Targeted metabolic analysis of nucleotides and identification of biomarkers associated with cancer in cultured cell models

Cancer, like other diseases accompanied by metabolic changes, shows characteristic DNA/RNA modifications and activities of modifying enzymes, resulting in fluctuations in nucleoside levels. In this study, we undertook targeted metabolomic analyses of nucleotides in different cancer cell culture models using a sensitive and reproducible ion-pair HPLC method. The experimental data were analyzed by principal component analysis (PCA) to identify potential biomarkers in cancer cells, and statistical significance was determined by one-way analysis of variance. As a result, a clear differentiation of normal and tumor cells into two clusters was shown, indicating abnormal metabolism of nucleotides in tumor cells. Six variables (AMP, UDP, CTP levels with a significance of P<0.05; ATP, UTP and GMP levels with a significance of P<0.01) were considered as potential biomarkers; the content of AMP, UTP, GMP and ATP was significantly higher in cancer cells. The receiver operating characteristic (ROC) curve analysis allowed us to discriminate normal cells from tumor cells based on area under the curve (AUC). The sequence of their AUC values were: ATP (0.979)>UTP (0.938)>CTP=GMP (0.896)>AMP (0.812)>UDP (0.792), so we conclude that ATP and UTP are the best potential biomarkers in tumor cells. This study may provide a valuable tool for studying minute alterations of intracellular nucleotide pools induced by anticancer/antiviral drugs, diseases or environmental factors.

Targeted metabolomic analyses of nucleotides in 4 normal and 12 tumor cell lines were conducted using a sensitive and reproducible ion-pair HPLC method coupled with principal component analysis and one-way analysis of variance. The normal and tumor cells clustered in two regions, owing to differing levels of AMP, UDP, CTP, ATP, UTP and GMP. Abnormal metabolism of nucleotides was found in tumor cells. Figure optionsDownload as PowerPoint slide