Better Predictions

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Researchers discover new way to classify brain tumours that may outperform current standard.
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Meningiomas are a form of brain cancer that is traditionally grouped into three grades based on cellular features seen under a microscope by a trained pathologist.

Researchers at UHN have uncovered a new classification system for meningiomas—the most common type of brain cancer, accounting for 30% of all brain tumours. The work was led by Dr. Gelareh Zadeh, Senior Scientist at the Princess Margaret Cancer Centre and Head of Neurosurgery at Toronto Western Hospital. It will be presented during the Plenary Session of the Society for Neuro-Oncology Annual Scientific Meeting.

Currently, brain tumours are classified using criteria published by the World Health Organization (WHO), which categorizes them into three grades based on histopathological features by examining them under a microscope. However, this classification system does not mirror the clinical behaviour of all meningiomas.

“The field is in urgent need of new methods to classify all forms of meningioma that not only predict how they will behave, but will ultimately help inform therapy,” says Dr. Zadeh.

To do this, the team developed an integrative approach that involved generating and combining genetic and epigenetic data from tumour samples from 121 patients. By integrating these different data types in a single analysis, they found that meningioma could classified into four molecular groups, which also generated new biological insight into how these tumours behave.

“In comparison to current classification systems, including the WHO grading criteria, the four molecular groups that we identified were more accurate in predicting clinical outcomes—particularly the time it took for cancer to return after treatment,” says Dr. Farshad Nassiri, the first author of the study.

The team took these results further and developed a test that can be used to classify tumours in a clinical setting. They were also able to uncover potential treatment options based on biological characteristics of the tumour.

“This work represents a pivotal step in redefining the current classification of meningiomas, which has changed very little in three decades,” says Dr. Zadeh. “Being able to classify tumours using molecular features that reflect their clinical behaviour will pave the path forward for deciding the best course of therapy for these patients.”

This work was supported by the Canadian Institutes of Health Research, the AANS/CNS Section on Tumors, the Neurosurgery Research & Education Foundation, Hold’em for Life, the Canadian Cancer Society, the Brain Tumour Charity U.K., the National Institutes of Health, the Mary Hunter Meningioma Program, The Princess Margaret Cancer Foundation and the UHN Foundation.

Nassiri F, Liu J, Patil V, Mamatjan Y, Wang JZ, Hugh-White R, Macklin AM, Khan S, Singh O, Karimi S, Corona RI, Liu LY, Chen CY, Chakravarthy A, Wei Q, Mehani B, Suppiah S, Gao A, Workewych AM, Tabatabai G, Boutros PC, Bader GD, de Carvalho DD, Kislinger T, Aldape K, Zadeh G. A clinically applicable integrative molecular classification of meningiomas. Nature. 2021 Sep;597(7874):119-125. doi: 10.1038/s41586-021-03850-3. 

(Left to right) Dr. Farshad Nassiri, Neurosurgery Resident and PhD candidate; Dr. Gelareh Zadeh, Senior Scientist at Princess Margaret Cancer Centre, Co-Director of the Krembil Brain Institute, and Head of the Division of Neurosurgery at Toronto Western Hospital.