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Molecular profiling predicts meningioma recurrence and reveals loss of DREAM complex repression in aggressive tumors.
- Source :
-
Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2019 Oct 22; Vol. 116 (43), pp. 21715-21726. Date of Electronic Publication: 2019 Oct 07. - Publication Year :
- 2019
-
Abstract
- Meningiomas account for one-third of all primary brain tumors. Although typically benign, about 20% of meningiomas are aggressive, and despite the rigor of the current histopathological classification system there remains considerable uncertainty in predicting tumor behavior. Here, we analyzed 160 tumors from all 3 World Health Organization (WHO) grades (I through III) using clinical, gene expression, and sequencing data. Unsupervised clustering analysis identified 3 molecular types (A, B, and C) that reliably predicted recurrence. These groups did not directly correlate with the WHO grading system, which classifies more than half of the tumors in the most aggressive molecular type as benign. Transcriptional and biochemical analyses revealed that aggressive meningiomas involve loss of the repressor function of the DREAM complex, which results in cell-cycle activation; only tumors in this category tend to recur after full resection. These findings should improve our ability to predict recurrence and develop targeted treatments for these clinically challenging tumors.<br />Competing Interests: Competing interest statement: S.E.P. is a member of the Scientific Advisory Board for Baylor Genetics.
- Subjects :
- Adult
Aged
Aged, 80 and over
Cell Cycle genetics
Cell Cycle physiology
Cell Line
DNA Copy Number Variations genetics
Disease Progression
Female
Gene Expression Profiling
Humans
Male
Meningeal Neoplasms pathology
Meningioma pathology
Middle Aged
Prognosis
Young Adult
Kv Channel-Interacting Proteins genetics
Meningeal Neoplasms genetics
Meningioma genetics
Neoplasm Recurrence, Local genetics
Repressor Proteins genetics
Subjects
Details
- Language :
- English
- ISSN :
- 1091-6490
- Volume :
- 116
- Issue :
- 43
- Database :
- MEDLINE
- Journal :
- Proceedings of the National Academy of Sciences of the United States of America
- Publication Type :
- Academic Journal
- Accession number :
- 31591222
- Full Text :
- https://doi.org/10.1073/pnas.1912858116