A detailed molecular analysis reveals four subtypes of a common brain cancer.
A deeper look at the molecular makeup of meningiomas revealed four distinct subtypes of the common brain tumor. These bars — shown here below the surface of water — illustrate how the proportions of T cells (blue), macrophages (purple), endothelial cells (dark green), fibroblasts (light green) and neoplastic cells (red) vary in tumor samples from patients with the four subtypes. These variations helped to define the four subtypes, separated here by thick dark bars. Identifying and describing the subtypes will help researchers better predict the aggressiveness of patients’ tumors and select better treatment options. Credit: Nassiri, F. et al. Nature; iStock
Meningiomas are relatively common tumors that form in the membrane lining the brain. Although most of the time these tumors are not aggressive and can be treated with surgery, there are limited treatment options for more aggressive cases.
To better understand the biology of this cancer and identify new therapies for it, a multi-national consortium co-led by Senior Investigator Kenneth Aldape, M.D., conducted a thorough molecular analysis of meningiomas, identifying four subtypes of the disease, as well as one potential treatment for a particularly aggressive subtype. The results were published in Nature.
“Even if most meningiomas are benign, the brain tumor can affect the person’s life in important ways in terms of neurological deficits, and can be lethal in some cases,” explains Aldape, noting that there are currently no drugs approved by the U.S. Food and Drug Administration (FDA) to treat meningiomas.
This prompted Aldape and his CCR colleagues to partner with researchers at the University of Toronto and the International Consortium on Meningiomas to conduct a large-scale analysis of meningiomas. Specifically, they analyzed DNA copy numbers, gene mutations and RNA expression, as well as DNA methylation, which influences DNA expression. “We wanted to define robust subtypes and the only way to do that would be to get this composite of molecular data,” explains Aldape.
The team then applied a machine learning algorithm to the data to identify four previously unknown molecular subtypes of meningioma. The subtypes differ in their immunogenic features, genetic mutations, metabolism and aggressiveness.
Next, the researchers cross-referenced the gene activity patterns of the meningiomas to a database of FDA-approved drugs, exploring whether any existing therapies could be suitable candidates for treating each subtype. These results suggested that the drug vorinostat may be effective against MG4, one of the more aggressive subtypes. Vorinostat binds to the active site of enzymes known as histone deacetylases, which alter chemical modifications of major DNA-binding proteins.
In follow-up experiments, the researchers showed that vorinostat in fact can impair the viability of MG4 cancer cells in a petri dish and can limit tumor growth and improve survival in mice with MG4 tumors.
Aldape notes that this study will advance research on meningiomas in several ways, including the development of better animal models to study the various subtypes of meningioma and the development of new targeted therapies.
“Further work will examine whether specific drugs will work against the different subtypes of these tumors,” says Aldape, noting it’s exciting to be learning new insights into this understudied type of brain cancer.
Reference
Nassiri, F. et al. Nature. 2021 Aug 25;597(7874):119-125.
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