Patient-Specific "Blood–Brain Tumor Barrier Chip" Predicts How Glioblastoma Patients Will Respond to Treatment
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Patient-Specific "Blood–Brain Tumor Barrier Chip" Predicts How Glioblastoma Patients Will Respond to Treatment


Even for the same brain tumor treated with the same anticancer drug, the effect can differ from patient to patient. A Korean research team has developed a chip that recreates a patient's own tumor cells together with the surrounding peritumoral vascular environment, making it possible to predict patient-specific treatment responses in advance.

KAIST (President Choongsik Bae) announced on August 18 that a research team led by Professor Song Ih Ahn from the Department of Mechanical Engineering, in collaboration with Professor Jungho Ahn's team at Sungkyunkwan University, Professor Jaejoon Lim of CHA Bundang Medical Center, and Professor Youn-Jung Kang's team at CHA University, has developed a patient-specific blood–brain tumor barrier (BBTB) chip capable of predicting treatment responses in glioblastoma patients.

Glioblastoma is one of the most lethal malignant brain tumors, hard to treat because the cancer cells spread rapidly into normal brain tissue and tumor characteristics differ from patient to patient. The brain is also protected by a "blood–brain barrier," which blocks harmful substances in the blood from entering brain tissue. The problem is that it blocks anticancer drugs too, so not enough of the drug reaches the tumor. When glioblastoma develops, this vascular barrier changes as well. How much it changes differs from patient to patient, which is one reason the same drug can work differently in different people.

Predictions of treatment response have so far relied mainly on tumor genetic information and biomarkers, which cannot capture the patient-specific vascular environment around the tumor or the resulting drug response.

To address this, the team built a chip that includes not only the patient's tumor cells but also the vascular barrier. This barrier is the "route" an anticancer drug must travel to reach the tumor. Patient-derived glioblastoma cells were co-cultured with brain vascular endothelial cells and astrocytes inside a small microfluidic chip. Together they recreate the boundary where tumor tissue meets normal brain tissue. The design also accommodates perivascular and immune cells, allowing the tumor's vascular environment to be reproduced more precisely.

Using tumor cells from three glioblastoma patients, the team built patient-mimicking BBTB chips and applied temozolomide (TMZ) and bevacizumab (BEV), the standard agents in glioblastoma treatment, to compare responses.

The three patients showed the same result on conventional genetic testing, the MGMT promoter methylation biomarker, and were therefore expected to respond similarly. On the chip, however, both the vascular barrier characteristics and the drug responses differed from one patient to another. The chip results showed a high level of agreement with the patients' actual clinical courses, indicating that outcomes can vary with the state of the vascular barrier even when genetic information is similar.

The core advance is that the platform evaluates not only whether cancer cells respond to a drug, but how a treatment acts within a given patient's tumor environment. If predictive performance and reproducibility are validated in a larger cohort, several agents could be tested on a chip made from a patient's own tumor cells to select the most promising strategy in advance. The same environment could also serve to screen new drug candidates.

Professor Song Ih Ahn said, "This study is meaningful in that it presents a platform that recreates patient-derived tumor cells together with the blood–brain tumor barrier, allowing patient-to-patient differences in treatment response to be evaluated in a way that closely reflects reality," adding, "We hope to validate it in a larger patient population and develop it into a preclinical evaluation platform for establishing personalized treatment strategies and for new drug development."

Minsu Ryoo, a doctoral student in KAIST's Department of Mechanical Engineering, and Gaeun Lee, a doctoral student at Sungkyunkwan University, participated as co-first authors. The results were published on June 27, 2026, in Small, an international journal in materials and nanoscience, and were selected as the journal's Front Cover.

※ Paper title: Human Blood-Brain Tumor Barrier on a Chip to Investigate Personalized Treatment for Glioblastoma Patients
DOI: 10.1002/smll.202506712

This research was supported by the Korea–US Collaborative Research Fund of the Ministry of Health and Welfare and the Korea Health Industry Development Institute (RS-2024-00468873), and by the Early-Career Researcher Program of the Ministry of Science and ICT and the National Research Foundation of Korea (RS-2026-25487930).
Paper title: Human Blood-Brain Tumor Barrier on a Chip to Investigate Personalized Treatment for Glioblastoma Patients
DOI: 10.1002/smll.202506712
Fichiers joints
  • Figure 1. The upper-left schematic shows the structure of a microfluidic chip designed to recreate the glioblastoma margin. Brain endothelial cells (HBMECs) in the upper vascular channel are co-cultured with astrocytes and patient-derived glioblastoma cells in the lower tissue channel. The fluorescence images compare healthy blood-brain barrier (BBB) with blood-brain tumor barrier model and graphs in the lower-left compare barrier permeability, electrical resistance, gene expression level, and anticancer drug responses between BBB and patient-specific blood-brain tumor barrier models (BBTB-A, B, and C). The right panel presents MRI scans from three patients with the same IDH-wildtype and MGMT-methylated status, together with their on-chip barrier function and drug responses and actual clinical outcomes, including progression-free survival (PFS) and post-progression survival (PPS). The close agreement between the on-chip results and the patients’ clinical courses demonstrates the model’s potential to predict patient-specific treatment responses.
  • Figure 2. Conceptual illustration of the research (AI-generated image)
  • Members of the research team. Top row, from left: Gaeun Lee, Ph.D. candidate at Sungkyunkwan University; Professor Jungho Ahn of Sungkyunkwan University; Professor Jaejoon Lim of Bundang CHA Medical Center; and Professor Youn-Jung Kang of CHA University. Bottom front row: Minsu Ryoo, Ph.D. candidate at KAIST, and Professor Song Ih Ahn of KAIST. Bottom back row: Nayeong Kang, master’s student at KAIST, and Jinwoo Jung, Ph.D. candidate at KAIST.
Regions: Asia, South Korea
Keywords: Applied science, Engineering, Technology, Health, Medical, Well being, Science, Life Sciences

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