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分子分类以细化脑膜瘤的手术和放射治疗决策。

Molecular classification to refine surgical and radiotherapeutic decision-making in meningioma.

机构信息

MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.

Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.

出版信息

Nat Med. 2024 Nov;30(11):3173-3183. doi: 10.1038/s41591-024-03167-4. Epub 2024 Aug 21.

DOI:10.1038/s41591-024-03167-4
PMID:39169220
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11564112/
Abstract

Treatment of the tumor and dural margin with surgery and sometimes radiation are cornerstones of therapy for meningioma. Molecular classifications have provided insights into the biology of disease; however, response to treatment remains heterogeneous. In this study, we used retrospective data on 2,824 meningiomas, including molecular data on 1,686 tumors and 100 prospective meningiomas, from the RTOG-0539 phase 2 trial to define molecular biomarkers of treatment response. Using propensity score matching, we found that gross tumor 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). Molecular group classification predicted response to radiotherapy, including in the RTOG-0539 cohort. We subsequently developed a molecular model to predict response to radiotherapy that discriminates outcome better than standard-of-care classification. This study highlights the potential for molecular profiling to refine surgical and radiotherapy decision-making.

摘要

手术治疗肿瘤和硬脑膜边缘,有时辅以放疗,是脑膜瘤治疗的基石。分子分类为疾病生物学提供了新的认识;然而,治疗反应仍然存在异质性。在这项研究中,我们使用了 RTOG-0539 二期试验中 2824 例脑膜瘤的回顾性数据,包括 1686 例肿瘤和 100 例前瞻性脑膜瘤的分子数据,以确定治疗反应的分子生物标志物。通过倾向评分匹配,我们发现全切除肿瘤与所有分子亚组的无进展生存期(PFS)延长相关,并且在增殖性脑膜瘤中与总生存期延长相关。硬脑膜边缘治疗(Simpson 分级 1/2)与未治疗(Simpson 分级 3)相比,可延长 PFS。分子亚组分类预测了放疗反应,包括在 RTOG-0539 队列中。我们随后开发了一种分子模型来预测放疗反应,该模型比标准治疗分类更能区分预后。这项研究强调了分子分析在改进手术和放疗决策方面的潜力。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbba/11564112/19a539d3adf2/41591_2024_3167_Fig8_ESM.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbba/11564112/5886bc79f868/41591_2024_3167_Fig9_ESM.jpg
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