original tumors in phenotypic and genotypic features. Utilizing standardized culture and drug-response assessment protocols, PTC drug-testing assays reveal 89% overall consistency in prospectively predicting clinical outcomes, with 98.1% accuracy distinguishing complete/partial response from progressive disease. Notably, PTCs enable accurate prediction of clinical outcomes for patients undergoing anti-PD1 therapy by combining cell viability and IFN-γ value assessments. These findings suggest that PTCs could serve as a valuable preclinical model for personalized medicine and basic research in NSCLC.