Background
Breast cancer (BC) is the most common female malignancy and is a major cause of cancer-related mortality in the US [
1]. Despite improvements in diagnostics and therapeutic strategies for BC in recent decades, the prognosis and long-term survival of BC patients remains poor, which attribute to the molecular heterogeneity, high metastatic characteristics, and low detection rate of BC [
2]. Therefore, it is important to explore new molecular biomarkers with high specificity and sensitivity of BC detection and treatment.
N6-methyladenosine (m6A) modification, the methylation of the adenosine base at the nitrogen-6 position of mRNA, is the most prevalent, abundant, and conserved internal co-transcriptional modification in eukaryotes. The impacts of m6A on RNA are determined by the dynamic interactions between m6A RNA methylation modulators, including m6A methyltransferases (writers), binding proteins (readers), and demethylases (erasers) [
3]. Generally speaking, m6A is installed by methyltransferase complex that functions as m6A writers, consisting of METTL3, METTL14, RBM15, and ZC3H13 [
4]. The m6A erasers, such as FTO, ALKBH3, and ALKBH5, are able to remove m6A modification to balance methylation and demethylation [
5]. Furthermore, the reversible m6A modification also depends on the recognition by m6A-binding proteins, namely the YTH domain-containing family of proteins, which is denoted as readers [
6,
7]. Emerging evidence indicates that m6A modifications are closely associated with tumorigenesis, tumor proliferation, differentiation, metastasis, and poor prognosis [
8]. The writers, erasers, and readers of m6A RNA modification engage in the tumorigenesis and progression of BC. These BC-specific m6A modulators are potentially useful for serving as prognosis and therapy targets.
Circular RNAs (CircRNAs) are single-stranded RNA molecules, lacking a 5-prime cap and 3-prime poly-A tail and joining head to tail to create a covalently closed loop structure via back-splicing [
9]. In BC, the most studied function of circRNA is acting as tumor promoters or suppressors by miRNA sponges. Besides, emerging studies have identified the roles of circRNAs serving as miRNA sponges in the regulation of m6A RNA methylation modulators in various cancers, including hepatocellular carcinoma [
10], gastric cancer [
11], and adrenocortical carcinoma [
12]. However, few studies have comprehensively investigated roles in the interaction of circRNAs and m6A in BC. The identification of circRNA regulatory network related to m6A RNA methylation modulators will undoubtedly provide key clues for mechanism discovery and therapeutic targets for BC.
In the present study, we identified differentially expressed (DE) prognostic m6A RNA methylation modulators, circRNAs, and miRNAs between BC samples and normal tissues from The Cancer Genome Atlas (TCGA) projects and Gene Expression Omnibus (GEO) database, and then constructed the circRNA-miRNA-mRNA regulatory network. Based on the clinical characteristics and co-expression patterns of miRNA-m6A RNA modulators, it was speculated that BC patients with high expression of hsa-miR-944 and low expression of HNRNPC were significantly concerned with longer survival times than control. Importantly, circBACH2, also known as hsa_circ_0001625, was further confirmed to promote BC cell proliferation via acting as hsa-miR-944 sponge to regulate HNRNPC expression. Moreover, the circBACH2/hsa-miR-944/HNRNPC axis accelerated BC progression via the MAPK signaling pathway-dependent manner. Undoubtedly, these findings shed new light on how circRNAs regulate m6A RNA methylation modulators by directly binding to miRNAs, thereby providing new perspectives for the development of clinical diagnostic and therapeutic strategies against BC.
Methods
Data collection and processing of BC datasets
Identification of DE genes
From previous studies, a total of 21 m6A methylation regulators were selected for identification [
3,
13], and 17 m6A methylation regulators between 1065 BC patients and 112 normal samples were finally confirmed by Mann–Whitney-Wilcoxon Test according to the available mRNA expression data from TCGA. The prognostic value of the m6A RNA methylation modulators was further assessed by univariate Cox regression survival analyses and Lasso Cox regression analysis, and those DE modulators were identified as components of the following network construction. The R package “Bioconductor Limma” was used to screen out DE miRNAs between 1057 BC and 103 normal samples in TCGA. Benjamini Hochberg method was used to calculate the adjusted P value (false discovery rate, FDR) of each gene and the threshold for DE miRNAs selection was set to FDR < 0.05 and |log
2FC|> 1. The DE circRNAs between 8 BC and 3 normal cases were evaluated by a rank aggregation method in GSE101123. Both DE miRNAs and circRNAs were further visualized via heatmap.
