Lipidomic Characterization of Tumor Tissues Using LC/MS, SFC/MS, MALDI-MS and Multivariate Data Analysis
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25310%2F14%3A39899342" target="_blank" >RIV/00216275:25310/14:39899342 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Lipidomic Characterization of Tumor Tissues Using LC/MS, SFC/MS, MALDI-MS and Multivariate Data Analysis
Popis výsledku v původním jazyce
Results Comprehensive lipidomic analyses of tumor tissues and surrounding normal tissues from several clinical trials (breast, kidney and lung cancer) were performed using optimized HILIC-HPLC/ESI-MS, SFC/MS, MALDI-Orbitrap MS methods. Individual lipid classes were quantified based on the addition of single IS and response factors for each class related to the IS. Statistically significant differences in average concentrations were observed several classes of polar lipids (PI, PE, LPE, SM, LPC, etc.). Detailed analysis of lipid species inside above mentioned classes was performed using relative abundances of deprotonated molecules in the negative-ion ESI mode or protonated molecules in the positive-ion ESI mode followed by MS/MS experiments. Multivariate data analysis using orthogonal 2 projections of latent structures (O2PLS) enables a clear differentiation of tumor and normal tissues based on changes of their lipidome. Conclusions The statistically significant lipidomic differences w
Název v anglickém jazyce
Lipidomic Characterization of Tumor Tissues Using LC/MS, SFC/MS, MALDI-MS and Multivariate Data Analysis
Popis výsledku anglicky
Results Comprehensive lipidomic analyses of tumor tissues and surrounding normal tissues from several clinical trials (breast, kidney and lung cancer) were performed using optimized HILIC-HPLC/ESI-MS, SFC/MS, MALDI-Orbitrap MS methods. Individual lipid classes were quantified based on the addition of single IS and response factors for each class related to the IS. Statistically significant differences in average concentrations were observed several classes of polar lipids (PI, PE, LPE, SM, LPC, etc.). Detailed analysis of lipid species inside above mentioned classes was performed using relative abundances of deprotonated molecules in the negative-ion ESI mode or protonated molecules in the positive-ion ESI mode followed by MS/MS experiments. Multivariate data analysis using orthogonal 2 projections of latent structures (O2PLS) enables a clear differentiation of tumor and normal tissues based on changes of their lipidome. Conclusions The statistically significant lipidomic differences w
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
CB - Analytická chemie, separace
OECD FORD obor
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Návaznosti výsledku
Projekt
<a href="/cs/project/LL1302" target="_blank" >LL1302: Hmotnostní spektrometrie při hledání lipidových biomarkerů pro včasnou diagnostiku rakoviny</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2014
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů