Glioblastoma (GBM) remains the most aggressive adult brain tumor, with median survival largely unchanged over two decades. Antibody-based therapies have shown promise in hematologic and systemic cancers, but translation to GBM has been hindered by the tumor's hostile microenvironment and immune evasion mechanisms. A structured literature search was conducted in PubMed, Scopus, Web of Science, and ClinicalTrials.gov for studies published between 2010 and 2025. Eligible publications included preclinical investigations, clinical trials, and reviews addressing antibody-based therapies, tumor microenvironmental barriers, and computational innovations. Data were synthesized into thematic categories: mechanisms of resistance, antibody-based platforms, nanotechnology-assisted delivery, and artificial intelligence (AI)-driven strategies. Antibody therapeutics including monoclonal antibodies, antibody-drug conjugates, bispecific antibodies, and photoimmunotherapy show potential to enhance tumor targeting and immune activation. Key barriers such as the blood-brain barrier, immunosuppressive cell infiltration, and tumor heterogeneity significantly restrict efficacy. Novel approaches, including AI-enabled antibody design, digital twin modeling, and biomarker-driven patient stratification, offer opportunities to improve precision and overcome resistance. Combination strategies with radiotherapy, vaccines, or adoptive cell therapies further expand therapeutic potential. By reframing antibody therapy through the lens of barrier disarmament and technological integration, this review positions antibody-based approaches as realistic pillars of future GBM management. Strategic innovations in delivery, engineering, and computational modeling may transform antibodies from experimental tools into cornerstone therapies for this lethal malignancy.
Dababneh et al. (Thu,) studied this question.