The development of the patient-specific lung cancer assembloid (LCA) model using droplet microfluidic technology represents a significant advancement in cancer research and precision medicine. By addressing the limitations of current in vitro cancer models, such as the inability to mimic the complex three-dimensional architecture and heterogeneous tumor microenvironments (TME), this innovative approach offers new opportunities for studying cancer biology and testing personalized treatment strategies.

The use of microfluidic technology and a microinjection strategy allows for precise manipulation of clinical samples, enabling the rapid generation of LCAs with consistent size and cell composition. By encapsulating patient tumor-derived TME cells and lung cancer organoids within microgels, the LCA model successfully recapitulates the inter- and intratumoral heterogeneity, cellular diversity within the TME, and the genomic and transcriptomic landscape of the original tumors.

One of the key advantages of the LCA model is its ability to reconstruct the functional heterogeneity of cancer-associated fibroblasts, a critical component of the TME, and to reflect the influence of the TME on drug responses. This capability enhances the model’s relevance for studying tumor biology and evaluating therapeutic interventions.

Furthermore, the LCA model demonstrates promising potential for personalized medicine by accurately replicating clinical outcomes and predicting individualized treatment responses. By leveraging patient-specific characteristics, such as genomic profiles and TME composition, the LCA model could serve as a valuable tool for predicting treatment efficacy and guiding therapeutic decision-making.

Overall, this study provides a valuable method for precisely fabricating cancer assembloids and establishes the LCA model as a robust platform for cancer research and personalized medicine. Its ability to faithfully recapitulate key aspects of tumor biology and predict treatment responses underscores its importance in advancing our understanding of cancer and improving patient care.

Keywords: patient-specific lung cancer assembloid, droplet microfluidic technology, cancer heterogeneity, personalized medicine