A predictive model for MGMT promoter methylation status in glioblastoma based on terahertz spectral data

被引：0

作者：

Du, Minghui ^{[1
,2
]}

Wu, Xianhao ^{[3
]}

Sun, Zhiyan ^{[1
,2
]}

Tao, Rui ^{[1
,2
]}

Sun, Peiyuan ^{[1
,2
]}

Zheng, Shaowen ^{[3
]}

Zhang, Zhaohui ^{[3
,5
]}

Zhang, Tianyao ^{[3
]}

Zhao, Xiaoyan ^{[3
,4
]}

Yang, Pei ^{[1
,2
]}

机构：

[1] Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, Beijing, Peoples R China

[2] Capital Med Univ, Beijing Neurosurg Inst, Beijing, Peoples R China

[3] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing, Peoples R China

[4] Univ Sci & Technol Beijing, Beijing Engn Res Ctr Ind Spectrum Imaging, Sch Automat & Elect Engn, Beijing, Peoples R China

[5] Univ Sci & Technol Beijing, Shunde Innovat Sch, Foshan, Peoples R China

来源：

ANALYTICAL BIOCHEMISTRY | 2025年 / 702卷

关键词：

Terahertz; Glioblastoma; MGMT; Predictive modeling; CENTRAL-NERVOUS-SYSTEM; BIOMEDICAL APPLICATIONS; TEMOZOLOMIDE; GLIOMAS;

D O I：

10.1016/j.ab.2025.115850

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is a crucial biomarker in glioblastoma (GBM) that influences response to temozolomide. Traditional detection methods, such as gene sequencing, are time-consuming and limited to postoperative analysis. This study explores the use of terahertz time-domain spectroscopy (THz-TDS) combined with machine learning to predict MGMT methylation status intraoperatively. By analyzing 180 GBM tissue samples, a Random Forest model was developed, achieving an AUC of 0.862. The findings suggest that THz spectroscopy offers a rapid, intraoperative alternative to traditional MGMT methylation detection methods, potentially enhancing surgical decision-making and personalized treatment strategies in GBM.

引用

页数：8

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