Summary
Lipids are involved in numerous pathways of human metabolism that are related to pathological states. Alterations of lipid concentrations in the blood of cancer patients have been reported but the biological origin is still unknown. Deciphering the mechanisms of the lipid dysregulation mechanism could dramatically change oncology because it can open new avenues for cancer detection with subsequent effective treatment and drug development targeting dysregulated pathways. Early cancer diagnosis is one of the main unmet needs in medicine, which can improve the unfavorable prognosis of patients. The potential of lipidomics has not been fully explored yet, because analytical workflows have limitations in terms of accurate molar quantitation and insufficient coverage of the lipidome. Biologists predict up to 100,000 lipid species in nature, but current methods typically report less than 1% of this number. Here, we will develop novel approaches for quantitation of more than 2,000 lipids from >80 classes using 13C stable isotope labeled internal standards and ultrahigh-resolution methods in liquid or supercritical fluid chromatography, mass spectrometry, and ion mobility. The comprehensive characterization of lipidome will allow us to construct Cancer Lipidome Atlas (WP1). We will develop new Bayesian software for automated data processing and statistical evaluation applicable to the main lipidomic and metabolomic workflows (WP2). We will correlate lipidomics data with metabolomics, proteomics, and transcriptomics data to unravel why lipidomic dysregulation in blood has a similar pattern for various cancers (WP3). This strategy will be applied for the comparison of ten types of cancer with control samples in cell lines, animal models (mice and pigs), human samples (tissues and plasma), and extracellular vesicles. Our initial hypothesis is that the lower activity of CERS2 triggered by cancer cells can downregulate very long fatty acyl ceramides and other sphingolipids.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101095860 |
| Start date: | 01-08-2023 |
| End date: | 31-07-2028 |
| Total budget - Public funding: | 3 499 413,00 Euro - 3 499 413,00 Euro |
Cordis data
Original description
Lipids are involved in numerous pathways of human metabolism that are related to pathological states. Alterations of lipid concentrations in the blood of cancer patients have been reported but the biological origin is still unknown. Deciphering the mechanisms of the lipid dysregulation mechanism could dramatically change oncology because it can open new avenues for cancer detection with subsequent effective treatment and drug development targeting dysregulated pathways. Early cancer diagnosis is one of the main unmet needs in medicine, which can improve the unfavorable prognosis of patients. The potential of lipidomics has not been fully explored yet, because analytical workflows have limitations in terms of accurate molar quantitation and insufficient coverage of the lipidome. Biologists predict up to 100,000 lipid species in nature, but current methods typically report less than 1% of this number. Here, we will develop novel approaches for quantitation of more than 2,000 lipids from >80 classes using 13C stable isotope labeled internal standards and ultrahigh-resolution methods in liquid or supercritical fluid chromatography, mass spectrometry, and ion mobility. The comprehensive characterization of lipidome will allow us to construct Cancer Lipidome Atlas (WP1). We will develop new Bayesian software for automated data processing and statistical evaluation applicable to the main lipidomic and metabolomic workflows (WP2). We will correlate lipidomics data with metabolomics, proteomics, and transcriptomics data to unravel why lipidomic dysregulation in blood has a similar pattern for various cancers (WP3). This strategy will be applied for the comparison of ten types of cancer with control samples in cell lines, animal models (mice and pigs), human samples (tissues and plasma), and extracellular vesicles. Our initial hypothesis is that the lower activity of CERS2 triggered by cancer cells can downregulate very long fatty acyl ceramides and other sphingolipids.Status
SIGNEDCall topic
ERC-2022-ADGUpdate Date
12-03-2024
Images
No images available.
Geographical location(s)
