Jung Jae-Joon, Jeung Hei-Cheul, Chung Hyun Cheol, Lee Jung Ok, Kim Tae Soo, Kim Yong Tai, Noh Sung Hoon, Rha Sun Young
Cancer Metastasis Research Center, Yonsei University College of Medicine, Seoul, 120-752, Korea.
Genomics. 2009 Jan;93(1):52-61. doi: 10.1016/j.ygeno.2008.08.002. Epub 2008 Oct 22.
Gastric cancer is one of the most common cancers worldwide, and there are clinical caveats in predicting tumor response to chemotherapy. This study describes the construction of an in vitro pharmacogenomic database, and the selection of genes associated with chemosensitivity in gastric cancer cell lines. Gene expression and chemosensitivity databases were integrated using the Pearson correlation coefficient to give the GC-matrix. The 85 genes were selected that were commonly associated with chemosensitivity of the major anticancer drugs. We then focused on the genes that were highly correlated with each specific drug. Classification of cell lines based on the set of genes associated with each drug was consistent with the division into resistant or sensitive groups according to the chemosensitivity results. The GC-matrix of the gastric cancer cell line database was used to identify different sets of chemosensitivity-related genes for specific drugs or multiple drugs.
胃癌是全球最常见的癌症之一,在预测肿瘤对化疗的反应方面存在临床注意事项。本研究描述了体外药物基因组数据库的构建,以及胃癌细胞系中与化学敏感性相关基因的选择。利用皮尔逊相关系数整合基因表达和化学敏感性数据库,得到GC矩阵。选择了85个与主要抗癌药物化学敏感性通常相关的基因。然后我们专注于与每种特定药物高度相关的基因。根据与每种药物相关的基因集对细胞系进行分类,与根据化学敏感性结果分为耐药或敏感组一致。胃癌细胞系数据库的GC矩阵用于识别特定药物或多种药物的不同化学敏感性相关基因集。