In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 74, No. 19_Supplement ( 2014-10-01), p. 5341-5341
Abstract:
Glioblastoma multiforme (GBM) is the most prevalent malignant primary brain tumor in adults. GBM is classified as primary if it is assumed to have arisen de novo or as secondary if it progressed from lower grade astrocytoma. Previous studies have found that primary and secondary GBMs have distinct molecular and mutational profiles. Both have a grim prognosis with survival times of about a year with therapy. Although much progress in delineating the temporal order of mutations and copy number aberrations in the progression of lower grade gliomas was made in the past years, none of the studies have actively followed individual tumors through their progression. Whereas this method can detect aberrations that are prevalent in gliomas, it can miss events that are important in a subset of gliomas or are necessary for progression. The GlioMath-DD consortium is an interdisciplinary collaboration of several groups at the Technische Universität Dresden (TU-Dresden) aiming to study the progression of gliomas and to come up with a mathematical model for gliomagenesis. The work involves analyzing pairs of gliomas obtained from patients who had presented with a low grade glioma and who later had a recurrence of a higher grade glioma. All tumors were checked by pathologists and then high quality DNA and RNA material extracted and used for analysis. The tumors are analyzed for copy number variations (CNV) by array comparative genome hybridization (aCGH), while gene expression changes and small mutations are analyzed using high-throughput sequencing (RNA- and Exome-seq). The data gleaned from these experiments and from in vitro models of cell growth and spheroid formation will be used by bioinformaticians and mathematicians to infer key signaling networks and formulate a mathematical model of glioma progression. The ultimate aim of this work that spans two and a half years is to create a comprehensive model of glioma promotion and progression. Furthermore, it will pinpoint driver mutations and aberrations that contribute to this progression and eventually isolate biomarkers for diagnosis and therapy. During the conference, we will present preliminary genetic data of our ongoing study. Acknowledgements: The GlioMath-DD project (coordinator: Andreas Deutsch; SAB-Number 100098214) is funded by the European Social Fund (ESF) and the Free State of Saxony Citation Format: Evelin Schröck, Khalil Abou-El-Ardat, Ralf Wiedemuth, Michael Seifert, Alvaro Köhn-Luque, Mirjam Ingargiola, Kristin Stirnnagel, Alexander Krüger, Wolfgang Nagel, Kathrin Geiger, Andreas Beyer, Leoni A. Kunz-Schughart, Gabriele Schackert, Achim Temme, Barbara Klink, Andreas Deutsch. GlioMath-DD: A multidisciplinary approach to study glioma evolution and identify targets for individualized therapies. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5341. doi:10.1158/1538-7445.AM2014-5341
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2014-5341
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2014
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
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