Kim Mijung, Chung Hyun Cheol
Institute for Mathematical Sciences, Yonsei University, 134 Shinchon-Dong, Seodaemun-Gu, Seoul 120-752, Korea.
J Cancer Res Clin Oncol. 2009 Nov;135(11):1501-12. doi: 10.1007/s00432-009-0597-1. Epub 2009 May 16.
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.
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.
When classifying cancer patients, the accuracy was 92.59% in the leave-one-out validation method.
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.
基于与患者复发状态相关的基因构建标准化基因改变评分（SGAS），并获得用于预测患者复发状态的预测评分（PS），该评分反映胃癌患者的遗传信息。
使用能最佳解释数据变异性的线性组合构建SGAS。该方法用从延世大学癌症转移研究中心获得的基于cDNA微阵列的比较基因组杂交（CGH）数据进行拟合和验证。
在留一法验证中，对癌症患者进行分类时准确率为92.59%。
SGAS提供了复发风险的PS，能够区分患者的复发状态。共发现59个基因在复发或非复发状态下有高频改变。SGAS被发现是复发的一个重要风险因素，可解释这59个基因31%的变异性。
