Two common types of brain tumor remain particularly deadly: ependymomas in children and glioblastomas in adults. Both have a median survival of just 1-2 years after diagnosis.
A research team led by David L. Kaplan, Ph.D., Distinguished Professor and Director, Tissue Engineering and Research Center at Tufts School of Engineering, developed the new model. A good model of the tissue-engineered microenvironment of brain ECM is important because beyond physically supporting and connecting neural tissues, the ECM also helps to guide cell growth and development.
“One reason tumors thrive is that they become adapted to growing in the matrix of proteins and other surrounding molecules known as the ECM,” explains Seila Selimovic, Ph.D., director of the NIBIB program in Engineered Tissues. “Kaplan and his colleagues have made a significant jump in being able to study specific mechanisms used by the tumor to alter the surrounding ECM so that it supports tumor growth. With this they can also now examine possible mechanisms that result in tumor resistance to chemotherapy.”
“The first step was to accurately mimic in our tissue culture system what is happening in the patient,” explains Kaplan. “Having done that, we can add and subtract various components to our culture and gain new information–such as which components make tumors grow faster and which ones act to inhibit that growth.”
Kaplan drew from his extensive background in using silk to create implantable devices, such as surgical screws and porous scaffolds that support new cartilage growth. Tissues do not recognize the silk as foreign so there is no inflammation or other immune response.
The team started with a 3D block of porous silk and then seeded it with the matrix material from fetal pigs to support the childhood tumors, and material from adult pigs to support the adult tumors. This biocompatible silk frame served to support the transplanted ECM, additional factors needed to support the human tumor cells such as hyaluronic acid and collagen, as well as the additional tumor cells—without affecting the natural cell/ECM interaction.
“The system yielded some fascinating results,” said Kaplan. “For example, we found that the fetal ECM tissue supported more robust tumor growth than the adult ECM.” He explained that this phenomenon was intriguing considering previous reports that the tumors that are the most rapid proliferators have the ability to alter adult ECM so that it becomes similar to fetal ECM. According to Kaplan, such results suggest that inhibiting a tumor’s ability to alter the ECM towards a more fetal phenotype could be a target for potential therapies.
An unexpected observation was the formation of extracellular droplets of fat that were released by the adult tumor cells, which had never been seen before in less sophisticated culture systems. The working hypothesis put forth by the research team was that the droplets may capture medications used to treat adult glioblastoma before they can reach the tumor cells. That would be consistent with what is found in the clinic—the tendency of adult brain tumors to become resistant to drug treatment over time.
The studies were aided by an imaging system called two-photon microscopy, which provided non-invasive monitoring of what was happening in the cultures in real-time via the laboratory of Irene Georgakoudi, Ph.D., Professor, Department of Biomedical Engineering at Tufts University.
Based on the initial results, the team is enthusiastic about using the system to rapidly test drug candidates that have tumor-inhibiting activity. In the future, the system could potentially be used to identify the most effective treatments by testing potential medications against 3D ECM cultures that are specific to each patient.
The results were published in the October issue of Nature Communications1. This work was funded by the US National Institutes of Health (NIH) P41 Tissue Engineering Resource Center Grant (EB002520) from the National Institute of Biomedical Imaging and Bioengineering, the National Institute of Neurological Diseases and Stroke, an NIH Research Infrastructure grant, and grants from NSF and USDA.
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