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A predictive model for MGMT promoter methylation status in glioblastoma based on terahertz spectral data
Minghui Du1, Xianhao Wu2, Zhiyan Sun1
1Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Abstract:
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.
