Compelling evidence has demonstrated the potential functions of circular RNAs (circRNAs) in breast cancer (BC) tumorigenesis. Nevertheless, the underlying mechanism by which circRNAs regulate BC progression is still unclear. The purpose of present research was to investigate the novel circRNA circRNF20 (hsa_circ_0087784) and its role in BC. CircRNA microarray sequencing revealed that circRNF20 was one of the upregulated transcripts in BC samples. Increased circRNF20 level predicted the poor clinical outcome in BC specimens. Functionally, circRNF20 promoted the proliferation and Warburg effect (aerobic glycolysis) of BC cells. Mechanistically, circRNF20 harbor miR-487a, acting as miRNA sponge, and then miR-487a targeted the 3'-UTR of hypoxia-inducible factor-1α (HIF-1α). Moreover, HIF-1α could bind with the promoter of hexokinase II (HK2) and promoted its transcription. In conclusion, this finding illustrates the vital roles of circRNF20 via the circRNF20/ miR-487a/HIF-1α/HK2 axis in breast cancer progress and Warburg effect, providing an interesting insight for the BC tumorigenesis.

Tumor necrosis factor α-induced protein 8-like-1 (TIPE1) functions as an activator or a repressor in a tumor cell type-specific manner. However, the role of TIPE1 in breast cancer, especially regarding metastasis, is unknown. In this study, we aimed to investigate the TIPE1 expression in breast cancer tissues, the biological functions, and the underlying mechanisms of TIPE1 regarding the metastatic properties of breast cancer cells. The results of immunohistochemical staining and western blot analysis indicated that TIPE1 expression was associated with tumor size and lymph node metastasis, and the expression of TIPE1 was downregulated in the tissues of patients with lymph node metastasis. Transwell and wound healing assay results showed that TIPE1 inhibited the invasive and migratory capacities of breast cancer cells. Moreover, the epithelial-mesenchymal transition (EMT) was suppressed in TIPE1-overexpressing cells, as demonstrated by western blot analysis. In addition, western blot analysis also showed that TIPE1 reduced the expression levels of MMP2 and MMP9 and decreased the phosphorylation level of ERK. These results suggested that TIPE1 might suppress the invasion and migration of breast cancer cells and inhibit EMT primarily via the ERK signaling pathway. Our findings revealed the anti-tumor metastasis role of TIPE1 in breast cancer and TIPE1 might be a new candidate prognostic indicator and a potential molecular target for the treatment of breast cancer.

Background This study intended to determine important genes related to the prognosis and recurrence of breast cancer. Methods Gene expression data of breast cancer patients were downloaded from TCGA database. Breast cancer samples with recurrence and death were defined as poor disease-free survival (DFS) group, while samples without recurrence and survival beyond 5 years were defined as better DFS group. Another gene expression profile dataset (GSE45725) of breast cancer was downloaded as the validation data. Differentially expressed genes (DEGs) were screened between better and poor DFS groups, which were then performed function enrichment analysis. The DEGs that were enriched in the GO function and KEGG signaling pathway were selected for cox regression analysis and Logit regression (LR) model analysis. Finally, correlation analysis between LR model classification and survival prognosis was analyzed. Results Based on the breast cancer gene expression profile data in TCGA, 540 DEGs were screened between better DFS and poor DFS groups, including 177 downregulated and 363 upregulated DEGs. A total of 283 DEGs were involved in all GO functions and KEGG signaling pathways. Through LR model screening, 10 important feature DEGs were identified and validated, among which, ABCA3, CCL22, FOXJ1, IL1RN, KCNIP3, MAP2K6, and MRPL13, were significantly expressed in both groups in the two data sets. ABCA3, CCL22, FOXJ1, IL1RN, and MAP2K6 were good prognostic factors, while KCNIP3 and MRPL13 were poor prognostic factors. Conclusion ABCA3, CCL22, FOXJ1, IL1RN, and MAP2K6 may serve as good prognostic factors, while KCNIP3 and MRPL13 may be poor prognostic factors for the prognosis of breast cancer.

The main treatment of breast cancer includes surgical resection, radiotherapy, chemotherapy, endocrine therapy, and molecular targeted therapy, but the outcomes remain unsatisfactory. Previous studies demonstrated that echinacoside, microRNA (miRNA/miR)-4306 and miR-4508 were associated with lymph node metastasis, chemoresistance and self-renewal capability in breast cancer, but in-depth studies on the underlying mechanism of their anticancer effects have not been performed to date. In order to identify the role of miR-4306 and miR-4508, and the mechanism of the antitumor effect of echinacoside in breast cancer, the present study first examined the expression of miR-4306 and miR-4508 in breast cancer tissues to examine their possible role in the development of breast cancer, then evaluated the effect of echinacoside on the expression of miR-4306 and miR-4508 on the viability, apoptosis, cell cycle, migration, and invasion abilities of breast cancer cells to explore the anti-cancer effect of echinacoside and the involvement of miR-4306 and miR-4508. Finally, the breast cancer cells and mice bearing breast cancer xenografts were treated with echinacoside and inhibitors of miR-4508 or miR-4306 to confirm their role on the anticancer effect of echinacoside. The results showed that miR-4306 and miR-4508 were decreased in breast cancer tissues and cells. Echinacoside inhibited cell proliferation, invasion and migration, and promoted the apoptosis of breast cancer cells by downregulating the expression of miR-4306 and miR-4508. In conclusion, this is the first study to show the association between echinacoside and miRNAs in cancer. The present study elucidates an underlying molecular mechanism of the antitumor effect of echinacoside on breast cancer, and thus may contribute to preventive and therapeutic strategies for breast cancer.

Background Copy number variation (CNVs) is a key factor in breast cancer development. This study determined prognostic molecular characteristics to predict breast cancer through performing a comprehensive analysis of copy number and gene expression data. Methods Breast cancer expression profiles, CNV and complete information from The Cancer Genome Atlas (TCGA) dataset were collected. Gene Expression Omnibus (GEO) chip data sets (GSE20685 and GSE31448) containing breast cancer samples were used as external validation sets. Univariate survival COX analysis, multivariate survival COX analysis, least absolute shrinkage and selection operator (LASSO), Chi square, Kaplan-Meier (KM) survival curve and receiver operating characteristic (ROC) analysis were applied to build a gene signature model and assess its performance. Results A total of 649 CNV related-differentially expressed gene obtained from TCGA-breast cancer dataset were related to several cancer pathways and functions. A prognostic gene sets with 9 genes were developed to stratify patients into high-risk and low-risk groups, and its prognostic performance was verified in two independent patient cohorts (n = 327, 246). The result uncovered that 9-gene signature could independently predict breast cancer prognosis. Lower mutation of PIK3CA and higher mutation of TP53 and CDH1 were found in samples with high-risk score compared with samples with low-risk score. Patients in the high-risk group showed higher immune score, malignant clinical features than those in the low-risk group. The 9-gene signature developed in this study achieved a higher AUC. Conclusion The current research established a 5-CNV gene signature to evaluate prognosis of breast cancer patients, which may innovate clinical application of prognostic assessment.