Changes in the urine volatile metabolome throughout growth of transplanted hepatocarcinoma.

Trained detection dogs distinguish between urine samples from healthy organisms and organisms with malignant tumors, suggesting that the volatile urine metabolome contains information about tumor progression. The aim of this study was to determine whether the stage of tumor growth affects the chemical differences in the urine of mice and to what extent the "olfactory image of disease" perceived by dogs coincides with the "image of disease" recorded by the mass spectrometer. We used a novel laser ionization mass spectrometry method and propose a mass spectrometric analysis without detailed interpretation of the spectrum of volatile metabolomes in urine. The mass spectrometer we use works without sample preparation and registers volatile organic compounds in air at room temperature without changing the pH of the sample, i.e. under conditions similar to those in which dogs solve the same problem. The experimental cancer models were male BDF-f1 hybrid mice transplanted with hepatocarcinoma tissue, and similar mice transplanted with healthy liver tissue were used as controls. Our data show that both dogs and our proposed laser mass spectrometry method are able to detect both the entire spectrum of volatile organic compounds associated with the disease and minor changes in this spectrum during its course.

[Detection of Volatile Organic Compounds Associated with Hepatocellular Carcinoma by Macrosmatic Animals: Approaches to the Search for New Tumor Markers].

Macrosmatic animals (dogs and mice) have been proved to be able to distinguish between the urine or feces of mice with transplanted hepatocellular carcinoma and those of healthy mice by odor. The chemical composition of animal excreta was found to change with tumor growth; however, it is not clear yet if this results from tumor growth itself, inflammation, or immune response. We suggested that the use of the ability of macrosmatic animals to compare odor mixtures combined with mouse cancer models is a promising trend in the search for new tumor markers.