There is increasing worldwide interest in developing of markers for
tumor diagnosis and identification of individuals who are at high
cancer risk.
Cancer, like other diseases accompanied by metabolic disorders, causes characteristic effects on cell turnover rate, activity of modifying
enzymes, and
RNA/
DNA modifications. This results in an increased excretion of modified
nucleosides in
cancer patients. Therefore, for many years modified
nucleosides have been suggested as
tumor markers. The aim of the study was to elucidate further the usefulness of urinary
nucleosides as possible markers at early detection of
cancer in persons which are exposed against
tumor promoting influences during their working life.
Uranium miners are exposed to many kinds of
pollutants that can cause health damage even lead to
carcinogenesis. We analyzed modified
nucleosides in urine samples from 92 miners who are at high risk for
lung cancer to assess the levels of
nucleosides by a multilayer perceptron (MLP) classifier - a neural network model. Eighteen
nucleosides/metabolites were detected with reversed-phase high-pressure liquid chromatography (RP-HPLC). A valid set of urinary metabolites were selected and multivariate statistical technique of multilayer perceptron neural network were applied. In a previous study, MLP shows a sensitivity and specificity of 97 and 85%, respectively. MLP classification including the most relevant markers/
nucleosides clearly demonstrates the elevation of
RNA metabolism in miners, which is associated with possible malignant disease. We found that there were 30 subjects with early health disorders among 92
uranium workers based on MLP technique using modified
nucleosides. The combination of RP-HPLC analysis of modified
nucleosides and subsequent MLP analyses represents a promising tool for the development of a non-invasive prediction system and may assist in developing management and surveillance procedures.