Even for the same brain tumour 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 tumour 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 Centre, and Professor Youn-Jung Kang's team at CHA University, has developed a patient-specific blood–brain tumour barrier (BBTB) chip capable of predicting treatment responses in glioblastoma patients.

The results were published in Small, an international journal in materials and nanoscience, and were selected as the journal's Front Cover.

Glioblastoma is one of the most lethal malignant brain tumours, hard to treat because the cancer cells spread rapidly into normal brain tissue and tumour 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 tumour.

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 tumour genetic information and biomarkers, which cannot capture the patient-specific vascular environment around the tumour or the resulting drug response.

To address this, the team built a chip that includes not only the patient's tumour cells but also the vascular barrier.

This barrier is the "route" an anticancer drug must travel to reach the tumour.

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 tumour tissue meets normal brain tissue.

The design also accommodates perivascular and immune cells, allowing the tumour's vascular environment to be reproduced more precisely.

Using tumour 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 tumour 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 tumour 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 tumour cells together with the blood–brain tumour 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 personalised 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.

Source: The Korea Advanced Institute of Science and Technology (KAIST)