LEADER 03690nam 2200949z- 450 001 9910367563603321 005 20231214132858.0 010 $a3-03921-346-6 035 $a(CKB)4100000010106110 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/42643 035 $a(EXLCZ)994100000010106110 100 $a20202102d2019 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aCancer Metabolomics 2018 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 215 $a1 electronic resource (184 p.) 311 $a3-03921-345-8 330 $aThe metabolomics approach, defined as the study of all endogenously-produced low-molecular-weight compounds, appeared as a promising strategy to define new cancer biomarkers. Information obtained from metabolomic data can help to highlight disrupted cellular pathways and, consequently, contribute to the development of new-targeted therapies and the optimization of therapeutics. Therefore, metabolomic research may be more clinically translatable than other omics approaches, since metabolites are closely related to the phenotype and the metabolome is sensitive to many factors. Metabolomics seems promising to identify key metabolic pathways characterizing features of pathological and physiological states. Thus, knowing that tumor metabolism markedly differs from the metabolism of normal cells, the use of metabolomics is ideally suited for biomarker research. Some works have already focused on the application of metabolomic approaches to different cancers, namely lung, breast and liver, using urine, exhaled breath and blood. In this Special Issue we contribute to a more complete understanding of cancer disease using metabolomics approaches. 610 $acell transporters 610 $apharmacodynamics 610 $acell growth 610 $ain vitro study 610 $ametabolomic signatures 610 $aendometabolome 610 $alung cancer 610 $ametabolomics 610 $achemometric methods 610 $abladder cancer 610 $amTOR 610 $ametabolite profiling 610 $ametabolic pathways 610 $ahepatocellular carcinoma 610 $aglutamate 610 $asenescence MCF7 610 $abreath analysis 610 $abio actives 610 $abiomarker 610 $agas chromatography?mass spectrometry (GC?MS) 610 $aGC-MS 610 $alung 610 $aomics 610 $anutraceuticals 610 $aglutaminase 610 $ametabolism 610 $aacylcarnitines 610 $aErwinaze 610 $aKidrolase 610 $aglutathione 610 $atargeted metabolomics 610 $aapoptosis 610 $aSLC1A5 610 $aessential amino acids 610 $acancer progression 610 $aASCT2 610 $aHR MAS 610 $aalanine 610 $aanalytical platforms 610 $avolatile organic compound 610 $aglutaminolysis 610 $aisotope tracing analysis 610 $aasparaginase 610 $avitamin E 610 $abreast cancer 610 $aprognosis 610 $aearly diagnosis 610 $atocotrienols 610 $aNMR 610 $aprostate cancer 610 $ain vitro 610 $acancer 610 $aMDA-MB-231 700 $aPinto$b Joana$4auth$01281247 702 $aCarvalho$b Márcia$4auth 702 $aDe Pinho$b Paula Guedes$4auth 906 $aBOOK 912 $a9910367563603321 996 $aCancer Metabolomics 2018$93018420 997 $aUNINA