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3D cell model helps identify drug candidates to treat brain cancer

One of the challenges for drugs treating brain cancer is overcoming the blood brain barrier which filters out toxins, keeping the area clean. BRAINHIB used an iterative selection process to create a library of potential drug candidates, also creating 3D cell models for future trials.

Health

Glioblastoma multiforme or glioma is the most aggressive of the cancers that begin in the brain. As with many other types of cancer, it starts with DNA mutations in one cell, leading to cells dividing uncontrollably and invading surrounding tissue. It affects around 4-5 per 100 000 adults per year in Europe, making it the most common central nervous system cancer. Without treatment, average life expectancy following diagnosis is only 3 months. With the help of support from the Marie Skłodowska-Curie Actions programme, the BRAINHIB project set out to discover new drugs to fight glioma, looking especially at those capable of penetrating the blood brain barrier. The team, working at the University of Edinburgh, the host institution, tested newly constructed molecular compounds as potential drug candidates. They also improved current models to study the disease, incorporating cells extracted from patients undergoing surgery. The work resulted in a large library of promising molecules as cures for glioma and other diseases. Additionally, 3D patient-derived cellular models which more accurately resemble the disease were developed. “Having the tools to verify the potential of molecules at an early stage, could speed up the discovery of novel patentable drugs,” says Teresa Valero, Marie Skłodowska-Curie Research Fellow.

Molecules and models

Once the chemical building blocks had been assembled to create molecules thought to be potentially useful for drug candidates, they were added to the growth medium of glioma cells. After 5 days the team measured the growth of the glioma cells, comparing them with cell cultures without those molecules. The molecules were also tested on healthy cells of the blood brain barrier, to rule out any toxic effects. Molecules which were shown to have both anticancer and safe properties, were identified as potential drug candidates. “This iterative cycle ends when one or several drugs efficiently stop the growth of glioma cells without affecting the normal cells. The best candidate inhibitors – our ‘hits’ – were then studied to identify how they work,” explains Valero. Drugs deemed successful have to stop the growth of one or several proteins in cancerous cells. The team used so-called proteomic techniques to identify those target proteins, the oncotargets, and better understand how the drug’s structure and activity worked. Proteomic techniques were also used to help predict side effects, since these are usually due to targeting the wrong proteins. The team found that their most promising molecules all targeted the same two oncotargets to stop the growth of glioma cells. As the next drug development stage would involve prediction of how the drugs would behave within the human body, the team developed a 3D cellular model. This was based on patient-derived cells provided by the Glioma Cellular Genetics Resource, University of Edinburgh. “By more accurately resembling what happens inside patients, these 3D cultures can more effectively predict the efficacy of proposed drugs,” notes Valero.

An unmet medical need

The best current treatment for glioma involves surgical removal of tumours, followed by a combination of radiotherapy and chemotherapy, using the drug temozolomide. Even with the best available treatment, the average survival time is 10 to 15 months. “The discovery of these new drugs, alongside our new 3D research model, opens new avenues for the treatment of this unmet medical need,” says Valero. The results of BRAINHIB have inspired a larger project at the University of Edinburgh for synthesising and then testing promising original chemical molecules in these new 3D models.

Keywords

BRAINHIB, cancer, Glioblastoma multiforme, glioma, brain, DNA, cell, drugs, 3D cell model, molecular compounds, oncotargets

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