Researchers leveraged the largest meningioma cohort to date with multiplatform molecular, treatment and 20-year outcome data in addition to samples from a prospective phase II RTOG-0539 study to identify molecular predictors of treatment response in meningiomas. They used propensity score matching to mimic a randomised trial design to characterise the benefits of differential degrees of tumour resection and dural margin treatment across different molecular classifications, in addition to identifying a group of molecularly defined radiotherapy-resistant meningiomas.
The findings have the potential to meaningfully impact clinical decision-making and treatment selection for patients in molecular era of meningioma management according to Drs. Farshad Nassiri, Gelareh Zadeh of the Princess Margaret Cancer Centre, University Health Network and University of Toronto in Toronto, Ontario, Canada, and colleagues, who published the findings on 21 August 2024 in the Nature Medicine.
Meningiomas are the most common primary intracranial tumour in adults. Contemporary studies have challenged the benefit of aggressive surgical strategies, including dural resection in every case, particularly if it places critical neurovascular structures at risk. Radiotherapy is the alternative treatment for these tumours, generally reserved as adjuvant therapy for aggressive, recurrent, or incompletely resected meningiomas. However, rates of tumour control after adjuvant radiotherapy are highly variable, creating a need to determine better predictors of response.
The authors wrote in the background that molecular classifications have provided insights into the biology of meningiomas; however, response to treatment remains heterogeneous. The role of treatment in the context of these molecular biomarkers has not been fully explored. Although ongoing randomised studies are examining the efficacy of radiotherapy in a subset of patients with meningioma, molecular features were not used for treatment stratification, as most were discovered after the inception of these studies.
The authors used a large cohort of clinically annotated, molecularly profiled meningiomas, including data from a prospective RTOG-0539 study in propensity score matching to determine the benefit of extent of resection and additive dural treatment (Simpson grade) in the context of molecular biomarkers, determine the capability of molecular classification to predict response to radiotherapy and create and validate molecular predictive models of response to radiotherapy using prospective clinical trial samples that are made publicly available to help inform radiotherapy treatment decisions.
In this study, the investigators used retrospective data on 2,824 meningiomas, including molecular data on 1,686 tumours and 100 prospective meningiomas from the RTOG-0539 phase II trial to define molecular biomarkers of treatment response. Using propensity score matching, they found that gross tumour resection was associated with longer progression-free survival (PFS) across all molecular groups and longer overall survival in proliferative meningiomas. Dural margin treatment (Simpson grade 1/2) prolonged PFS compared to no treatment (Simpson grade 3).
These results suggest that the dural origin and attachments of a meningioma need to be treated to optimally delay recurrence. Although most clinicians subscribe to the maximal resection of both the meningioma and its dural attachments, when possible, this had not been thoroughly investigated in a sufficiently large clinical cohort that included molecular data and the use of propensity score matching until now. The findings of this study revisit this historical dogma and provide rationale for a more nuanced consideration of addressing dural margins, particularly when it may be associated with higher surgical risk.
Molecular group classification predicted response to radiotherapy, including in the RTOG-0539 cohort. Molecular stratification of meningiomas provides predictive information beyond WHO grade when considering response to radiotherapy. The researchers subsequently developed a molecular model to predict response to radiotherapy that discriminates outcome better than standard-of-care classification.
The analyses suggest that adjuvant radiotherapy provides robust PFS benefits for immunogenic and NF2-wild-type meningiomas, including after incomplete resection, moderate benefit for hypermetabolic meningiomas but little-to-no benefit for aggressive, proliferative cases. These findings support the rationale for investigating radiotherapy results for meningiomas in the context of molecular classification and considering future molecular pathology informed clinical trials to investigate systemic treatments for radiotherapy-resistant meningiomas.
Although models using either DNA methylation or gene expression alone could outperform WHO grade in predicting response to radiotherapy, DNA methylation appeared to have better performance as a standalone platform, but a model combining both molecular modalities was optimal. These models also supported findings that radiotherapy-resistant meningiomas have a largely proliferative biology, enriched for cell cycle, and DNA-damage repair pathways with downregulation of apoptotic processes.
This project was funded in part with federal funds from the US National Cancer Institute, National Institutes of Health, under the Cancer Moonshot Initiative. Additional funding was provided by the Canadian Institutes of Health Research (CIHR) Project Fund, Brain Tumor Charity United Kingdom, the UHN Foundation, Mary Hunter Meningioma Research Fund, the V Foundation for Cancer Research, the CIHR Vanier Scholarship, the American Association of Neurological Surgeons Neurosurgery Education & Research Foundation Research Fellowship, the Congress of Neurological Surgeons Tumor Section and the Princess Margaret Hospital Foundation Hold ‘em For Life Oncology Fellowship.
Reference
Wang JZ, Patil V, Landry AP, et al. Molecular classification to refine surgical and radiotherapeutic decision-making in meningioma. Nature Medicine; Published online 21 August 2024. DOI: https://doi.org/10.1038/s41591-024-03167-4