E2F1 transcriptionally regulates CCNA2 expression to promote triple negative breast cancer tumorigenicity

Abstract

BACKGROUND:

Triple-negative breast cancer (TNBC) is a highly malignant breast cancer subtype with a poor prognosis. The cell cycle regulator cyclin A2 (CCNA2) plays a role in tumor development. Herein, we explored the role of CCNA2 in TNBC.

METHODS:

We analyzed CCNA2 expression in 15 pairs of TNBC and adjacent tissues and assessed the relationship between CCNA2 expression using the tissue microarray cohort. Furthermore, we used two TNBC cohort datasets to analyze the correlation between CCNA2 and E2F transcription factor 1 (E2F1) and a luciferase reporter to explore their association. Through rescue experiments, we analyzed the effects of E2F1 knockdown on CCNA2 expression and cellular behavior.

RESULTS:

We found that CCNA2 expression in TNBC was significantly higher than that in adjacent tissues with similar observations in MDA-MB-231 and MDA-MB-468 cells. E2F1 was highly correlated with CCNA2 as observed through bioinformatics analysis ( $R=$ 0.80, $P<$ 0.001) and through TNBC tissue verification analysis ( $R=$ 0.53, $P<$ 0.001). We determined that E2F1 binds the $+$ 677 position within the CCNA2 promoter. Moreover, CCNA2 overexpression increased cell proliferation, invasion, and migration owing to E2F1 upregulation in TNBC.

CONCLUSION:

Our data indicate that E2F1 promotes TNBC proliferation and invasion by upregulating CCNA2 expression. E2F1 and CCNA2 are potential candidates that may be targeted for effective TNBC treatment.

Keywords

TNBC E2F1 CCNA2 tumorigenicity

1. Introduction

The latest data show that breast cancer is the most common cancer worldwide, and it is the primary cause of cancer-related deaths among women [1, 2]. Breast cancer incidence and mortality rank first among all cancers, respectively, with 2.3 million new cases and 0.68 million deaths [1]. Triple-negative breast cancer (TNBC) is characterized by a lack of expression of the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). This breast cancer subtype is highly proliferative and associated with a poor prognosis, accounting for approximately 15–20% of all breast cancers [3]. Although many molecular biomarkers have been found [4], TNBC lacks effective therapeutic targets, and its treatment is still primarily based on radiotherapy and chemotherapy [5]. Therefore, there is an urgent need to find potential and effective molecular therapeutic targets for TNBC.

The cell cycle controls proliferation and plays an important role in the early stage of DNA synthesis (G1 stage), the DNA synthesis stage (S stage), the late DNA synthesis stage (G2 stage), and the division stage (M stage); notably, misregulation of this process can contribute to cancer occurrence and development [6, 7]. Cyclin A2 (CCNA2) is a core component of the cell cycle and is abnormally expressed in cervical, colorectal, and breast cancers, thereby affecting cell proliferation [6, 8, 9]. Previously, we found that CCNA2 is highly expressed in TNBC tissues based on bioinformatics analysis [10]. Some studies have found that the transcription factors E2F4 and GATA3 have direct binding sites for CCNA2 [11, 12].

Transcriptional regulation is very important in cancer progression. The E2F transcription factor family proteins, including E2F1, play an important role in controlling cell cycle progression as well as in promoting proliferation and tumorigenesis [13]. Lu et al. [14] found that the LINC00511/miR-185-3p/E2F1/Nanog axis can promote breast cancer tumorigenesis. Recent findings from Xiong et al. [3] confirmed that ABP32E induces TNBC, a process regulated by the expression of E2F1. Furthermore, higher E2F1 expression levels are often observed in breast cancer tissues than in normal tissues [15]. Therefore, E2F1 plays a key role in the occurrence and development of TNBC. Interestingly, the expression levels of E2F1 and cyclin A2 were downregulated in MSK2-depleted cervical cancer cells [16]. In hepatocellular carcinoma cells, E2F1 reduces the hyperphosphorylation level of cyclin A2 mRNA pRb, leading to a decrease in the number of cells in the S-phase and promoting the occurrence and development of liver cancer [17]. However, the relationship between E2F1 and CCNA2 and whether E2F1 mediates the transcriptional regulation of CCNA2 to promote TNBC progression have not been fully elucidated.

How CCNA2 promotes the progression of TNBC is our core concern. Here, we found that CCNA2 expression promoted the proliferation of TNBC cells through a series of in vivo and in vitro experiments. Our results showed that CCNA2 expression was highly correlated with E2F1. Notably, we revealed that E2F1 could promote CCNA2 expression through an interaction with the CCNA2 promoter at $+$ 677-position in TNBC cells. Finally, we demonstrated that E2F1 promoted cell proliferation and inhibited apoptosis via rescue experiments. Taken together, our data uncovered the important role of E2F1 and its mechanism in promoting TNBC proliferation, and our results might provide theoretical support for the treatment of TNBC.

2. Materials and methods

2.1 Cell culture

MCF10A cells, a normal human mammary epithelial cell line, were obtained from Fuheng Company (Shanghai, China) and cultured in a special medium. Breast cancer cell lines, including HS578T, MCF-7, MDA-MB-231, and MDA-MB-468 cells, were obtained from Fuheng Company (Shanghai, China) and were cultured in DMEM supplemented with 10% fetal bovine serum (Gibco, Thermo Fisher Scientific, Waltham, MA, USA) at 37 ${{}^{\circ}}$ C.

2.2 Tissue microarray (TMA) cohorts and immunohistochemical staining

TMA cohorts containing 15 TNBC tissues and 15 adjacent tissues were obtained from the First Hospital of Lanzhou University. The study was performed with the approval of the Ethics Committee of the First Hospital of Lanzhou University. All participants agreed to participate in this study and signed an informed consent form. TMA sections were deparaffinized, hydrated, and blocked for endogenous peroxidases and antigen retrieval. After sealing for 1 h at room temperature, anti-cyclin A2 (1:50) was added, followed by incubation at 37 ${{}^{\circ}}$ C for 2 h and washing with phosphate-buffered saline (PBS). Appropriate amounts of secondary antibody were added dropwise to the sections, which were incubated at 37 ${}^{\circ}$ C for 30 min, washed with PBS, and dried. Finally, the diaminobenzidine solution was added to the sections, which were counterstained with hematoxylin and mounted.

2.3 RNA extraction and quantitative PCR (qPCR)

TRIzol reagent (Invitrogen, Carlsbad, CA, USA) was used to extract total RNA according to the manufacturer’s protocol. A NanoDrop spectrophotometer (Thermo, Rockford, IL, USA) was used to quantify the RNA. Reverse transcription was then used to synthesize cDNA. Using cDNA as the template and GAPDH as the internal reference, the expression levels of CCNA2 and E2F1 were calculated using the 2 ${}^{\rm-\Delta\Delta CT}$ method. The primer sequences are shown in Table S1.

2.4 Western blotting

Cellular proteins were extracted using lysis buffer. An equal amount of cell lysate was separated via sodium dodecyl sulfate polyacrylamide gel electrophoresis using a 10% gel and then transferred onto a polyvinylidene fluoride membrane. The membrane was blocked, incubated with the indicated primary antibody (1:200), and then incubated with a secondary antibody (1:1,000). The cyclin A2 and E2F1 antibodies were purchased from Abcam (Cambridge, MA, USA).

2.5 Cell transfection

For siRNA-mediated knockdown, cells were transiently transfected using Lipofectamine 2000 (GenePharma, Shanghai, China) according to the manufacturer’s instructions. The siRNA sequences (sense strand) are shown in Table S2. The lentiviral vector used to overexpressession and interferes with E2F1 was constructed by GenePharma.

2.6 Cell proliferation assay

The Cell Counting Kit-8 (CCK-8) assay was used to detect cell proliferation. Cell suspensions (100 $\mu$ L) were seeded in 96-well plates for 24 h. Cells transfected with CCNA2 siRNAs (CCNA2-si; 100 nM), E2F1 siRNAs (E2F1-si; 100 nM), and the negative control (100 nM) were cultured for an additional 5 days. After replacing the medium every 24 h for 5 days, enzyme-linked immunoassay was used to detect the absorbance optical density value of each well at 450 nm. Cell growth curves were drawn based on time points between 1–5 days.

2.7 Colony formation assay

MDA-MB-231 and MDA-MB-468 cells infected with CCNA2-si and E2F1-si for 72 h were seeded in a 6-well plate with 300 cells per well. Three parallel replicate wells were set up for each group, incubated at 37 ${}^{\circ}$ C, and replaced with fresh medium every 2 days. The culture medium was removed when macroscopic cell clumps formed after approximately 2 weeks and washed three times with PBS. Samples were fixed with methanol for 10 min, stained with Giemsa for 20 min, washed three times with double distilled water, and then dried. The number of clonal clumps formed was counted.

2.8 Transwell assay

Cells that were serum-starved were resuspended in serum-free medium and seeded into the upper chamber of a Transwell insert (Shanghai) with 8 $\mu$ m-pore-size filters and equipped with a basement membrane. The lower chamber was supplemented with complete medium. Cells remaining on the top side of the filter were removed with a cotton swab. The migrated cells on the bottom side of the filter were fixed with 4% paraformaldehyde, stained with 0.1% crystal violet dye, and then visually inspected. Percent cell migration was determined by counting five random fields under a microscope.

2.9 Wound healing assay

The transfected cells were seeded in a 24-well plate and cultured for 24 h. A linear wound was generated, and the cells were washed three times with PBS. Then, complete medium was added, and the cells were cultured for 36 h. Images were taken at 0 and 36 h, and the scratched area was recorded.

2.10 Cell apoptosis analysis

We used the terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) kit to detect apoptosis in TNBC tumor cells. The transfected cells were seeded on glass sheets in a 6-well plate (5 $\times$ 10 ${}^{5}$ cells/well). After the cells were cultured for 24 h, they were fixed using 4% paraformaldehyde for 25 min. After following the manufacturer’s instructions and staining the cells with 4 ${}^{\prime}$ , 6-diamidino-2-phenylindole (DAPI), TUNEL-positive signals (green) and nuclei were observed using a fluorescent microscope under 200 $\times$ magnification. The numbers of apoptotic cells and total cells from five randomly selected fields were used to calculate the rate of apoptosis.

2.11 Luciferase reporter gene assay

The CCNA2 promoter region was amplified and then subcloned into the pGL3-Basic vector (GenePharma) for the luciferase assay. The cells were co-transfected with the pGL3 vector and cultured for 48 h, and then the luciferase reporter gene detection system (Promega) was used. To further clarify the transcriptional regulation of CCNA2 via E2F1, a wild-type or mutant binding site of CCNA2 was synthesized for luciferase reporter gene analysis.

2.12 In vivo tumorigenesis in nude mice

BALB/c female nude mice (Charles River, Beijing, China) were randomly divided into two groups, with five in each group. All mice were kept in a specific pathogen-free environment. MDA-MB-468 cells in which endogenous CCNA2 was knocked down and then stably overexpressed were regarded as the CCNA2-si group. The control group was designated as the negative control (NC) group. After disinfecting the skin with alcohol, the cells were implanted into the upper abdomen of the nude mice (8 $\times$ 10 ${}^{6}$ cells/mouse), and the mice were observed for 6 weeks. Tumor weight was measured on the day the mice were sacrificed, and the tumor volume was determined using calipers. Animal experiments were approved by the ethics committee of the First Hospital of Lanzhou University. The study was performed with the approval of the Ethics Committee of the First Hospital of Lanzhou University.

2.13 Statistical analysis

All data are expressed as the mean $\pm$ standard error. Differences between two groups were compared based on a two-tailed Student’s $t$ -test. Correlation analysis was performed using the Pearson correlation coefficient. Statistical analysis was performed using Prism 8 (GraphPad Software, La Jolla, CA, USA). $P<$ 0.05 was considered statistically different as follows: ${}^{*}P<$ 0.05, ${}^{**}P<$ 0.01, and ${}^{***}P<$ 0.001. All experiments were repeated three times.

3. Results

3.1 CCNA2 is overexpressed in breast cancer based on The Cancer Genome Atlas (TCGA) database

CCNA2 mRNA level was found to be upregulated in breast cancer tissues compared with the levels in adjacent tissues based on TCGA database (Fig. 1A). Further subgroup analysis showed that the expression of CCNA2 mRNA was upregulated in different pathological stages compared to that in stage I (Fig. 1B). Multivariate Cox regression analysis showed that the prognosis of breast cancer patients with high expression of CCNA2 is poor. It was also found to be an independent risk factor for the prognosis of breast cancer patients with an HR (95% CI) of 1.20 (1.02–1.40) (Fig. 1C).

