The effectiveness of cancer immunotherapy may depend not only on which immune cells reach a tumor, but also on when they arrive. Researchers from Sungkyunkwan University and Seoul National University College of Medicine have demonstrated that the sequence of interactions between immune cells and glioblastoma cells can significantly influence treatment response.
Their findings, published in Neuro-Oncology, suggest that timing is an overlooked factor in the tumor microenvironment and could become an important consideration in the development of personalized immunotherapies for one of the deadliest forms of brain cancer.
Recreating the tumor microenvironment
Glioblastoma (GBM) remains one of the most difficult cancers to treat, partly because its tumor microenvironment suppresses immune activity. Large numbers of microglia, the brain's resident immune cells, accumulate within the tumor and can limit the ability of natural killer (NK) cells to infiltrate and destroy cancer cells.
To better understand these dynamic interactions, the researchers developed a multi-inlet microfluidic tumor-on-a-chip platform. Unlike conventional laboratory models, the system enables precise control over the timing and sequence in which different cell types are introduced into a three-dimensional tumor model. This allowed the team to investigate how identical combinations of tumor and immune cells behave when only the order of interaction changes.
The importance of arriving first
The experiments revealed striking differences. When microglia reached glioblastoma cells before NK cells, STAT3 signalling became activated, reducing NK-cell infiltration and promoting tumor growth. However, when NK cells encountered the tumor first, the cancer cells showed increased expression of the immune-stimulating factor IL12A, resulting in sustained suppression of tumor growth.
The findings indicate that the tumor immune response is influenced not only by the types of cells present, but also by the timing of their interactions. This temporal dimension has been difficult to study using conventional cell cultures or animal models, highlighting the value of more advanced laboratory platforms that can mimic the complexity of the tumor microenvironment.
Precision oncology
The researchers also explored the platform's potential for precision oncology using patient-derived glioblastoma cells. Combining the STAT3 inhibitor WP1066 with the chemotherapy drug temozolomide increased NK-cell infiltration and enhanced tumor cell death, suggesting a synergistic therapeutic effect.
According to the research team, recreating an individual patient's tumor microenvironment on a chip could eventually help identify the most effective drug combinations and treatment schedules before therapy begins. While additional validation will be needed before such approaches can influence clinical decision-making, the study demonstrates how organ-on-a-chip technologies may complement traditional preclinical models.
As immunotherapy continues to evolve, the work highlights an emerging concept in cancer research: understanding when immune responses occur may prove just as important as understanding how they occur. By incorporating the timing of cellular interactions into experimental models, researchers may gain new opportunities to optimize therapies for glioblastoma and other treatment-resistant solid tumors.
Evading immune attacks
Last year, researchers at the University of Pennsylvania developed a tumor-on-a-chip platform that offers new insights into why solid tumors often evade immunotherapy. The transparent microengineered device replicates a vascularized human lung tumor, allowing scientists to observe in real time how CAR T-cells interact with cancer cells and the tumor microenvironment. Using multiomics analysis, the team identified the enzyme DPP4 as a key factor that degrades chemical signals guiding CAR T-cells to tumors.
By adding vildagliptin, a diabetes drug that inhibits DPP4, researchers improved CAR T-cell infiltration and enhanced tumor attack. Published in Nature Biotechnology, the study highlights the platform's potential to accelerate the development of more effective and personalized immunotherapies while reducing reliance on animal testing. The technology also provides a powerful tool for evaluating new CAR T-cell designs before they enter clinical trials.
References
Neuro-Oncology (research)
