基于人类信号转导网络研究卵巢癌病变过程的信号转导模式

发布时间：2018-05-19 08:17

本文选题：人类信号转导网络 + 卵巢癌　；参考：《生物物理学报》2015年03期

【摘要】：为了系统地研究卵巢癌病变过程的信号转导模式,综合多种信息构建了完整的人类信号转导网络,发现卵巢癌相关基因在网络中的拓扑学性质与其它基因存在显著差异。将正常、早期卵巢癌和晚期卵巢癌三种状态下的基因表达谱数据映射到信号转导网络中,利用基于共表达改变量的方法,筛选出正常与早期卵巢癌、正常与晚期卵巢癌、早期卵巢癌与晚期卵巢癌间的显著差异模体。通过对显著差异模体进行功能和模式的分析,发现卵巢癌的发生发展主要和信号级联模式的异常相关。另外,还发现AR、PAK6和KPNB1三个基因间信号转导模式的异常和卵巢癌的恶化相关。
[Abstract]:In order to systematically study the signal transduction modes in the process of ovarian cancer, a complete human signal transduction network was constructed by synthesizing many kinds of information. It was found that the topological properties of ovarian cancer related genes in the network were significantly different from those of other genes. The gene expression profiles of normal, early and advanced ovarian carcinomas were mapped to signal transduction networks, and normal and early ovarian carcinomas, normal and advanced ovarian carcinomas were screened by coexpression alteration method. Significant difference motifs between early and advanced ovarian cancer. By analyzing the function and pattern of significantly different motifs, it is found that the occurrence and development of ovarian cancer is mainly related to the abnormal signal cascade pattern. It was also found that the abnormal signal transduction patterns of ARN PAK6 and KPNB1 were associated with the deterioration of ovarian cancer.
【作者单位】：同济大学生命科学与技术学院;上海生物信息技术研究中心;华东理工大学生物工程学院;中国科学院上海生命科学院生化与细胞研究所系统生物学重点实验室;
【分类号】：R318.04

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