Gastric Cancer Assembloids Derived from Patient-Derived Xenografts: A Preclinical Model for Therapeutic Drug Screening

The construction of reliable preclinical models is crucial for understanding the molecular mechanisms involved in gastric cancer and for advancing precision medicine. Currently, existing in vitro tumor models often do not accurately replicate the human gastric cancer environment and are unsuitable for high-throughput therapeutic drug screening. In this study, droplet microfluidic technology is employed to create novel gastric cancer assembloids by encapsulating patient-derived xenograft gastric cancer cells and patient stromal cells in Gelatin methacryloyl (GelMA)-Gelatin-Matrigel microgels. The usage of GelMA-Gelatin-Matrigel composite hydrogel effectively alleviated cell aggregation and sedimentation during the assembly process, allowing for the handling of large volumes of cell-laden hydrogel and the uniform generation of assembloids in a high-throughput manner. Notably, the patient-derived xenograft assembloids exhibited high consistency with primary tumors at both transcriptomic and histological levels, and can be efficiently scaled up for preclinical drug screening efforts. Furthermore, the drug screening results clearly demonstrated that the in vitro assembloid model closely mirrored in vivo drug responses. Thus, these findings suggest that gastric cancer assembloids, which effectively replicate the in vivo tumor microenvironment, show promise for enabling more precise high-throughput drug screening and predicting the clinical outcomes of various drugs. Realistic cancer models are critical for drug screening and personalized medicine. Here, the authors develop a preclinical gastric cancer assembloid model that demonstrates a good intra-batch consistency and recapitulates key components of the primary tumors, overcoming the throughput problem of traditional preclinical cancer models in drug screening. This model can be used in therapeutic drug screening and predicting clinical outcomes. image