Single-gene prognostic signatures for advanced stage serous ovarian cancer based on 1257 patient samples
Single-gene prognostic signatures for advanced stage serous ovarian cancer based on 1257 patient samples
复制标题
基于 1257 例患者样本的晚期浆液性卵巢癌的单基因预后特征
DOI：
10.1039/c7mo00119c
复制
发表时间：
2018
期刊：
影响因子：
2.9
通讯作者：
Li Kang
中科院分区：
文献类型：
--
作者：
Zhang Fan;Yang Kai;Deng Kui;Zhang Yuanyuan;Zhao Weiwei;Xu Huan;Rong Zhiwei;Li Kang
ObjectiveWe sought to identify stable single-gene prognostic signatures based on a large collection of advanced stage serous ovarian cancer (AS-OvCa) gene expression data and explore their functions.MethodsThe empirical Bayes (EB) method was used to remove the batch effect and integrate 8 ovarian cancer datasets. Univariate Cox regression was used to evaluate the association between gene and overall survival (OS). The Database for Annotation, Visualization and Integrated Discovery (DAVID) tool was used for the functional annotation of genes for Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.ResultsThe batch effect was removed by the EB method, and 1257 patient samples were used for further analysis. We selected 341 single-gene prognostic signatures with FDR < 0.05, in which 110 and 231 genes were positively and negatively associated with OS, respectively. The functions of these genes were mainly involved in extracellular matrix organization, focal adhesion and DNA replication which are closely associated with cancer.ConclusionWe used the EB method to remove the batch effect of 8 datasets, integrated these datasets and identified stable prognosis signatures for AS-OvCa.
