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Impact of post-surgical freezing delay on brain tumor metabolomics

Introduction: Translational cancer research has seen an increasing interest in metabolomic profiling to decipher tumor phenotypes. However, the impact of post-surgical freezing delays on mass spectrometric metabolomic measurements of the cancer tissue remains elusive. Objectives: To evaluate the imp...

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Main Authors: Mock, Andreas (Author) , Rapp, Carmen (Author) , Warta, Rolf (Author) , Abdollahi, Amir (Author) , Jäger, Dirk (Author) , Sakowitz, Oliver (Author) , Brors, Benedikt (Author) , Deimling, Andreas von (Author) , Jungk, Christine (Author) , Unterberg, Andreas (Author) , Herold-Mende, Christel (Author)
Format: Article (Journal)
Language:English
Published: 13 May 2019
In: Metabolomics
Year: 2019, Volume: 15, Issue: 5
ISSN:1573-3890
DOI:10.1007/s11306-019-1541-2
Online Access:Verlag, Pay-per-use, Volltext: https://doi.org/10.1007/s11306-019-1541-2
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Author Notes:Andreas Mock, Carmen Rapp, Rolf Warta, Amir Abdollahi, Dirk Jäger, Oliver Sakowitz, Benedikt Brors, Andreas von Deimling, Christine Jungk, Andreas Unterberg, Christel Herold-Mende
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Summary:Introduction: Translational cancer research has seen an increasing interest in metabolomic profiling to decipher tumor phenotypes. However, the impact of post-surgical freezing delays on mass spectrometric metabolomic measurements of the cancer tissue remains elusive. Objectives: To evaluate the impact of post-surgical freezing delays on cancer tissue metabolomics and to investigate changes per metabolite and per metabolic pathway. Methods: We performed untargeted metabolomics on three cortically located and bulk-resected glioblastoma tissues that were sequentially frozen as duplicates at up to six different time delays (0-180 min, 34 samples). Results: Statistical modelling revealed that 10% of the metabolome (59 of 597 metabolites) changed significantly after a 3 h delay. While carbohydrates and energy metabolites decreased, peptides and lipids increased. After a 2 h delay, these metabolites had changed by as much as 50-100%. We present the first list of metabolites in glioblastoma tissues that are sensitive to post-surgical freezing delays and offer the opportunity to define individualized fold change thresholds for future comparative metabolomic studies. Conclusion: More researchers should take these pre-analytical factors into consideration when analyzing metabolomic data. We present a strategy for how to work with metabolites that are sensitive to freezing delays.
Item Description:Gesehen am 16.09.2019
Physical Description:Online Resource
ISSN:1573-3890
DOI:10.1007/s11306-019-1541-2

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