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Pediatric low-grade gliomas: how modern biology reshapes the clinical field
Guillaume Bergthold1, Pratiti Bandopadhayay2, Wenya Linda Bi1
1Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
Abstract:
Low-grade gliomas represent the most frequent brain tumors arising during childhood. They are characterized by a broad and heterogeneous group of tumors that are currently classified by the WHO according to their morphological appearance. Here we review the clinical features of these tumors, current therapeutic strategies and the recent discovery of genomic alterations characteristic to these tumors. We further explore how these recent biological findings stand to transform the treatment for these tumors and impact the diagnostic criteria for pediatric low-grade gliomas.
Insights
Pediatric low-grade gliomas are common childhood brain tumors. Recent genomic discoveries are revolutionizing their diagnosis and treatment, moving beyond traditional morphology-based classification.
Area of Science:
- Pediatric neuro-oncology
- Cancer genomics
- Tumor classification
Background:
- Low-grade gliomas are the most common pediatric brain tumors.
- Current classification relies on WHO morphological criteria.
- Tumor heterogeneity presents diagnostic and therapeutic challenges.
Purpose of the Study:
- To review clinical features of pediatric low-grade gliomas.
- To summarize current therapeutic strategies.
- To explore the impact of recent genomic discoveries on diagnosis and treatment.
Main Methods:
- Literature review of clinical features.
- Analysis of current therapeutic approaches.
- Synthesis of recent findings on genomic alterations.
Main Results:
- Genomic alterations are characteristic of specific low-grade glioma subtypes.
- These discoveries offer new avenues for targeted therapies.
- Understanding molecular drivers is crucial for improved patient outcomes.
Conclusions:
- Genomic insights are transforming the understanding and management of pediatric low-grade gliomas.
- Future diagnostic criteria will likely incorporate molecular data.
- Personalized treatment strategies based on tumor genomics are emerging.
