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Effect of dietary polyphenols on K562 leukemia cells: A Foodomics approach

AutorValdés, Alberto ; Simó, Carolina ; Ibáñez, Clara ; Rocamora-Reverte, Lourdes; Ferragut, José A.; García-Cañas, Virginia ; Cifuentes, Alejandro
Palabras claveTranscriptomics
Metabolomics
Leukemia cells
Foodomics
Dietary polyphenols
Fecha de publicación2012
EditorWiley-VCH
CitaciónElectrophoresis 33(15): 2314-2327 (2012)
ResumenIn this work, a global Foodomics strategy has been applied to study the antiproliferative effect of dietary polyphenols from rosemary on two human leukemia lines, one showing a drug-sensitive phenotype (K562), and another exhibiting a drug-resistant phenotype (K562/R). To this aim, whole-transcriptome microarray together with an MS-based nontargeted analytical approach (via CE-TOF MS and UPLC-TOF MS) have been employed to carry out transcriptomics and metabolomics analyses, respectively. Functional enrichment analysis was done using ingenuity pathway analysis (IPA) software as a previous step for a reliable interpretation of transcriptomic and metabolomic profiles. Rosemary polyphenols altered the expression of approximately 1% of the genes covered by the whole transcriptome microarray in both leukemia cell lines. Overall, differences in the transcriptional induction of a number of genes encoding phase II detoxifying and antioxidant genes, as well as differences in the metabolic profiles observed in the two leukemia cell lines suggest that rosemary polyphenols may exert a differential chemopreventive effect in leukemia cells with different phenotypes. IPA predictions on transcription factor analysis highlighted inhibition of Myc transcription factor function by rosemary polyphenols, which may explain the observed antiproliferative effect of rosemary extract in the leukemia cells. Metabolomics analysis suggested that rosemary polyphenols affected differently the intracellular levels of some metabolites in two leukemia cell sublines. Integration of data obtained from transcriptomics and metabolomics platforms was attempted by overlaying datasets on canonical (defined) metabolic pathways using IPA software. This strategy enabled the identification of several differentially expressed genes in the metabolic pathways modulated by rosemary polyphenols providing more evidences on the effect of these compounds. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
URIhttp://hdl.handle.net/10261/101270
DOI10.1002/elps.201200133
Identificadoresdoi: 10.1002/elps.201200133
issn: 0173-0835
e-issn: 1522-2683
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