Abstract
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.
Highlights
Breast cancer is the most commonly diagnosed cancer among women worldwide (Bray et al, 2018)
According to gene ontology (GO) analysis of coexpressed mRNAs that strongly correlated with candidate long noncoding RNA (lncRNA), we found that the biological functions of OSTN-AS1 were significantly associated with immunity and metabolism
According to the probe annotation information from the Ensemble database, 19,676 mRNAs and 14,447 lncRNAs were separated from gene count expression matrix and downloaded from the Cancer Genome Atlas (TCGA) database
Summary
Breast cancer is the most commonly diagnosed cancer among women worldwide (Bray et al, 2018). Triple-negative breast cancer (TNBC) comprises approximately 15% of all breast tumors and is characterized by a lack of ER, PR, and ERBB2 expression, which conveys a higher risk of distant metastasis compared to the other two subtypes, collectively referred to as non–triple-negative breast cancer (nTNBC) (Foulkes et al, 2010). In addition to surgical treatment and radiation for local therapy, nTNBC can be treated using hormone-dependent endocrine therapy or molecular-targeted therapy based on molecular marker to reduce the risk of recurrence and improve overall survival rate, while TNBC lacks this corresponding systemic therapy to increase treatment efficacy (Joensuu et al, 2006; Whelan et al, 2010; Early Breast Cancer Trialists’ Collaborative Group, 2011). With the development of molecular sequencing methodology, it has become highly efficient to explore correlations between molecular markers and prognosis among different tumor types
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