Related Experiment Video
Updated: Jun 26, 2026
Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids
Published on: June 8, 2019
[Current Status of Genetic/Molecular Abnormality Analysis and Prognosis Prediction of Meningioma]
1Department of Neurosurgery, Tokyo Metropolitan Police Hospital.
Abstract:
Biological molecular studies of meningiomas have also developed with the development of molecular biological methods. In 2013, Clark et al. reported that driver genetic mutations other than NF2, including TRAF7, KLF4, AKT1, and SMO, were associated with meningioma development. In 2017, Sahm et al. proposed a classification of meningiomas based on global methylation status, which was more accurate in predicting prognosis than conventional WHO grading. In 2022, based on this classification, various groups reported an integrated classification that comprehensively included some biological molecular abnormalities, such as DNA mutations, copy number alterations, and RNA sequences. This field is expected to elucidate the mechanism of meningioma development and further research is expected to lead to the development of effective molecularly targeted therapeutics and biomarkers of radiosensitivity in the future. In this article, we summarize the current status and prospects of these biological molecular studies.
Insights
Recent advances in molecular biology have identified key genetic mutations and methylation patterns in meningiomas. This research aims to improve prognosis prediction and develop targeted therapies for this brain tumor.
Area of Science:
- Neuro-oncology
- Genetics
- Molecular Biology
Background:
- Meningiomas are tumors arising from the meninges.
- Traditional classification relies on World Health Organization (WHO) grading.
- Molecular biological methods have advanced the study of meningiomas.
Purpose of the Study:
- To summarize the current status of biological molecular studies in meningiomas.
- To discuss the prospects of these studies for understanding tumor development.
- To highlight potential for developing targeted therapeutics and biomarkers.
Main Methods:
- Review of key publications on meningioma molecular biology.
- Analysis of genetic mutations (e.g., NF2, TRAF7, KLF4, AKT1, SMO).
- Examination of methylation profiling for prognostic classification.
- Integration of multi-omic data (DNA mutations, copy number alterations, RNA sequences).
Main Results:
- Identification of driver genetic mutations beyond NF2.
- Development of methylation-based classification for improved prognosis prediction.
- Emergence of integrated classifications incorporating multi-omic data.
Conclusions:
- Molecular profiling is crucial for understanding meningioma pathogenesis.
- Advanced classifications offer better prognostic accuracy than conventional grading.
- Future research holds promise for targeted therapies and radiosensitivity biomarkers.
