Liu Zijian, Mi Mi, Li Xiaoqian, Zheng Xin, Wu Gang, Zhang Liling
Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Front Genet. 2019 Sep 13;10:850. doi: 10.3389/fgene.2019.00850. eCollection 2019.
The competing endogenous RNA (ceRNA) networks are an effective method for investigating cancer; however, construction of ceRNA networks among different subtypes of breast cancer has not been previously performed. Based on analysis of differentially expressed RNAs between 150 triple-negative breast cancer (TNBC) tissues and 823 non-triple-negative breast cancer (nTNBC) tissues downloaded from TCGA database, a ceRNA network was constructed based on database comparisons using Cytoscape. Survival analysis and receiver operating characteristic curve data were combined to screen out prognostic candidate genes, which were subsequently analyzed using co-expressed functionally related analysis, Gene Set Variation Analysis (GSVA) pathway-related analysis, and immune infiltration and tumor mutational burden immune-related analysis. A total of 190 differentially expressed lncRNAs (DElncRNAs), 48 differentially expressed mRNAs (DEmRNAs), and 13 differentially expressed miRNAs (DEmiRNAs) were included in the ceRNA network between TNBC and nTNBC subtypes. Gene ontology analysis of mRNAs coexpressed with prognostic candidate lncRNAs (AC104472.1, PSORS1C3, DSCR9, OSTN-AS1, AC012074.1, AC005035.1, SIAH2-AS1, and ERVMER61-1) were utilized for functional prediction. Consequently, OSTN-AS1 was primarily related to immunologic function, for instance, immune cell infiltration and immune-related markers coexpression. The GSVA deviation degree was increased with OSTN increased expression. In addition, many important immune molecules, such as PDCD1 and CTLA-4, were strongly correlated in terms of their quantitative expression. Competing endogenous RNA networks may identify candidate therapeutic targets and potential prognostic biomarkers in breast cancer. In particular, OSTN-AS1 serves as a novel immune-related molecule and could be involved in immunotherapy efforts in the future.
竞争性内源性RNA(ceRNA)网络是研究癌症的一种有效方法;然而,此前尚未在不同亚型的乳腺癌之间构建ceRNA网络。基于对从TCGA数据库下载的150例三阴性乳腺癌(TNBC)组织和823例非三阴性乳腺癌(nTNBC)组织之间差异表达RNA的分析,使用Cytoscape通过数据库比较构建了一个ceRNA网络。结合生存分析和受试者工作特征曲线数据筛选出预后候选基因,随后使用共表达功能相关分析、基因集变异分析(GSVA)通路相关分析以及免疫浸润和肿瘤突变负担免疫相关分析对这些基因进行分析。TNBC和nTNBC亚型之间的ceRNA网络共纳入了190个差异表达的长链非编码RNA(DElncRNAs)、48个差异表达的信使RNA(DEmRNAs)和13个差异表达的微小RNA(DEmiRNAs)。对与预后候选长链非编码RNA(AC104472.1、PSORS1C3、DSCR9、OSTN-AS1、AC012074.1、AC005035.1、SIAH2-AS1和ERVMER61-1)共表达信使RNA进行基因本体分析以进行功能预测。因此,OSTN-AS1主要与免疫功能相关,例如免疫细胞浸润和免疫相关标志物共表达。随着OSTN表达增加,GSVA偏差程度升高。此外,许多重要的免疫分子,如程序性死亡受体1(PDCD1)和细胞毒性T淋巴细胞相关蛋白4(CTLA-4),在定量表达方面高度相关。竞争性内源性RNA网络可能识别出乳腺癌的候选治疗靶点和潜在预后生物标志物。特别是,OSTN-AS1作为一种新型免疫相关分子,未来可能参与免疫治疗研究。