Data mining of microarray for differentially expressed genes in liver metastasis from gastric cancer

Abstract

Tumor metastasis is the leading cause of death for gastric cancer. Metastasis is the main reason for the failure of clinical treatment for gastric cancer. In order to find metastasis-related genes and abnormal signal transduction pathway of high-invasive gastric cancer, samples of gastric cancer with liver metastasis were collected for microarray detection; up-regulated or down-regulated genes in all three cases were simultaneously screened out. Subsequently, from the preliminary screened genes, molecular pathways possibly impacting liver metastasis from gastric cancer were investigated by the Gene Cluster with Literature Profiles (GenCLip) analysis software. Many biological effects including apoptosis have been validated. Functional analysis of differentially expressed genes revealed that a variety of biological pathways, such as blood circulation and gas exchange, vasodilation and vasoconstriction regulation, and immune defense, could be significantly activated. Besides, gene sequences, specific keywords or gene regulatory networks were further searched by GenCLiP. We conclude that data mining allows to quickly identify a series of special signal transduction pathways involving abnormally expressed genes.

Keywords

gastric carcinoma / metastasis / signal transduction / gene chips