Abstract：Abstract: Alternative splicing is a regulatory mechanism of transcriptional regulation, which is of great significance for the prognosis and treatment of cancers. In order to explore the prognostic value of alternative splicing events in ovarian cancer, the alternative splicing events were analyzed systematically. First, the data of ovarian cancer patients were obtained from TCGASpliceSeq database, and 290 prognostic-associated alternative splicing events (PASEs) were selected by using univariate Cox regression analysis; Then, the protein-protein interaction (PPI) data of PASEs were combined to construct a prognostic weighted network for ovarian cancer. At the same time, topological analysis of the network and functional enrichment analysis of genes of PASEs were carried out; Finally, 20 alternative splicing events were selected as prognostic features according to the degree of nodes in the network, and the Cox proportional hazard model was used to establish a prognostic model by these features. The results showed that these alternative splicing events can be used to predict the prognosis of ovarian cancer patients, and as potential biomarkers for ovarian cancer prognosis.
引用本文:
顾云婧, 潘以红, 朱东月, 朱 平. 基于加权网络的卵巢癌可变剪接预后特征分析[J]. 生命科学研究, 2019, 23(6): 444-451. GU Yun-jing, PAN Yi-hong, ZHU Dong-yue, ZHU Ping. Analysis of Prognostic-associated Alternative Splicing Signatures in Ovarian Cancer Based on Weighted Network. Life Science Research, 2019, 23(6): 444-451.
2019,Vol. 23
