Andreas Mock1,2,3, Carmen Rapp1, Rolf Warta1, Amir Abdollahi4, Dirk Jäger2, Oliver Sakowitz1, Benedikt Brors5, Andreas von Deimling6, Christine Jungk1, Andreas Unterberg1, Christel Herold-Mende7. 1. Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany. 2. Department of Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg University Hospital, Heidelberg, Germany. 3. Department of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg, German Cancer Research Center (DKFZ), Heidelberg, Germany. 4. Molecular and Translational Radiation Oncology, National Center for Tumor Diseases (NCT), Heidelberg University Hospital and German Cancer Research Center (DKFZ), Heidelberg, Germany. 5. Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany. 6. Department of Neuropathology & Clinical Cooperation Unit Neuropathology, University Hospital Heidelberg, German Cancer Research Center (DKFZ), Heidelberg, Germany. 7. Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany. Christel.Herold-Mende@med.uni-heidelberg.de.
Abstract
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.
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.
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