Authors
Bida Joshua John, Dauda Maibasha, Ratnakar Shukla, Adil Husain, Afza Ahmad, Shambhavi Kumari, Vidhi Arora, Gungun Sherawat, Rohit Kumar Tiwari
Published in
CNS & neurological disorders drug targets. Sep 17, 2026. Epub Sep 17, 2026.
Abstract
Glioblastoma (GB) is a highly aggressive tumor that demonstrates significant treatment resistance due to the blood-brain barrier (BBB) and resistance mechanisms of the tumor. Nanoparticle- based drug delivery systems (NDDS) can enhance drug bioavailability, enable targeted delivery, and provide controlled release. These nanoparticles can be engineered to target GB-specific biomarkers, such as EGFRvIII, which is expressed on glioma stem cells, to enhance treatment precision. A comprehensive literature review was conducted using the keywords "Glioblastoma," "Nanoparticles," "Pathogenesis," and "Treatment Resistance" across PubMed, MEDLINE, Web of Science, ClinicalTrial. gov, Science Direct, and Google Scholar databases. Engineered nanoparticles have considerable potential to overcome major therapeutic obstacles in GB. Techniques such as surface functionalization (e.g., with cRGD or transferrin) and biomimetic coatings enable nanoparticles to cross the BBB, significantly increasing drug accumulation within brain tumors by up to 12-fold. This leads to improved anti-tumor efficacy, demonstrating significant reductions in tumor burden and improved survival in animal models. Additionally, these platforms are used to deliver genetic therapies, such as siRNA and miRNA, to specific cancer-driving genes. The ability to deliver drugs intranasally further enhances the therapeutic potential. Nanoparticle-based therapies have emerged as a promising approach in the treatment of GB and have successfully overcome barriers such as the BBB and treatment resistance. These methods have demonstrated robust preclinical outcomes, which emphasize their potential for clinical translation. Ongoing research is important to maximize the potential of these technologies and improve survival rates for patients with GB.
PMID:
42770366
Bibliographic data and abstract were imported from PubMed on 22 Sep 2026.
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