The next generation of glioma biomarkers: MGMT methylation, BRAF fusions and IDH1 mutations

For some, glioma biomarkers have been expected to solve common diagnostic problems in routine neuropathology service caused by insufficient material, technical shortcomings or lack of experience. Further, biomarkers should predict patient outcome and direct optimal therapy for the individual patient...

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Hauptverfasser: Deimling, Andreas von (VerfasserIn) , Korshunov, Andrey (VerfasserIn) , Hartmann, Christian (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 2011
In: Brain pathology
Year: 2011, Jahrgang: 21, Heft: 1, Pages: 74-87
ISSN:1750-3639
DOI:10.1111/j.1750-3639.2010.00454.x
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1111/j.1750-3639.2010.00454.x
Verlag, lizenzpflichtig, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1750-3639.2010.00454.x
Volltext
Verfasserangaben:Andreas von Deimling; Andrey Korshunov; Christian Hartmann
Beschreibung
Zusammenfassung:For some, glioma biomarkers have been expected to solve common diagnostic problems in routine neuropathology service caused by insufficient material, technical shortcomings or lack of experience. Further, biomarkers should predict patient outcome and direct optimal therapy for the individual patient. Unfortunately, current biomarkers still fall somewhat short of these grand expectations. While there has been some progress, it has generally been slow and in small steps. In this review, the newest set of glioma biomarkers: O6-methylguanine-DNA methyltransferase (MGMT) methylation, BRAF fusion and IDH1 mutation are discussed. MGMT methylation is well established as a prognostic/predictive marker for glioblastoma; however, technical questions regarding testing remain, it is not currently utilized widely in guiding patient management, and it has proven to be of no assistance in diagnostics. In contrast, BRAF fusion and IDH1 mutation analyses promise to be very helpful for classifying and grading gliomas, while their potential predictive value has yet to be established.
Beschreibung:Erstmals veröffentlicht: 03 December 2010
Gesehen am 28.10.2022
Beschreibung:Online Resource
ISSN:1750-3639
DOI:10.1111/j.1750-3639.2010.00454.x