Capillary electrophoretic profiling and pattern recognition analysis of urinary nucleosides from thyroid cancer patients

Abstract

Metabolic profiling analysis by capillary electrophoresis (CE) was combined with pattern recognition methods to see some correlation between urinary nucleoside levels and thyroid cancer. A total of 15 nucleosides were identified in urines from 12 female thyroid cancer patients and 12 healthy females studied. From the scatter plot evaluation, inosine showed the highest estimated diagnostic power with ca. 97.725% confidence level, followed by N 2-methylguanosine. Star symbol graphs showed differences in levels of both minor and major nucleosides between cancer and normal groups more efficiently, compared with histogram. The stepwise discriminant analysis (SDA) selected N 2-methylguanosine, N 2, N 2-dimethylguanosine and 1-methylguanosine as the most discriminating variables between thyroid cancer and normal groups. The canonical discriminant analysis (CDA) correctly classified all urine specimens studied into two separate clusters of cancer and normal groups in a canonical plot. The principal component analysis (PCA) distinguished cancer patients from normal controls in a principal component plot. The cluster analysis (CA) yielded a dendrogram displaying group separation without any single wrong linkage.