Table_2_lncRNA OSTN-AS1 May Represent a Novel Immune-Related Prognostic Marker for Triple-Negative Breast Cancer Based on Integrated Analysis of a ceRNA Network.docx

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.

内源竞争RNA（competing endogenous RNA，ceRNA）网络是研究癌症的有效手段，但此前尚未开展针对乳腺癌不同亚型的ceRNA网络构建工作。本研究基于从癌症基因组图谱（TCGA）数据库下载的150份三阴性乳腺癌（triple-negative breast cancer，TNBC）组织与823份非三阴性乳腺癌（non–triple-negative breast cancer，nTNBC）组织的差异表达RNA分析结果，借助Cytoscape软件通过数据库比对构建了ceRNA网络。结合生存分析与受试者工作特征曲线（receiver operating characteristic curve，ROC）数据筛选出预后候选基因，随后对这些候选基因开展共表达功能关联分析、基因集变异分析（Gene Set Variation Analysis，GSVA）通路关联分析，以及免疫浸润与肿瘤突变负荷免疫相关分析。TNBC与nTNBC亚型间的ceRNA网络共包含190个差异表达长链非编码RNA（differentially expressed lncRNAs，DElncRNAs）、48个差异表达信使RNA（differentially expressed mRNAs，DEmRNAs）以及13个差异表达微小RNA（differentially expressed miRNAs，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及ERVMER61-1）共表达的信使RNA进行基因本体（Gene Ontology，GO）分析以实现功能预测。结果显示，OSTN-AS1主要与免疫功能密切相关，例如免疫细胞浸润及免疫标志物共表达等过程；随着OSTN表达水平升高，GSVA分析的偏差程度也随之增加。此外，PDCD1、CTLA-4等诸多重要免疫分子的表达量均呈现显著相关性。本研究表明，内源竞争RNA网络可用于筛选乳腺癌的候选治疗靶点与潜在预后生物标志物，其中OSTN-AS1作为一种新型免疫相关分子，有望在未来的肿瘤免疫治疗中发挥应用价值。