Modeling Tumor–Immune Dynamics: Patient-Derived Cancer Based Fluidic System for In Vitro Immunotherapy

Lung cancer remains the leading cause of cancer related mortality in the United States, accounting for approximately one in five cancer deaths, underscoring the urgent need for improved therapeutic strategies. Immunotherapy has emerged as a transformative modality in oncology, enabling more targeted and personalized treatment approaches; however, clinical response rates remain variable, highlighting gaps in preclinical models that adequately capture tumor–immune interactions. There is a growing demand for physiologically relevant in vitro cancer models capable of supporting mechanistic studies, therapeutic screening, and translational decision making prior to clinical evaluation.

Patient derived cancer organoid models offer enhanced biological relevance by preserving key architectural, cellular, and molecular features of tumors in vivo, including cell–cell and cell–matrix interactions. The Human Cancer Models Initiative (HCMI), an international consortium, has developed a diverse repository of genomically and clinically annotated tumor-derived models, which are made broadly accessible through ATCC. These models include both common and rare cancer types, addressing a critical need for standardized, well-characterized platforms to support oncology research and drug development.

In this study, HCMI lung cancer organoid models were used to establish a tumor microenvironment (TME) through co culture with Jurkat T cells within a commercially available on chip, microfluidic platform to evaluate cell based immunotherapy in vitro.  Jurkat T cells demonstrated active infiltration into the tumor microenvironment and exerted cytotoxic effects on tumor cells, supporting the suitability of this platform for assessing tumor–immune interactions within a controlled in vitro setting.

Collectively, these findings highlight the utility of patient-derived HCMI lung cancer organoid models for investigating immunotherapeutic mechanisms and screening candidate therapies in complex three-dimensional and microfluidic environments. The growing demand for human-relevant, scalable, and well-annotated cancer models positions these systems as valuable tools for advancing immuno-oncology research and translational drug development.