Abstract
Circular RNA (circRNA) is closely related to tumorigenesis and cancer progression. Yet, the roles of cancer-specific circRNAs in the circRNA-related ceRNA network of breast cancer (BRCA) remain unclear. The aim of this study was to construct a ceRNA network associated with circRNA and to explore new therapeutic and prognostic targets and biomarkers for breast cancer. We downloaded the circRNA expression profile of BRCA from Gene Expression Omnibus (GEO) microarray datasets and downloaded the miRNA and mRNA expression profiles of BRCA from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed circRNAs (DEcircRNAs) were identified, and a competitive endogenous RNA (ceRNA) regulatory network was constructed based on circRNA–miRNA pairs and miRNA–mRNA pairs. Gene ontology and pathway enrichment analyses were performed on mRNAs regulated by circRNAs in ceRNA networks. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network were performed. A total of 72 DEcircRNAs, 158 DEmiRNAs, and 2762 DE mRNAs were identified. The constructed ceRNA network contains 60 circRNA–miRNA pairs and 140 miRNA–mRNA pairs, including 40 circRNAs, 30 miRNAs, and 100 mRNAs. Functional enrichment indicated that DEmRNAs regulated by DEcircRNAs in ceRNA networks were significantly enriched in the PI3K-Akt signaling pathway, microRNAs in cancer, and proteoglycans in cancer. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network showed that 13 mRNAs and 6 miRNAs were significantly associated with overall survival, and 48 miRNA–mRNA interaction pairs had a significant negative correlation. A PPI network was established, and 21 hub genes were determined from the network. This study provides an effective bioinformatics basis for further understanding of the molecular mechanisms and predictions of breast cancer. A better understanding of the circRNA-related ceRNA network in BRCA will help identify potential biomarkers for diagnosis and prognosis.
Highlights
Breast cancer is one of the most common cancers among women worldwide [1], with strong invasiveness and a high incidence of metastasis [2]
We performed a correlation analysis of miRNA–mRNA pairs in the competitive endogenous RNA (ceRNA) network based on R software, and the results showed that there were 48 miRNA-mRNA pairs with a strong negative correlation (r < −0:3, P < 0:001) (Table 2)
We have found that specific circRNAs in this ceRNA network, such as hsa_circ_0000376, hsa_circ_ 0000069, hsa_circ_0000520, hsa_circ_0008365, and hsa_circ_0000511 have been reported as potential diagnostic markers in certain cancers. hsa_circ_0000376 is highly expressed in gastric cancer tissues [20], and there are reports that it is involved in the occurrence of breast cancer [21]
Summary
Breast cancer is one of the most common cancers among women worldwide [1], with strong invasiveness and a high incidence of metastasis [2]. Breast cancer treatments include surgery, radiation therapy, endocrine therapy, chemotherapy, and biotargeted therapy. The recurrence rate and drug resistance in some patients are still high, and the therapeutic effect and prognosis of breast cancer are not satisfactory. Breast cancer’s molecular pathogenesis needs to be further explored, and the identification of new candidate therapeutic targets and biomarkers is urgently needed. Bioinformatics analysis has been widely applied in oncology to identify genetic changes and new potential biomarkers associated with cancer [3]. In the past few decades, 70%-90% of the transcribed human genome has been searched.
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