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Hierarchically Engineered Self-Adaptive Nanoplatform Guided Intuitive and Precision Interventions for Deep-Seated
Wei Cheng1,2, Haijing Qu1,2, Jiaojiao Yang2
1Shanghai Frontiers Science Center of Drug Target Identification and Delivery, School of Pharmaceutical Sciences, Shanghai Jiao Tong University, Shanghai 200240, China.
ACS Nano
|January 4, 2025
Summary
A novel self-adaptive nanoplatform (SAN) and guided intervention strategy (SGIPi) effectively treat glioblastoma multiforme (GBM). This approach overcomes delivery challenges and enhances chemotherapy for improved patient survival.
Area of Science:
- Biomedical Engineering
- Nanotechnology
- Oncology
Background:
- Glioblastoma multiforme (GBM) presents significant treatment challenges, especially for deep-seated tumors, due to biological barriers and risks to healthy brain tissue.
- Current interventions often require sophisticated equipment and skilled operations, limiting accessibility.
Purpose of the Study:
- To develop a self-adaptive nanoplatform (SAN) to overcome GBM delivery barriers by dynamically adjusting its properties.
- To introduce a guided intuitive and precision intervention (SGIPi) strategy for GBM treatment, simplifying current complex methods.
Main Methods:
- Hierarchical engineering of a self-adaptive nanoplatform (SAN) with dynamic structural, charge, size, and targeting adjustments.
- Development of the SGIPi strategy for GBM intervention, obviating the need for advanced facilities and real-time MRI guidance.
Main Results:
- SGIPi-based photodynamic therapy demonstrated high tumor specificity and significantly extended survival in a preclinical GBM model.
- The SGIPi strategy potentiated chemotherapy, eradicating intracranial GBM lesions in 100% of cases with Temozolomide alone and minimizing adverse effects.
Conclusions:
- The SGIPi strategy offers a promising, simpler approach to GBM clinical management, potentially improving survival and achieving complete remission.
- This research shifts focus towards delivery-based interventions, moving away from complex hardware development for GBM treatment.
