Perspectives of Biophysical Therapies in Glioblastoma.

Abstract

Despite intensive multimodal treatment, outcomes in glioblastoma remain poor, with median overall survival typically limited to 14-18 months and only 5-10% of patients surviving beyond five years. These limitations have fueled interest in biophysical, device-based strategies that apply electric, magnetic, acoustic, optical, or thermal energy to modulate tumor biology and the immune microenvironment, while also enhancing systemic therapies. This review summarizes current concepts and evidence for major biophysical modalities in glioblastoma, emphasizing mechanistic rationale, translational maturity, and implications for trial design. Besides radiotherapy, Tumor Treating Fields (TTFields) therapy is the only noninvasive biophysical modality currently integrated into routine clinical practice, supported by randomized phase III survival data in newly diagnosed disease. Other modalities are at earlier stages of translation, including oscillating magnetic field (OMF) concepts targeting metabolic and oxidative-stress vulnerabilities; ultrasound-based platforms for reversible and focused blood-brain barrier (BBB) modulation, sonodynamic approaches, and focal ablation; photodynamic therapy combining photosensitizers with spatially controlled light activation; and thermal strategies such as laser interstitial thermal therapy and magnetic nanoparticle-mediated hyperthermia. Across modalities, key unresolved issues include parameter standardization and dosimetry, patient selection, interactions with chemoradiation and corticosteroids, feasibility and adherence in real-world settings, and the scarcity of controlled trials with clinically meaningful endpoints. Overall, biophysical therapies are best conceived as adjunctive tools within multimodal glioblastoma management rather than stand-alone solutions. Their integration into clinical practice should proceed cautiously, accompanied by an iterative cycle of translation and reverse translation, with a strong focus on predictive biomarker-driven, mechanistically informed trial designs.