Oral Presentation 22nd Annual Lorne Proteomics Symposium 2017

Finding cancer fats through integrated proteomics and lipidomics (#51)

Jeffrey Molendijk 1 , Thomas Stoll 1 , Federico Torta 2 , Markus Wenk 2 , Thomas P Hennessy 3 , Mark Hodson 4 , Michelle M Hill 1
  1. The University of Queensland Diamantina Institute, The University of Queensland, Translational Research Institute, Brisbane, QLD, Australia
  2. National University of Singapore, Singapore
  3. Agilent Technologies, Australia, Singapore
  4. Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Australia

Obesity, elevated cholesterol and triglyceride levels are associated with cancer progression and recurrence. However, the specific lipid metabolism pathways involved remain mostly unclear. We combined mass spectrometry-based lipidomics and proteomics in cell line models to determine lipid metabolism differences between oesophageal adenocarcinoma and its pre-malignant condition, Barrett’s oesophagus. Untargeted lipidomics in 5 cell lines (5 replicates each) measured 6843 features, of which 901 features with p-value <0.001 and fold change >2 were selected for MS/MS using a range of collision energies. Spectra were matched in MS-DIAL against the FiehnRT Lipid database (v16), confidently identifying 92 lipids. Strikingly, the results suggest that oesophageal adenocarcinoma cancer is associated with changes in 3 lipid metabolism pathways. For 2 of these pathways, corresponding lipid metabolic enzyme changes were detected in the proteomics analysis of the same cell lysates. The relevance of these lipid metabolic pathway changes were confirmed in patient biopsy samples using targeted MRM-MS assays.