Plasma metabolome profiling identifies metabolic subtypes of pancreatic ductal adenocarcinoma

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Ujjwal Mukund Mahajan - , Ludwig Maximilian University of Munich (Author)
  • Ahmed Alnatsha - , Ludwig Maximilian University of Munich (Author)
  • Qi Li - , Ludwig Maximilian University of Munich (Author)
  • Bettina Oehrle - , Ludwig Maximilian University of Munich (Author)
  • Frank Ulrich Weiss - , University of Greifswald (Author)
  • Matthias Sendler - , University of Greifswald (Author)
  • Marius Distler - , Department of Visceral, Thoracic and Vascular Surgery, National Center for Tumor Diseases Dresden, University Hospital Carl Gustav Carus Dresden (Author)
  • Waldemar Uhl - , Ruhr University Bochum (Author)
  • Tim Fahlbusch - , Ruhr University Bochum (Author)
  • Elisabetta Goni - , Ludwig Maximilian University of Munich (Author)
  • Georg Beyer - , Ludwig Maximilian University of Munich (Author)
  • Ansgar Chromik - , Asklepios Clinic Hamburg Nord-Heidberg (Author)
  • Markus Bahra - , Krankenhaus Waldfriede (Author)
  • Fritz Klein - , Charité – Universitätsmedizin Berlin (Author)
  • Christian Pilarsky - , Friedrich-Alexander University Erlangen-Nürnberg (Author)
  • Robert Grützmann - , Friedrich-Alexander University Erlangen-Nürnberg (Author)
  • Markus M. Lerch - , Ludwig Maximilian University of Munich (Author)
  • Kirsten Lauber - , Ludwig Maximilian University of Munich (Author)
  • Nicole Christiansen - , trinamiX GmbH (Author)
  • Beate Kamlage - , Metanomics-Health GmbH (Author)
  • Ivonne Regel - , Ludwig Maximilian University of Munich (Author)
  • Julia Mayerle - , Ludwig Maximilian University of Munich, University of Greifswald (Author)

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Developing biomarkers for early detection and chemotherapeutic response prediction is crucial to improve the dismal prognosis of PDAC patients. However, molecular cancer signatures based on transcriptome analysis do not reflect intratumoral heterogeneity. To explore a more accurate stratification of PDAC phenotypes in an easily accessible matrix, plasma metabolome analysis using MxP® Global Profiling and MxP® Lipidomics was performed in 361 PDAC patients. We identified three metabolic PDAC subtypes associated with distinct complex lipid patterns. Subtype 1 was associated with reduced ceramide levels and a strong enrichment of triacylglycerols. Subtype 2 demonstrated increased abun-dance of ceramides, sphingomyelin and other complex sphingolipids, whereas subtype 3 showed decreased levels of sphingolipid metabolites in plasma. Pathway enrichment analysis revealed that sphingolipid-related pathways differ most among subtypes. Weighted correlation network analysis (WGCNA) implied PDAC subtypes differed in their metabolic programs. Interestingly, a reduced expression among related pathway genes in tumor tissue was associated with the lowest survival rate. However, our metabolic PDAC subtypes did not show any correlation to the described molecular PDAC subtypes. Our findings pave the way for further studies investigating sphingolipids metabolisms in PDAC.

Details

Original languageEnglish
Article number1821
JournalCells
Volume10
Issue number7
Publication statusPublished - Jul 2021
Peer-reviewedYes

External IDs

PubMed 34359990

Keywords

Sustainable Development Goals

ASJC Scopus subject areas

Keywords

  • Complex lipids, Metabolic subtypes, Pancreatic ductal adenocarcinoma, Sphingolipids