Prediction of breast cancer by profiling of urinary RNA metabolites using Support Vector Machine-based feature selection.

ABSTRACT:

Background

Breast cancer belongs to the most frequent and severe cancer types in human. Since excretion of modified nucleosides from increased RNA metabolism has been proposed as a potential target in pathogenesis of breast cancer, the aim of the present study was to elucidate the predictability of breast cancer by means of urinary excreted nucleosides.

Methods

We analyzed urine samples from 85 breast cancer women and respective healthy controls to assess the metabolic profiles of nucleosides by a comprehensive bioinformatic approach. All included nucleosides/ribosylated metabolites were isolated by cis-diol specific affinity chromatography and measured with liquid chromatography ion trap mass spectrometry (LC-ITMS). A valid set of urinary metabolites was selected by exclusi

SUBMITTER: Henneges C 

PROVIDER: S-EPMC2680413 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature