Response-Predictive Gene Expression Profiling of Glioma Progenitor Cells In Vitro

Moeckel, Sylvia and Meyer, Katharina and Leukel, Petra and Heudorfer, Fabian and Seliger, Corinna and Stangl, Christina and Bogdahn, Ulrich and Proescholdt, Martin and Brawanski, Alexander and Vollmann-Zwerenz, Arabel and Riemenschneider, Markus J. and Bosserhoff, Anja-Katrin and Spang, Rainer and Hau, Peter (2014) Response-Predictive Gene Expression Profiling of Glioma Progenitor Cells In Vitro. PLOS ONE, 9 (9): e108632. ISSN 1932-6203,

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Abstract

Background: High-grade gliomas are amongst the most deadly human tumors. Treatment results are disappointing. Still, in several trials around 20% of patients respond to therapy. To date, diagnostic strategies to identify patients that will profit from a specific therapy do not exist. Methods: In this study, we used serum-free short-term treated in vitro cell cultures to predict treatment response in vitro. This approach allowed us (a) to enrich specimens for brain tumor initiating cells and (b) to confront cells with a therapeutic agent before expression profiling. Results: As a proof of principle we analyzed gene expression in 18 short-term serum-free cultures of high-grade gliomas enhanced for brain tumor initiating cells (BTIC) before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated progenitor cells allowed to predict therapy-induced impairment of proliferation in vitro. Conclusion: For the tyrosine kinase inhibitor Sunitinib used in this dataset, the approach revealed additional predictive information in comparison to the evaluation of classical signaling analysis.

Item Type: Article
Uncontrolled Keywords: ENDOTHELIAL GROWTH-FACTOR; STEM-CELLS; TUMOR-CELLS; SUNITINIB; CANCER; RECEPTORS; MIGRATION; IDENTIFICATION; RESISTANCE; PATTERN;
Subjects: 600 Technology > 610 Medical sciences Medicine
Divisions: Medicine > Lehrstuhl für Neurochirurgie
Medicine > Lehrstuhl für Neurologie
Medicine > Lehrstuhl für Pathologie
Medicine > Zentren des Universitätsklinikums Regensburg > Zentrum für Hirntumore (ZHT)
Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Statistische Bioinformatik (Prof. Spang)
Depositing User: Dr. Gernot Deinzer
Date Deposited: 13 Aug 2019 11:26
Last Modified: 13 Aug 2019 11:29
URI: https://pred.uni-regensburg.de/id/eprint/9523

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