基于基因团搜索的卵巢癌化疗反应敏感基因网络构建

Establish Relevant Gene Network for Ovarian Cancer Chemotherapy Response Based on Gene Clique Research

针对卵巢癌化疗反应(ovarian cancer chemotherapy response,OCCR)基因调控模型问题,文中提出一种基于基因团搜索建立基因网络的方法。利用搜索基因对基因组进行搜索,找到与之相关的基因团,通过桥基因拼接得到基因网络,并对结果从统计学和生物学角度进行验证。统计检验显示基因间关系显著,且基因间动态关系变化明显。丰度分析表明,基因团显著参与了生物调控过程。独立的网络分析及调控路径分析显示了基因团之间强烈的调控关系。大量文献查询显示,该基因网络在肿瘤形成、细胞增殖及转移中起重要作用,且与卵巢癌化疗反应有密切关系。

This paper proposed an efficient method to establish ovarian cancer chemotherapy response（OCCR） relevant gene network based on clique research. With query genes to detect genome and piece the isolated gene pairs up into networks with the help of the identified common bridging genes. At the same time, through statistics and biology knowledge to verify the network. Using 4 query genes, the authors established one OCCR relevant gene network. Statistical analysis shows that the scouting results for these four query genes are significant and the variation of relations between genes are obviously. Biologically,functional enrichment analysis shows that the gene network is enriched with known functional gene sets and shed light on regulatory circuits with network analysis. Pathway analysis shows that these genes are either functionally or physically connected. Literature analysis shows that the identified genes in this identified networks are playing import roles in tumorigenesis, cell proliferation and migration, and thus are significantly OCCR relevant.