Artificial neural network classification based on high-performance liquid chromatography of urinary and serum nucleosides for the clinical diagnosis of cancer.
Nucleosides in human urine and serum have frequently been studied as a possible biomedical marker for cancer, acquired immune deficiency syndrome (AIDS) and the whole-body turnover of RNAs. Fifteen normal and modified nucleosides were determined in 69 urine and 42 serum samples using high-performance liquid chromatography (HPLC). Artificial neural networks have been used as a powerful pattern recognition tool to distinguish cancer patients from healthy persons. The recognition rate for the training set reached 100%. In the validating set, 95.8 and 92.9% of people were correctly classified into cancer patients and healthy persons when urine and serum were used as the sample for measuring the nucleosides. The results show that the artificial neural network technique is better than principal component analysis for the classification of healthy persons and cancer patients based on nucleoside data.
Yang
Jun
J
National Chromatographic R&A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116012, China.
Xu
Guowang
G
Kong
Hongwei
H
Zheng
Yufang
Y
Pang
Tao
T
Yang
Qing
Q
D014408:Biomarkers, Tumor / Q000097:blood* / Q000652:urine*; D016022:Case-Control Studies; D002851:Chromatography, High Pressure Liquid / Q000379:methods*; D006801:Humans; D009369:Neoplasms / Q000097:blood / Q000175:diagnosis* / Q000652:urine; D016571:Neural Networks, Computer; D009705:Nucleosides / Q000097:blood* / Q000652:urine*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
D014408:Biomarkers, Tumor; D009705:Nucleosides