Construction of circRNA-miRNA-m6A RNA methylation modulator regulatory network
MiRDIP (
http://ophid.utoronto.ca/mirDIP/) and Circular RNA Interactome (
https://circinteractome.nia.nih.gov/) were used respectively to predict miRNA-m6A RNA methylation modulators interactive pairs and circRNA-miRNA interactive pairs. The miRNA-m6A modulators interactive pairs were selected after taking the intersection between the potential miRNAs targeting m6A RNA methylation regulators with the very high score (top 1%) in miRDIP and the miRNAs DE in BC tissues from TCGA project. Finally, a circRNA-miRNA-mRNA regulatory network was further constructed by taking the intersection of miRNA-m6A modulators interactive pairs and circRNA-miRNA interactive pairs.
Gene set enrichment analysis (GSEA), the Kyoto Encyclopedia of Genes and Genomes (KEGG) and single-sample gene set enrichment analysis (ssGSEA)
The 1178 BC samples from TCGA were divided into HNRNBC high- and low-expression groups respectively, which were further analyzed by GSEA (
http://software.broadinstitute.org/gsea/index.jsp) to compare the potential biological pathways and illuminate the potential regulatory mechanisms. The gene set list c5.go.bp.v7.4.symbols.gmt, c5.go.cc.v7.4.symbols.gmt, c5.go.mf.v7.4.symbols.gmt, c2.cp.kegg.v7.4.symbols.gmt were utilized as the reference gene set. The threshold was defined as nominal P < 0.05. According to the existing literature reports [
14‐
16], some biological processes and signaling pathways closely related to BC were selected for visualization. R software (4.0.1 version) was used for KEGG pathway enrichment analyses to investigate potential differential pathways between HNRNPC high and low expression groups. To evaluate the potential immune regulatory role of HNRNPC in the BC immune infiltrations and functions, the “gsva” package was used to perform the ssGSEA to calculate the scores of infiltrating immune cells and to evaluate the activity of immune-related pathways.
Cell culture and transfection
The human BC cell lines, MCF-7 and MDA-MB-231 were obtained from American Type Culture Collection (Manassas, VA, USA) and cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% (v/v) fetal bovine serum (Gibco) at 5% CO
2 at 37 °C. HNRNPC siRNA, hsa-miR-944 inhibitors, circBACH2 siRNA, and their corresponding negative control were purchased from Ribobio (Wuhan, China). The cells in 6 well plates were transfected with 50 nM inhibitors or siRNA by using Lipofectamine 3000 reagent (Invitrogen) according to the manufacturer’s instructions. The specific siRNA sequences for HNRNPC were provided in Additional file
1: Table S1. Three independent experiments were performed for cell transfection.
Cell proliferation assay
Cell proliferation assay was measured using the Cell Counting Kit-8 (CCK-8) (Dojindo, Kumamoto, Japan) and 5-ethynyl-2′-deoxyuridine (EdU) incorporation assay (RiboBio, Wuhan, China) kits. In the CCK-8 assay, the transfected cells were seeded in 96-well plates at a density of 2 × 103/well. Cell viability was detected from 12 to 72 h by directly adding CCK-8 reagent to each well. Finally, the optical density (OD) was recorded at a wavelength of 450 nm by a microplate reader (BioTek Instruments, United States). In the EdU assay, the BC cells were incubated with a medium containing 50 µM EdU for 2 h. After being fixed in 4% paraformaldehyde for 30 min, the BC cells were stained in Apollo reaction cocktail and Hoechst 33,342 respectively. The ratio of proliferating cells (EdU positive) to the total number of cells (DAPI positive) was observed by using a fluorescence microscope (IX35, Olympus, Japan). All the results were performed in three independent experiments.
Quantitative real-time polymerase chain reaction (qRT-PCR) analysis
TRIzol reagent kit (Invitrogen) was performed to isolate total RNA from BC cells. The concentration and purity of total RNA were evaluated using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, United States). The complementary DNA (cDNA) was synthesized by using the PrimeScript RT kit (Takara, Japan) at 103 °C for 5 s, 37 °C for 10 min, and 4 °C for 15 min. The primer sequences for detection were provided in Additional file
1: Table S2. The expression level of GAPDH was used as an internal standard control. All the gene expression levels were collected and quantified using the 2
−△△Ct method. The results were gained from three independent experiments.
