Title |
An integrated genomic analysis of anaplastic meningioma identifies prognostic molecular signatures
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Published in |
Scientific Reports, September 2018
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DOI | 10.1038/s41598-018-31659-0 |
Pubmed ID | |
Authors |
Grace Collord, Patrick Tarpey, Natalja Kurbatova, Inigo Martincorena, Sebastian Moran, Manuel Castro, Tibor Nagy, Graham Bignell, Francesco Maura, Matthew D. Young, Jorge Berna, Jose M. C. Tubio, Chris E. McMurran, Adam M. H. Young, Mathijs Sanders, Imran Noorani, Stephen J. Price, Colin Watts, Elke Leipnitz, Matthias Kirsch, Gabriele Schackert, Danita Pearson, Abel Devadass, Zvi Ram, V. Peter Collins, Kieren Allinson, Michael D. Jenkinson, Rasheed Zakaria, Khaja Syed, C. Oliver Hanemann, Jemma Dunn, Michael W. McDermott, Ramez W. Kirollos, George S. Vassiliou, Manel Esteller, Sam Behjati, Alvis Brazma, Thomas Santarius, Ultan McDermott |
Abstract |
Anaplastic meningioma is a rare and aggressive brain tumor characterised by intractable recurrences and dismal outcomes. Here, we present an integrated analysis of the whole genome, transcriptome and methylation profiles of primary and recurrent anaplastic meningioma. A key finding was the delineation of distinct molecular subgroups that were associated with diametrically opposed survival outcomes. Relative to lower grade meningiomas, anaplastic tumors harbored frequent driver mutations in SWI/SNF complex genes, which were confined to the poor prognosis subgroup. Aggressive disease was further characterised by transcriptional evidence of increased PRC2 activity, stemness and epithelial-to-mesenchymal transition. Our analyses discern biologically distinct variants of anaplastic meningioma with prognostic and therapeutic significance. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 3 | 27% |
United States | 2 | 18% |
Unknown | 6 | 55% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 11 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 57 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 19% |
Student > Bachelor | 6 | 11% |
Student > Master | 6 | 11% |
Researcher | 5 | 9% |
Other | 4 | 7% |
Other | 7 | 12% |
Unknown | 18 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 12 | 21% |
Biochemistry, Genetics and Molecular Biology | 8 | 14% |
Agricultural and Biological Sciences | 3 | 5% |
Unspecified | 1 | 2% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
Other | 7 | 12% |
Unknown | 25 | 44% |