Mass Spectrometry in Cancer Research: Lipid Biomarkers for Early Diagnostics
Provider: Ministerstvo školství, mládeže a tělovýchovy
Programme: ERC_CZ
Implementation period: 01.07.13 - 30.06.18
Workplace:
Fakulta chemicko-technologická - Katedra analytické chemie
Investigator: Holčapek MichalTeam member: Jirásko Robert
Description:
Cancer affects the metabolomic composition of cells, which can be used for the discovery of lipid biomarkers for the early cancer diagnostics. Biochemical changes are also reflected in the composition of body fluids applicable for the non-invasive cancer screening. The early diagnosis of cancer significantly improves the probability of survival, especially for cancer types with missing reliable screening and high mortality rates, e.g., lung, prostate, kidney and pancreas cancer. The goal of our comprehensive comparison of lipidomic profiles is to find up- or down-regulated lipid molecules in analyzed biological materials, such as surgically dissected tumors vs. healthy tissues, blood, urine and breath condensate from cancer patients and healthy controls. New articles indicate that lipidomic changes may be related to an increased activity of glycosylation enzymes and also the lipid oxidation of polyunsaturated fatty acid chains, so possible biomarkers are expected in this area. The whole range of modern mass spectrometric techniques and their coupling to liquid-phase separations with an ultimate performance in terms of sensitivity, specificity and resolution will be used. The multivariate statistical analysis will be used for the determination of possible biomarkers. The robotic system with an automated sample handling, lipid extraction from the tissue surface, infusion to disposable nanoelectrospray tips and finally automated data processing will be used for highthroughput lipidomic screening in the initial step. The quantitation of individual lipid classes will be done by our novel method based on hydrophilic interaction UHPLC/MS. Multidimensional separation approaches including the regioisomeric and chiral recognition will be applied for representative samples. The complementary information on the spatial distribution of lipid molecules will be studied by mass spectrometric imaging. The plasma lipidomic database will be created for all measured samples.
Cancer affects the metabolomic composition of cells, which can be used for the discovery of lipid biomarkers for the early cancer diagnostics. Biochemical changes are also reflected in the composition of body fluids applicable for the non-invasive cancer screening. The early diagnosis of cancer significantly improves the probability of survival, especially for cancer types with missing reliable screening and high mortality rates, e.g., lung, prostate, kidney and pancreas cancer. The goal of our comprehensive comparison of lipidomic profiles is to find up- or down-regulated lipid molecules in analyzed biological materials, such as surgically dissected tumors vs. healthy tissues, blood, urine and breath condensate from cancer patients and healthy controls. New articles indicate that lipidomic changes may be related to an increased activity of glycosylation enzymes and also the lipid oxidation of polyunsaturated fatty acid chains, so possible biomarkers are expected in this area. The whole range of modern mass spectrometric techniques and their coupling to liquid-phase separations with an ultimate performance in terms of sensitivity, specificity and resolution will be used. The multivariate statistical analysis will be used for the determination of possible biomarkers. The robotic system with an automated sample handling, lipid extraction from the tissue surface, infusion to disposable nanoelectrospray tips and finally automated data processing will be used for highthroughput lipidomic screening in the initial step. The quantitation of individual lipid classes will be done by our novel method based on hydrophilic interaction UHPLC/MS. Multidimensional separation approaches including the regioisomeric and chiral recognition will be applied for representative samples. The complementary information on the spatial distribution of lipid molecules will be studied by mass spectrometric imaging. The plasma lipidomic database will be created for all measured samples.
