Literature DB >> 17145697

Integrating metabolomics and transcriptomics for probing SE anticancer mechanisms.

Teresa W-M Fan1, Richard M Higashi, Andrew N Lane.   

Abstract

Transcriptomics provides the tool for deciphering gene expression networks, and proteomics links these networks to protein products. The third crucial partner is metabolomics, which defines the metabolic network(s) linked to gene expression. NMR and mass spectrometry enable the broad screen analysis of the metabolome and its transformation pathways, transcending classical targeted metabolic studies. These tools were combined to investigate the anticancer mechanisms of different selenium forms in human lung cancer cells. Using 2-D NMR and tandem-MS, we mapped perturbations of 13C labeling patterns in numerous metabolites induced by selenite and selenomethionine. This information was used to interpret selenite-induced changes in gene expression networks. Linking metabolic dysfunctions to altered gene expression profiles provided new insights into the regulatory network underlying the metabolic dysfunctions, enabled the assembly of discrete gene expression events into functional pathways, and revealed protein targets for proteomic analysis.

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Year:  2006        PMID: 17145697     DOI: 10.1080/03602530600959599

Source DB:  PubMed          Journal:  Drug Metab Rev        ISSN: 0360-2532            Impact factor:   4.518


  20 in total

Review 1.  Stable isotope-resolved metabolomics and applications for drug development.

Authors:  Teresa W-M Fan; Pawel K Lorkiewicz; Katherine Sellers; Hunter N B Moseley; Richard M Higashi; Andrew N Lane
Journal:  Pharmacol Ther       Date:  2011-12-23       Impact factor: 12.310

2.  Methylseleninic acid promotes antitumour effects via nuclear FOXO3a translocation through Akt inhibition.

Authors:  Míriam Tarrado-Castellarnau; Roldán Cortés; Miriam Zanuy; Josep Tarragó-Celada; Ibrahim H Polat; Richard Hill; Teresa W M Fan; Wolfgang Link; Marta Cascante
Journal:  Pharmacol Res       Date:  2015-11-04       Impact factor: 7.658

3.  Analyzing LC/MS metabolic profiling data in the context of existing metabolic networks.

Authors:  Tianwei Yu; Yun Bai
Journal:  Curr Metabolomics       Date:  2013-01-01

4.  Inhibition of Anaplerotic Glutaminolysis Underlies Selenite Toxicity in Human Lung Cancer.

Authors:  Ronald C Bruntz; Alex C Belshoff; Yan Zhang; Jessica K A Macedo; Richard M Higashi; Andrew N Lane; Teresa W-M Fan
Journal:  Proteomics       Date:  2019-09-12       Impact factor: 3.984

Review 5.  Applications of NMR spectroscopy to systems biochemistry.

Authors:  Teresa W-M Fan; Andrew N Lane
Journal:  Prog Nucl Magn Reson Spectrosc       Date:  2016-02-06       Impact factor: 9.795

6.  Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells.

Authors:  Teresa W-M Fan; Jinlian Tan; Martin M McKinney; Andrew N Lane
Journal:  Metabolomics       Date:  2012-06       Impact factor: 4.290

7.  Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM).

Authors:  Teresa W M Fan; Andrew N Lane; Richard M Higashi; Mohamed A Farag; Hong Gao; Michael Bousamra; Donald M Miller
Journal:  Mol Cancer       Date:  2009-06-26       Impact factor: 27.401

8.  Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR.

Authors:  Andrew N Lane; Teresa W-M Fan; Zhengzhi Xie; Hunter N B Moseley; Richard M Higashi
Journal:  Anal Chim Acta       Date:  2009-08-27       Impact factor: 6.558

9.  Metabolic profiling identifies lung tumor responsiveness to erlotinib.

Authors:  Teresa W-M Fan; Andrew N Lane; Richard M Higashi; Michael Bousamra; Goetz Kloecker; Donald M Miller
Journal:  Exp Mol Pathol       Date:  2009-05-03       Impact factor: 3.362

Review 10.  Prospects for clinical cancer metabolomics using stable isotope tracers.

Authors:  Andrew N Lane; Teresa W-M Fan; Richard M Higashi; Jinlian Tan; Michael Bousamra; Donald M Miller
Journal:  Exp Mol Pathol       Date:  2009-01-20       Impact factor: 3.362

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