Metabolomics-edited transcriptomics analysis of Se anticancer action in human lung cancer cells

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67 Scopus citations


Transcriptomic analysis is an essential tool for systems biology but it has been stymied by a lack of global understanding of genomic functions, resulting in the inability to link functionally disparate gene expression events. Using the anticancer agent selenite and human lung cancer A549 cells as a model system, we demonstrate that these difficulties can be overcome by a progressive approach which harnesses the emerging power of metabolomics for transcriptomic analysis. We have named the approach Metabolomics-edited transcriptomic analysis (META). The main analytical engine was 13C isotopomer profiling using a combination of multi-nuclear 2-D NMR and GC-MS techniques. Using 13C-glucose as a tracer, multiple disruptions to the central metabolic network in A549 cells induced by selenite were defined. META was then achieved by coupling the metabolic dysfunctions to altered gene expression profiles to: (1) provide new insights into the regulatory network underlying the metabolic dysfunctions; (2) enable the assembly of disparate gene expression events into functional pathways that was not feasible by transcriptomic analysis alone. This was illustrated in particular by the connection of mitochondrial dysfunctions to perturbed lipid metabolism via the AMP-AMPK pathway. Thus, META generated both extensive and highly specific working hypotheses for further validation, thereby accelerating the resolution of complex biological problems such as the anticancer mechanism of selenite.

Original languageEnglish
Pages (from-to)325-339
Number of pages15
Issue number4
StatePublished - Oct 2005

Bibliographical note

Funding Information:
This work was supported by NCI Grant 1 R01 CA101199-01, the JG Brown Foundation for the NMR facility and Microarray facility of the JG Brown Cancer Center and NSF EPSCoR Grant EPS-0132295 for the 18.8 T NMR spectrometer (to R.J. Wittebort) and NSF EPSCoR grant EPS-0447479 (to T.W.-M. Fan). ANL thanks the Kentucky Challenge for Excellence for support. We also thank Ms. Anna Tchernatynskaia for performing the HPLC analysis of nucleotides and Dr. Sabine Waigel for assistance in microarray data analysis.


  • (3-6) two-dimensional NMR
  • C isotopomer profiling
  • GC-tandem MS
  • Lung adenocarcinoma A549 cells
  • Selenite

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Clinical Biochemistry


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