Glioblastoma or GBM is a rare but aggressive primary brain cancer, also referred to as a grade IV astrocytoma. It is the most common, fast-growing tumor. According to the National Cancer Institute the incidence of glioblastoma is 3.21 per 100,000 population, accounting for 47.7% of all cases brain cancers.  The disease invades the nearby brain tissue, but generally does not spread to distant organs.  After surgical removal of the cancer, the disease often returns.

The current standard of care for diagnosed glioblastoma is surgical resection to the extent feasible, followed by chemotherapy temozolomide (Temodar®; Merck & Co) and/or adjuvant radiotherapy. [1] However, about half of patients die within 18 months.

However,  a novel 3D tissue-engineered model of the glioblastoma tumor microenvironment, developed by scientists at Virginia Tech, may be used to learn why the tumors return and what treatments will be most effective at eradicating them – right down to a patient-specific level.

The model and its development are described in a paper published July 29, 2022 in Nature Partner Journals Precision Oncology. [2]


“Our goal is ultimately to develop a personalized medicine approach in which we can take a patient’s tumor, build a model of that tumor in a dish, test drugs on it, and tell a clinician which therapy will work best to treat it,” said Jennifer Munson, associate professor at the Fralin Biomedical Research Institute at VTC and the paper’s corresponding author.

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The model is an important step to identify new markers and therapies for the cancer. Research using the new model has already identified a new measure for understanding a patient’s tumor, including the capability of the cancer cells to renew and differentiate themselves, which is an indicator of how the cancer will respond to drug treatments.

Jennifer Munson, associate professor at the Fralin Biomedical Research Institute at VTC, helped develop a novel 3D tissue-engineered model of the glioblastoma tumor microenvironment that can be used to learn why the tumors return and what treatments will be most effective at eradicating them. Photo courtesey: © 2022. Clayton Metz for Virginia Tech. Used with permission.

Munson, a tissue engineer who is also an associate professor in Virginia Tech’s Department of Biomedical Engineering and Mechanics and one of the co-directors of the Virginia Tech Cancer Research Alliance, began developing the models in 2014. While other engineered models exist, this one accounts for cell types other than tumor cells, along with the space for the tumor to grow and spread, and other aspects of the actual tumor microenvironment.

Munson’s models, which are typically about the size of a pencil eraser, more accurately recreate that environment for study, including cells unique to the central nervous system such as astrocytes and microglia, and in ratios based on those found in patients.

The model also considers the movement of fluid between and around cells in tissues — known as interstitial fluid flow — which is known to increase in tumors and speed the cancer’s spread. Fluid flow in the model also allows for easy testing of drug therapies.

The microenvironment is crucial to understanding why glioblastoma is so difficult to treat. Though a tumor can be removed, tumor cells tend to invade the surrounding tissue where they become more harmful or resistant to therapies, allowing the cancer to return.

“We wanted to mimic that environment as closely as possible because that is what you would be later treating with drugs or doing any sort of follow up treatment,” Munson said.

Munson and her team have used the models to test the impact of different treatments, analyzing for how cancer cells invade tissue, how they proliferate, their ability to renew themselves, and how many cells die. They found results varied widely, which highlights the importance of a personalized medicine approach to glioblastoma and the value of being able to recreate an individual patient’s tumor microenvironment.

“The model can help us answer questions like, can we predict therapeutic response?” Munson said. “Can we see how these different cell types contribute to tumor cell behavior, or can we just better understand this microenvironment that allows physicians to more effectively treat patients who typically have a poor chance of survival?”

Highlights of prescribing information
Temozolomide (Temodar®; Merck & Co)(Prescribing Information)

[1][1] Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJ, Belanger K, Brandes AA, Marosi C, Bogdahn U, Curschmann J, Janzer RC, Ludwin SK, Gorlia T, Allgeier A, Lacombe D, Cairncross JG, Eisenhauer E, Mirimanoff RO; European Organisation for Research and Treatment of Cancer Brain Tumor and Radiotherapy Groups; National Cancer Institute of Canada Clinical Trials Group. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med. 2005 Mar 10;352(10):987-96. doi: 10.1056/NEJMoa043330. PMID: 15758009.
[2] Cornelison RC, Yuan JX, Tate KM, Petrosky A, Beeghly GF, Bloomfield M, Schwager SC, Berr AL, Stine CA, Cimini D, Bafakih FF, Mandell JW, Purow BW, Horton BJ, Munson JM. A patient-designed tissue-engineered model of the infiltrative glioblastoma microenvironment. NPJ Precis Oncol. 2022 Jul 29;6(1):54. doi: 10.1038/s41698-022-00290-8. PMID: 35906273; PMCID: PMC9338058.

Featured image: Gabriela Mendes, a postdoctoral associate at Fralin Biomedical Research Institute at VTC, holds an example of the 3D model of the glioblastoma tumor microenvironment the lab developed to study how different people’s cancers respond to different therapies. Photo courtesey: © 2022. Clayton Metz for Virginia Tech. Used with permission.


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