cDNA microarray-based CGH ; Gene copy number change ; Correct classification rate ; Factor analysis ; Logistic regression model
Abstract
PURPOSE: To build a standardized genetic alteration score (SGAS) based on genes that are related to a patient's recurrence status, and to obtain the predicted score (PS) for predicting a patient's recurrence status, which reflects the genetic information of the gastric cancer patient.
METHODS: SGAS was constructed using linear combinations that best account for the variability in the data. This methodology was fit to and validated using cDNA microarray-based CGH data obtained from the Cancer Metastasis Research Center at Yonsei University.
RESULTS: When classifying cancer patients, the accuracy was 92.59% in the leave-one-out validation method.
CONCLUSIONS: SGAS provided PS for the risk of recurrence, which was capable of discriminating a patient's recurrence status. A total of 59 genes were found to have a high frequency of alteration in either the recurrence or non-recurrence status. SGAS was found to be a significant risk factor on recurrence and explained 31% variability of the 59 genes.