Western blot
Total proteins were extracted using radio-immunoprecipitation assay (RIPA) (Boster, Wuhan, China) and a bicinchoninic acid (BCA) protein assay kit (Boster, Wuhan, China) was used to estimate the protein concentration. The protein extract electrophoresed in a 10% sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) at 80 V for 20 min and then 120 V for 1 h and then transferred to PVDF membranes (Biosharp, Shanghai, China) at 220 mA for 60 min. After repeated washing using tris-buffered saline containing Tween 20 (TBST) and blocking with 5% bull serum albumin (BSA) blocking buffer for 2 h at 37 °C, the PVDF membranes were incubated with primary antibodies anti-HNRNPC (1:4000), anti-GAPDH (1:5000), p-ErK(1:1500), t-Erk (1:1500), t-MAPK (1:1000) and p-MAPK (1:1500) overnight at 4 °C and then incubated with the secondary antibody of HRP-linked antibody (1:5,000, Abcam, Cambridge, MA, United States) for 1 h at 37 °C. Finally, the blots were visualized using the enhanced chemiluminescence (ECL) detection kit (Yeasen, Shanghai, China), and the relative protein abundance was measured by ImageJ image analysis software (version 1.44p, National Institutes of Health, United States). All primary antibodies were purchased from Proteintech, Wuhan, China.
Statistical analysis
All statistical analysis was carried out by using R version 4.0.5 and GraphPad Prism 8.0. Mann–Whitney U test was used to compare the expression differences of the m6A RNA methylation regulators were compared between tumor tissues and normal tissues. The differences between the two subgroups were assessed via Student’s t-test. The independent prognostic value and other clinical characteristics were estimated by univariate and multivariate Cox proportional hazard regression analyses. Pearson correlation analyses were performed to evaluate the associations between two variables. P < 0.05 was thought to be statistically significant.
Discussion
Tumorous cells undergo genetic and epigenetic changes to obtain malignant transformation, including the modifications of mRNA transcripts. Among them, the m6A modification emerges as one of the most abundant RNA modifications in eukaryotic cells, involving RNA processing, nuclear export, and RNA translation. There is accumulating evidence indicating that m6A methylation affects the complexity of multiple cancer progression and thus plays important role in cancers. In this study, we focused on m6A-associated mechanisms and functions in BC, and presumed and validated the potential role of the circRNA-miRNA network in regulating m6A RNA methylation modulators in BC progression. In this work, we have constructed a circRNA- and m6A- based interaction network of circBACH2/hsa-miR-944/HNRNPC axis in BC. The hsa-miR-944/HNRNPC axis was determined to be associated with clinicopathological characteristics and prognosis of BC. More importantly, circMAP2K4 could sponge the hsa-miR-944 and subsequently counteract the inhibition effect of hsa-miR-944 on HNRNPC expression, which ultimately boosts the BC proliferation and progression.
In our study, RBM15B, HNRNPC, YTHDF3 and ZC3H13 were the eventually identified modulators of m6A RNA methylation based on their differential expression and prognostic values in the TCGA projects. And finally, HNRNPC was used to construct the interacting network. It is noted that m6A RNA methylation regulators impact the BC prognosis. Wang et al. reported that the m6A methylation regulators were observably dysregulated in TNBC tissues, including up-regulated KIAA1429, YTHDF2, RBM15, and down-regulated ZC3H13, METTL14, and FTO [
19]. These altered regulators constituted a meaningful prognostic signature for predicting survival of TNBC patients [
20]. By bioinformatic analysis, Gong et al. showed that the expressions of METTL14 and ZC3H13 mRNA were down-regulated in BC, and indicated their synergetic roles in regulating BC cell proliferation, invasion, and metastasis [
21]. As a m6A reader, YTHDF3 was overexpressed and clinically correlated with breast cancer brain metastases (BCBM), suggesting that YTHDF3 overexpression was indispensable for multiple steps of BCBM through facilitating ST6GALNAC5, GJA1, EGFR, and VEGFA expressions [
22]. Anita et al. also verified that the genetic alterations of YTHDF3 were frequently associated with poor prognosis in BC patients, suggesting their transcripts upregulation might promote BC progression via a m6A-dependent manner [
23]. The RNA-binding protein HNRNPC is highly expressed and can suppress the accumulation of immunostimulatory RNAs in BC cells [
24]. Our results also showed that HNRNPC was a highly expressed m6A RNA methylation regulator in BC. These alterations in the m6A proteins that write, recognize or erase the m6A could lead to extensive transformation in multiple cellular processes and play critical roles in the pathogenesis of BC.
