Nature Communications: A patient-specific lung cancer assembloid model
Tumor model is an important tool for tumor research and evaluation of tumor therapy, as well as a key rate-limiting factor for anti-tumor drug development. Traditional tumor models (two-dimensional tumor cells, mouse models, etc.) are unable to reproduce the three-dimensional structure and complex microenvironment of human tumors. Although the current popular model tumor organoids maintain a good consistency with patient tumors in molecular and tissue morphology, tumor organoids have problems such as single composition, lack of TME and poor intra-batch consistency. How to quickly and accurately construct a personalized tumor model with heterogeneous tumor microenvironment is a key problem to be solved in the field of tumor research and treatment.
Based on this, the research group of Zhuo Xiong and Ting Zhang from the Department of Mechanics of Tsinghua University and the research group of Gu Jin from the Department of Automation of Tsinghua University published the latest research results in the journal Nature Communications: “A patient-specific lung cancer assembloid model with heterogeneous tumor microenvironments”. This study innovatively proposed the rapid and accurate construction of a personalized lung cancer assembly model based on droplet microfluidic technology. The model had good batch consistency, reproduced the heterogeneity and microenvironment (including immune microenvironment) of personalized tumors in vitro, and could accurately predict the drug response of clinical patients (Figure 1). It provides a new model for personalized tumor treatment and precise drug screening, and has important translational application prospects.
Yanmei Zhang, a former postdoctoral fellow in the Department of Mechanics at Tsinghua University (now an associate researcher at the Beijing Academy of Science and Technology), Qifan Hu, a doctoral student in the Department of Automation, and Yuquan Pei, Director of the Peking University Cancer Hospital are the first authors of this paper. Xiong Zhuo, Professor in the Department of Mechanics at Tsinghua University, and Gu Jin, associate professor in the Department of Automation at Tsinghua University are the corresponding authors of this paper. Institute of New Materials and Advanced Manufacturing, Beijing Academy of Science and Technology, Peking University Cancer Hospital, PLA General Hospital and Chinese Academy of Medical Sciences Cancer Hospital participated in the study. The research was supported by the Toyota Foundation of Tsinghua University and the National Natural Science Youth Foundation of China.
In order to achieve rapid and accurate construction of assembly-like models with tumor microenvironment, the research team first developed droplet microfluidic technology based on micro-sampling strategy and hydrogel materials with good primary cell biocompatibility. Lung cancer organoids (LCOs), tumor-associated fibroblasts (CAFs) and tumor-infiltrating lymphocytes (TILs) derived from lung cancer patients were embedded in an optimized hydrogel material (GelMA-Matrigel), and 400-500 micron preassembled bodies were formed by mineral oil phase shear and 405 UV curing. The assembly-like model (LCAs) of cells with tumor-like tissue structure and tumor microenvironment can be formed after 3-5 days of culture in vitro (Figure 1, Figure 2). This technology has the characteristics of precise micro-control and rapid and accurate molding, which can accurately control the micro-cells (5-10 microliters) from clinical puncture samples, and more than 200 LCAs can be formed in 0.6 minutes. In addition, LCAs individuals have good consistency in size and cell distribution. The class assembly model formed based on GelMA-Matrigel material can be frozen and resuscitated directly, and the recovered LCAs can still maintain good class structure, morphology and cell activity, laying a foundation for the storage of class assembly.
Fig 1
Fig 2
In order to fully verify the validity of the assembly-like model, the research team demonstrated the similarity between assembly-like bodies and corresponding in vivo tumors at the molecular, cellular and tissue levels through transcriptome, genome, single-cell sequencing and pathological staining analysis (FIG. 3, FIG. 4), and found that the LCAs model could reconstruct CAFs with heterogeneous functions in vitro. To demonstrate the effect of CAFs on the drug responsiveness of cancer. This is a function that tumor organoids lack.
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Whether tumor models can be used as accurate models for precise drug screening and personalized diagnosis and treatment, the accepted criteria include: 1) consistency and repeatability between parallel groups of drug screening, 2) inter-individual heterogeneity reflecting clinical drug response; 3) Accuracy of drug response prediction in clinical patients. The research team conducted verification respectively, and found that the drug test results based on the LCAs model had strong repeatability, good consistency between parallel groups, and could fully reflect the differences in drug response among individuals, and could well predict clinical targeted therapy and PD-1-based immunocombined chemotherapy, and the prediction accuracy of drug response of 7 clinical patients reached 100%. It is fully proved that the LCAs model can be used as an ideal tumor drug screening model and personalized guided drug use model (Figure 5). In the future, the team will further verify the application value of the model in personalized guided medication in more samples and more cancer types.
Fig 5