Identification of metabolites with anticancer properties by computational metabolomics

Adrian K Arakaki^*¹^,2 , Roman Mezencev^*²^,3 , Nathan J Bowen²^,3 , Ying Huang¹^,2 , John F McDonald²^,3 and Jeffrey Skolnick¹^,2

¹Center for the Study of Systems Biology, Georgia Institute of Technology, Atlanta, Georgia, USA

²School of Biology, Georgia Institute of Technology, Atlanta, Georgia, USA

³Ovarian Cancer Institute, Georgia Institute of Technology, Atlanta, Georgia, USA

author email corresponding author email* Contributed equally

Molecular Cancer 2008, 7:57doi:10.1186/1476-4598-7-57


Published:	17 June 2008

Additional files

Additional File 1:

Supplementary Methods. Word document describing the cell cultures, RNA extraction, amplification and microarray data processing, cell proliferation assays and verification of selective antiproliferative effect of metabolites on Jurkat vs. lymphoblast cells.

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Additional File 2:

Metabolites present in the genetic-metabolic matrix. Excel table listing KEGG Ligand Identifier, common names and hyperlink to KEGG database for the 982 metabolites present in the genetic-metabolic matrix, as well as the 104 (78) metabolites whose concentration is predicted by CoMet to be lowered (increased) in Jurkat cells compared to normal lymphoblasts.

Format: XLS Size: 557KB Download file

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Additional File 3:

Validation of microarray gene expression data by qRT-PCR. Word document describing the validation by quantitative real-time PCR (qRT-PCR) of the microarray gene expression data corresponding to the genes used by CoMet to predict a decreased level of seleno-L-methionine in Jurkat cells.

Format: DOC Size: 33KB Download file

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