CELL INTELLIGENCE · 肿瘤细胞治疗研究

The clinical outcome predictions of conventional in vitro and in vivo models are often inaccurate because they cannot replicate the tumor microenvironment (TME) complexity. Existing 3D models encounter challenges regarding TME complexity replication, engineering constraints, and limited capacity in analyzing immune-cancer interactions.

This study employs 3D embedded bioprinting to develop a heterogeneous lung spheroid (HLS) model, incorporating key stromal factors to better reflect the TME. Transcriptomic profiling via RNA sequencing reveals gene signatures associated with extracellular matrix remodeling, immune suppression, and tumor progression, demonstrating substantial similarity to patient-derived lung tumor samples and validating the biological fidelity of the model.

Functional assays demonstrate that the model effectively replicated TME dynamics, as evidenced by reduced CAR-NK cell infiltration, cytotoxicity, and cytokine secretion with increasing model complexity, indicative of a highly immunosuppressive environment. Advanced CAR-NK cells expressing chemokine receptors are utilized to overcome this immune barrier and enhance migration and infiltration within the physiologically relevant lung TME model.

Overall, this model replicates critical features of the lung TME, showing potential for evaluating next-generation immunotherapies targeting complex solid tumors.