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

• Published in: Nature communications 2024-04, Vol.15 (1), p.3382-3382, Article 3382
• Main Authors: Zhang, Yanmei, Hu, Qifan, Pei, Yuquan, Luo, Hao, Wang, Zixuan, Xu, Xinxin, Zhang, Qing, Dai, Jianli, Wang, Qianqian, Fan, Zilian, Fang, Yongcong, Ye, Min, Li, Binhan, Chen, Mailin, Xue, Qi, Zheng, Qingfeng, Zhang, Shulin, Huang, Miao, Zhang, Ting, Gu, Jin, Xiong, Zhuo
• Format: Article
• Language: English
• Subjects: 13; 13/2; 13/21; 13/31; 13/51; 13/62; 14/28; 38; 38/39; 38/91; 45; 45/23; 45/43; 631/61/2035; 631/67/70; 96; Cancer research; Cell size; Customization; Heterogeneity; Humanities and Social Sciences; Humans; Lung cancer; Lung Neoplasms - genetics; Lung Neoplasms - pathology; Medical research; Microenvironments; Microfluidics; Microinjection; multidisciplinary; Organoids; Organoids - pathology; Precision medicine; Precision Medicine - methods; Science; Science (multidisciplinary); Transcriptomics; Tumor Microenvironment; Tumors
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-024-47737-z

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. Realistic tumour models are critical for the development of clinically relevant treatments. Here, the authors develop a lung cancer assembloid model which recapitulates key components of the primary tumour, and can be used to predict clinical outcome.