Dysfunction of miRNAs is a typical repertoire in cancer and is strongly emphasized to implicate in the pathogenesis and tumorigenicity of BC. Recently, miR-944 has been reported to possess multi-faceted characteristics in playing either oncogenic or tumor-suppressive roles in various human malignancies. For example, miR-944 may function as a tumor suppressor to inhibit colorectal cancer (CRC) by regulating GATA6, and their expression level was negatively associated with the pathological manifestation of CRC [
25]. But in BC, it was reported that miR-944 was confirmed as an oncogene to mediate the chemoresistance of BC [
26]. Conversely, Flores-Pérez et al. demonstrated that miR-944 was markedly suppressed in BC cell lines and tumors independent of hormonal status and stage, and could inhibit BC cell migration and invasion [
26]. Whereas in our study, miR-944 emerged as a cancer suppressor gene to restrain the HNRNPC. This result is consistent with the study of Flores-Pérez. Due to the limited studies, the underlying roles and mechanisms of miR-944 on BC need to be further confirmed.
CircRNAs are ubiquitous non-coding RNAs in eukaryotic cells, which are diverse, stable, and evolutionarily conserved. It is gradually recognized that circRNA is dysregulated in BC tissues and participated in the pathogenesis of BC by harboring miRNAs [
27]. For instance, Yang et al. successfully identified a total of 47 upregulated and 307 downregulated DE circRNAs to construct the competing endogenous RNA (ceRNA) network of BC [
28]. Additionally, the upregulated circAGFG1 was associated with accelerated cell division and poor prognosis involving the circRNA-miRNA-hub gene network in the pathogenesis of BC.
However, although in the past few years, many studies have attempted to decipher the properties of expression abundance, functions, and mechanism of m6A RNA methylation regulators and their interaction with miRNAs in BC, the interaction of circRNA involved in the interaction of miRNAs and modulators are remain not very clear. Besides, few studies have reported the function of the circRNA-miRNAs-m6A axis in BC, regardless of BC stage or type. This inspired us to explore the potential correlation between the circRNA and m6A modification. CircBACH2 was the screened and selected circRNA target, which was proved to be up-regulated in TNBC cancerous tissues and was associated with malignant progression in patients with TNBC [
17]. Mechanistically, the abnormally expressed circBACH2 acted as an oncogenic circRNA in TNBC via miR-186-5p and miR-548c-3p/CXCR4 axis. Interestingly, Cai et al. also investigated the function of circBACH2 in papillary PTC, and found that circBACH2 could bind to miR-139-5p to serve as a pro-tumorigenic RNA through a circBACH2/miR-139-5p/LMO4 axis in PTC [
18]. Here, we confirmed that circBACH2 was able to promote BC cell proliferation by combining with hsa-miR-944 to promote HNRNPC expression, thus establishing a circRNA-miRNA-mRNA regulatory network in BC. Meanwhile, our results were also consistent with previous reports that circBACH2 functioned as an oncogene in BC development. Besides, the MAPK signaling pathway is known to regulate various cellular activities related to cancer progression including proliferation, differentiation, apoptosis, and immune escape [
29]. According to relevant literature reports, the BC cell stemness and metastasis could be increased via activating the MAPK pathway [
30,
31]. Notably, non-coding RNAs have emerged as potential vital regulators in BC progression. For example, miR-188 inhibited BC cell migration and promoted apoptosis by suppressing the activation of the MAPK signaling pathway to negatively regulate Rap2c [
32]. Therefore, the MAPK/ERK pathway was selected to investigate how the circBACH2/hsa-miR-944/HNRNPC axis promoted BC cell proliferation. Western blot analysis suggested that the protein phosphorylation levels of ErK and MAPK in BC cells were increased after transfection with hsa-miR-944 inhibitors, while the above stimulative effects could be reversed by circBACH2 siRNAs. The results unveiled that the overexpression of circBACH2 could promote phosphorylation of the MAPK signaling pathway. Thus, we propose that circBACH2 mediated stimulation of BC cell proliferation via activating the MAPK signaling pathway by acting as the hsa-miR-944 sponge to promote HNRNPC expression. All of these results uncovered a novel tumor-boosting mechanism in BC, indicating that the circBACH2/hsa-miR-944/HNRNPC axis may serve as a promising therapeutic target in BC patients.
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