Malignant Transformation of a Dysembryoplastic Neuroepithelial Tumor (DNET) Characterized by Genome-Wide Methylation Analysis. Issue 4 (April 2016)

• Record Type: Journal Article
• Authors: Heiland, Dieter Henrik; Staszewski, Ori; Hirsch, Martin; Masalha, Waseem; Franco, Pamela; Grauvogel, Jürgen; Capper, David; Schrimpf, Daniel; Urbach, Horst; Weyerbrock, Astrid
• Is Part Of: Journal of neuropathology and experimental neurology. Volume 75:Issue 4(2016)
• Publication Date: 2016-04
• Subjects: Copy number changes -- Dysembryoplastic neuroepithelial tumor (DNET) -- Epigenetic alteration -- Illumina 450 K beadchip methylation array -- Malignant DNET -- Methylation.; Neurology -- Diseases -- Periodicals; Neurology -- Diseases -- Physiopathology -- Periodicals; 616.8047
• DOI: 10.1093/jnen/nlw007
• Languages: English
• ISSNs: 0022-3069

Abstract

Abstract : Dysembryoplastic neuroepithelial tumors (DNET) are considered to be rare, benign, and associated with chronic epilepsy. We present the case of a 28-year-old man with a history of epilepsy since age 12. Surgery of an occipital cortical lesion in 2009 revealed a DNET. Five years later, a recurrent tumor at the edge of the resection cavity was removed, and the tissue underwent an intensive diagnostic workup. The first tumor was unequivocally characterized as a DNET, but neuropathological diagnostics of the recurrent tumor revealed a glioblastoma. After 6 months, another recurrent tumor was detected next to the location of the original tumor, and this was also resected. An Illumina 450 K beadchip methylation array was performed to characterize all of the tumors. The methylation profile of these tumors significantly differed from other glioblastoma and epilepsy-associated tumor profiles and revealed a DNET-like methylation profile. Thus, molecular characterization of these recurrent tumors suggests malignant transformation of a previously benign DNET. We found increased copy number changes in the recurrent DNET tumors after malignant transformation. Modern high-throughput analysis adds essential molecular information in addition to standard histopathology for proper identification of rare brain tumors that present with an unusual clinical course.