基于复杂网络的胃癌关键基因筛选与分析

运用复杂网络理论,对TCGA胃癌数据进行了筛选与降维,筛选出275个胃癌相关的基因,获得样本容量为40的胃癌ⅡB期样本组和样本容量为36的胃癌ⅢA期样本组。通过分析胃癌ⅡB期样本组与胃癌ⅢA期样本组的基因变化率,建立节点（基因）间的连边关系,从而构建了胃癌恶化过程的基因表达网络。引入综合中心性指标对网络进行分析,筛选出17个综合中心指数较高的基因。应用复杂网络的相关理论对胃癌基因网络进行社区划分,发现17个综合中心指数较高的基因全部落在一个规模较大的连通的子网络中,此拓扑结构与胃癌基因表达网络的关键节点一致。通过综合分析获取了胃癌恶化过程中的关键基因,提供了良好的胃癌恶化早期的预警信号。

Screening and Analysis of Key Genes in Gastric Cancer Based on Complex Network

Through the complex network theory, screening and dimension reduction in accordance with the TCGA(The cancer genome atlas) gastric cancer data are dealt with. We selected 275 genes related to gastric cancer, 40 samples of patients with stage IIB of gastric cancer and 36 samples of patients with stage IIIA of gastric cancer. By analyzing the gene change rate of the gastric cancer IIB sample group and the gastric cancer IIIA sample group, the joint relationship between the nodes (genes) is established. Due to the above work, the gene expression network in the process of gastric cancer deterioration is constructed. The network is analyzed by making uses of comprehensive central indicators, and 17 genes with higher comprehensive index are screened out. Using the relevant theory of complex networks to divide the gastric cancer gene network into communities, it is found that all the genes with higher index of 17 comprehensive centers fall in a large connected sub-network.This topology is consistent with the key nodes of the gastric cancer gene expression network. Therefore we have verified our conclusions on the other hand.Through comprehensive analysis, the key genes in the process of gastric cancer deterioration are obtained, which provided an effective early warning signal for gastric cancer deterioration.