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Updated: Aug 24, 2026

Advancements in the Metabolic Profiling of Three-Dimensional Brain Tumor Spheroids for Drug Screening
Published on: September 5, 2025
Label-Free SERS Analysis of Glioma Cells to Detect Drug Resistance Using Metabolic Phenylalanine Level
Guohui Yang1, Xin Wang2, Jingbin Jin1
1China-Japan Union Hospital of Jilin University, Changchun 130033, PR China.
Abstract:
Glioma is one of the most common malignant brain tumors, and its mainstream clinical treatment regimens mainly include postoperative combined with Temozolomide chemotherapy. Unfortunately, glioma cells tend to mutate when subjected to prolonged Temozolomide treatment, leading to drug resistance and significantly weakening the therapeutic effect. Delaying the resistance time of Temozolomide has become a pressing issue for clinicians to address, and the primary regimen for delaying drug resistance is the combined application of Temozolomide with other therapies. To explore new molecular diagnostic markers of drug resistance in glioma and to assess treatment stage, surface-enhanced Raman spectroscopy (SERS) was used to investigate changes in glioma cells under combined therapies including physical (electrical stimulation, ES) and chemical (cancer drug: Temozolomide) treatments. By analyzing intensity changes in the SERS band at 997 cm-1, we observed that glioma cells showed a higher phenylalanine (Phe) expression. Interestingly, dynamic variations in Phe content secreted from glioma cells were drug resistance-dependent. ES, a novel therapeutic technique that can inhibit cell proliferation by promoting glioma cell apoptosis, was combined with Temozolomide. In both simple ES and ES plus Temozolomide conditions, metabolic Phe levels in glioma cells are significantly elevated, suggesting that Phe overexpression in glioma cells can serve as a potential indicator for accelerated cancer cell apoptosis. Our study proves that ES can effectively reduce Temozolomide doses, offering an easy-to-implement approach to delaying the onset of drug resistance. This work not only reveals a possible antidrug-resistance treatment strategy for glioma but also provides important guidance on a potential spectral indicator for early diagnosis of drug resistance, which is of significance for clinical applications.
