Seq-ing answers: exploring meningioma biology utilizing bulk RNA-seq-based reference landscapes

Area of Science:

• Neuro-oncology
• Genomics
• Molecular Biology

Background:

• Meningiomas are the most common primary brain tumors, representing 40% of central nervous system neoplasms.
• Traditional histopathology-based grading systems have limitations in predicting meningioma aggressiveness and patient outcomes.
• There is a need for more accurate methods to classify meningiomas and predict recurrence.

Purpose of the Study:

• To evaluate the utility of modern molecular classification systems for meningiomas.
• To explore the role of transcriptomic profiling via bulk whole-genome RNA sequencing (RNA-seq) in understanding meningioma biology.
• To assess the potential of RNA-seq for predicting meningioma recurrence and informing personalized treatment.

Main Methods:

• Analysis of copy number alterations, DNA methylation, and gene expression.
• Application of transcriptomic profiling using bulk whole-genome RNA sequencing (RNA-seq).
• Development of dimension-reduced reference landscapes for sample projection.

Main Results:

• Modern molecular systems provide a more accurate framework for identifying distinct biological signatures and aggressive meningioma subtypes.
• RNA-seq offers insights into alternative splicing, gene expression, fusion events, non-coding RNAs, and pathway activity.
• Transcriptomic profiling aids in accurate prediction of meningioma recurrence.

Conclusions:

• Modern molecular classification and transcriptomic profiling significantly enhance the understanding of meningioma tumorigenesis.
• Bulk RNA-seq is a powerful tool for refining prognostic models and predicting recurrence in meningiomas.
• Increased accessibility of RNA-seq holds promise for personalized treatment strategies and improved patient outcomes in meningioma care.