About: Lipidomic Characterization of Tumor Tissues Using LC/MS, SFC/MS, MALDI-MS and Multivariate Data Analysis     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • 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 were described for different types of tumor tissues (e.g., breast, kidney, lung) in comparison with surrounding normal tissues of the same patient obtained after the surgery. This work was supported by ERC CZ project No. LL1302 (MSMT, Czech Republic). Novel Aspect Combination of UHPLC/MS, SFC/MS and MALDI-MS followed by the multivariate data analysis is used for detailed lipidomic characterization of cancer tissues.
  • 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 were described for different types of tumor tissues (e.g., breast, kidney, lung) in comparison with surrounding normal tissues of the same patient obtained after the surgery. This work was supported by ERC CZ project No. LL1302 (MSMT, Czech Republic). Novel Aspect Combination of UHPLC/MS, SFC/MS and MALDI-MS followed by the multivariate data analysis is used for detailed lipidomic characterization of cancer tissues. (en)
Title
  • Lipidomic Characterization of Tumor Tissues Using LC/MS, SFC/MS, MALDI-MS and Multivariate Data Analysis
  • Lipidomic Characterization of Tumor Tissues Using LC/MS, SFC/MS, MALDI-MS and Multivariate Data Analysis (en)
skos:prefLabel
  • Lipidomic Characterization of Tumor Tissues Using LC/MS, SFC/MS, MALDI-MS and Multivariate Data Analysis
  • Lipidomic Characterization of Tumor Tissues Using LC/MS, SFC/MS, MALDI-MS and Multivariate Data Analysis (en)
skos:notation
  • RIV/00216275:25310/14:39899342!RIV15-MSM-25310___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(LL1302)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 26306
http://linked.open...ai/riv/idVysledku
  • RIV/00216275:25310/14:39899342
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • MALDI-MS; SFC/MS; LC/MS; Tumor; Lipidomic Characterization (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [29DA6A610DD2]
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Holčapek, Michal
  • Lísa, Miroslav
  • Melichar, Bohuslav
  • Cífková, Eva
  • Vrána, David
  • Gatěk, Jiří
  • Chagovets, Vitaliy Viktorovich
http://localhost/t...ganizacniJednotka
  • 25310
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 48 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software