A patient-specific lung cancer assembloid model with heterogeneous tumor microenvironments

Yanmei Zhang, Qifan Hu, Yuquan Pei, Hao Luo, Zixuan Wang, Xinxin Xu, Qing Zhang, Jianli Dai, Qianqian Wang, Zilian Fan, Yongcong Fang, Min Ye, Binhan Li, Mailin Chen, Qi Xue, Qingfeng Zheng, Shulin Zhang, Miao Huang, Ting Zhang, Jin Gu () and Zhuo Xiong ()
Additional contact information
Yanmei Zhang: Tsinghua University
Qifan Hu: Tsinghua University
Yuquan Pei: Peking University Cancer Hospital and Institute
Hao Luo: Tsinghua University
Zixuan Wang: Tsinghua University
Xinxin Xu: Medical School of Chinese PLA
Qing Zhang: Beijing Academy of Science and Technology
Jianli Dai: Beijing Academy of Science and Technology
Qianqian Wang: Beijing Academy of Science and Technology
Zilian Fan: Tsinghua University
Yongcong Fang: Tsinghua University
Min Ye: Tsinghua University
Binhan Li: Tsinghua University
Mailin Chen: Peking University Cancer Hospital & Institute
Qi Xue: Chinese Academy of Medical Sciences and Peking Union Medical College
Qingfeng Zheng: Chinese Academy of Medical Sciences and Peking Union Medical College
Shulin Zhang: Chinese Academy of Medical Sciences and Peking Union Medical College
Miao Huang: Peking University Cancer Hospital and Institute
Ting Zhang: Tsinghua University
Jin Gu: Tsinghua University
Zhuo Xiong: Tsinghua University

Nature Communications, 2024, vol. 15, issue 1, 1-17

Abstract: Abstract Cancer models play critical roles in basic cancer research and precision medicine. However, current in vitro cancer models are limited by their inability to mimic the three-dimensional architecture and heterogeneous tumor microenvironments (TME) of in vivo tumors. Here, we develop an innovative patient-specific lung cancer assembloid (LCA) model by using droplet microfluidic technology based on a microinjection strategy. This method enables precise manipulation of clinical microsamples and rapid generation of LCAs with good intra-batch consistency in size and cell composition by evenly encapsulating patient tumor-derived TME cells and lung cancer organoids inside microgels. LCAs recapitulate the inter- and intratumoral heterogeneity, TME cellular diversity, and genomic and transcriptomic landscape of their parental tumors. LCA model could reconstruct the functional heterogeneity of cancer-associated fibroblasts and reflect the influence of TME on drug responses compared to cancer organoids. Notably, LCAs accurately replicate the clinical outcomes of patients, suggesting the potential of the LCA model to predict personalized treatments. Collectively, our studies provide a valuable method for precisely fabricating cancer assembloids and a promising LCA model for cancer research and personalized medicine.

Date: 2024
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DOI: 10.1038/s41467-024-47737-z

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