ReviewJournal of personalized medicine2026
Targeted and Personalized Therapy for Difficult Benign Brain Tumors: A Review.
Review in Journal of personalized medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
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Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDifficult benign intracranial tumors (including meningiomas, schwannomas, neurofibromatosis-related tumors, and pituitary neuroendocrine tumors) have substantial morbidity in patients. Due to their limited treatment options, there is a need for individualized treatment beyond histological and surgical approaches.
objectiveTo summarize how novel treatment innovations have been implemented for these tumors, meningiomas and schwannomas are prioritized, followed by NF-associated neoplasms, and then pituitary neuroendocrine tumors in comparison to low-grade gliomas.
methodsWe summarize the current knowledge relating to targeted therapies for gliomas, meningiomas, schwannomas, neurofibromatosis (NF) tumors, and pituitary neuroendocrine tumors to investigate an individual's treatment options for difficult benign brain tumors. This review synthesizes evidence on tumor genomics and molecular markers, supported by methylation-based classification, immunohistochemistry, and functional assays, emphasizing current clinical applications. EVIDENCE SYNTHESIS: The recent data show that DNA methylation-based models can predict post-surgical outcomes and radiotherapy responses, enabling risk stratification and radiotherapy benefit prediction. Early signals support target-directed treatment, including cMET blockade that radiosensitizes NF2 schwannoma models, brigatinib-associated tumor shrinkage in NF2-deficient models, and PitNET organoid data.
conclusionsWe support clinical decision-making that utilizes molecular profiling with functional testing to guide targeted treatment. We also identify evidence gaps such as biomarker-defined prospective trials that are needed for broader clinical implementation.
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