医学
生物标志物
脑膜瘤
危险系数
肿瘤科
放射治疗
内科学
队列
置信区间
基因表达谱
临床试验
生物信息学
病理
基因表达
基因
生物
生物化学
作者
William Chen,Abrar Choudhury,Mark W. Youngblood,Mei‐Yin C. Polley,Calixto‐Hope G. Lucas,Kanish Mirchia,Sybren L. N. Maas,Abigail K. Suwala,Minhee Won,James C. Bayley,Akdes Serin Harmancı,Arif O. Harmanci,Tiemo J. Klisch,Minh Nguyen,Harish N. Vasudevan,Kathleen McCortney,Theresa Yu,Varun Bhave,Tai‐Chung Lam,Jenny Kan-Suen Pu
出处
期刊:Nature Medicine
[Nature Portfolio]
日期:2023-11-09
卷期号:29 (12): 3067-3076
被引量:58
标识
DOI:10.1038/s41591-023-02586-z
摘要
Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems tested (N = 9) in the clinical validation cohort for local recurrence (5-year area under the curve (AUC) 0.81) and overall survival (5-year AUC 0.80). The increase in AUC compared with the standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval 0.07 to 0.17, P < 0.001). The gene expression biomarker identified meningiomas benefiting from postoperative radiotherapy (hazard ratio 0.54, 95% confidence interval 0.37 to 0.78, P = 0.0001) and suggested postoperative management could be refined for 29.8% of patients. In sum, our results identify a targeted gene expression biomarker that improves discrimination of meningioma outcomes, including prediction of postoperative radiotherapy responses. A risk score based on a 34-gene signature for outcome prediction in meningioma was developed and validated in large multi-institutional cohorts and showed better performance in discriminating postoperative menignioma outcomes compared with existing meningioma classification systems.
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