Figure 1.

Cyclin A2 (CCNA2) is overexpressed in breast cancer based on TCGA database. (A) CCNA2 mRNA is upregulated in breast cancer tissues compared with adjacent tissues. (B) The expression of CCNA2 in different pathological stages. (C) Multivariate Cox regression analysis of breast cancer prognosis.

3.2 CCNA2 is overexpressed in TNBC tissues and breast cancer cells

Cyclin A2 mRNA and protein expression levels were upregulated in 15 pairs of TNBC tissues compared to those in adjacent tissues (Fig. 2A and B). Immunohistochemistry results showed that cyclin A2 is primarily located in the nucleus; notably, the positive expression rate of cyclin A2 in TNBC tissues was significantly higher than that in adjacent tissues (Fig. 2C). Moreover, the expression levels of cyclin A2 in multiple breast cancer cell lines, including BT-20, HS578T, MDA-MB-231, and MDA-MB-468 cells, were higher than those in MCF10A cells (Fig. 2D). Interestingly, cyclin A2 was the most abundantly expressed protein in MDA-MB-231 and MDA-MB-468 cells. Therefore, these two cell lines were used for the subsequent in vitro studies.

Figure 2.

CCNA2 is overexpressed in triple negative breast cancer (TNBC). (A) CCNA2 mRNA is upregulated in TNBC tissues compared with adjacent tissues, analyzed by quantitative PCR (qPCR). (B) CCNA2 expression is higher in TNBC tissues than in adjacent tissues, analyzed by western blot (WB). (C) Correlation between immunohistochemical grading and CCNA2 expression in TNBC. (D) mRNA and protein levels in a normal cell line (MCF10A cells) and four breast cancer cell lines (HS578T, MCF-7, MDA-MB-231, and MDA-MB-468 cells) via qPCR and WB, respectively. Data were compared using a Student’s $t$ -test; ${}^{*}P<$ 0.05, ${}^{**}P<$ 0.01, and ${}^{***}P<$ 0.001.

3.3 CCNA2 expression affects the malignant biological behavior of TNBC cells

To study the biological functions of CCNA2, we generated a stable CCNA2 knockdown cell line using both MDA-MB-231 and MDA-MB-468 cells ( $P<$ 0.001) (Fig. 3A). The CCK-8 assay showed that CCNA2-si significantly inhibited TNBC cell growth, compared to the NC group ( $P<$ 0.001) (Fig. 3B). Similarly, compared with that in the control group, CCNA2 knockdown significantly decreased the number of colonies formed after 14 days of culture ( $P<$ 0.001) (Fig. 3C). Overall, these results indicate that CCNA2 promotes the proliferation of TNBC cells in vitro.

Figure 3.

CCNA2 promotes the proliferation, invasion, and migration but inhibits apoptosis of MDA-MB-231 and MDA-MB-468 cells in vitro. (A) The CCNA2 knockdown effects were confirmed via WB. Knockdown of CCNA2 inhibited (B) cell proliferation, determined using CCK-8 kit and (C) colony formation assays, in MDA-MB-231 and MDA-MB-468 cells. (D) Knockdown of CCNA2 inhibited invasion, analyzed via a transwell assay in MDA-MB-231 and MDA-MB-468 cells. (E) Knockdown of CCNA2 suppressed migration as shown via a wound-healing assay in MDA-MB-231 and MDA-MB-468 cells. (F) Knockdown of CCNA2 promoted cell apoptosis as shown with TUNEL detection in MDA-MB-231 and MDA-MB-468 cells. (G) Knockdown of CCNA2 inhibited cell cycle-related genes expression in MDA-MB-231 and MDA-MB-468 cell lines. Data were compared using a Student’s $t$ -test; ${}^{*}P<$ 0.05, ${}^{**}P<$ 0.01, and ${}^{***}P<$ 0.001.

We further investigated the metastatic ability of TNBC cells with different CCNA2 expression levels. In the transwell assay, cells treated with CCNA2-si were significantly less invasive compared to the cells in the NC group ( $P<$ 0.001) (Fig. 3D). In the wound healing assay, the wound closure area was significantly reduced in cells from the CCNA2-si group relative to that in the NC group ( $P<$ 0.001) (Fig. 3E). These results indicate that CCNA2 downregulation reduces the invasion and migration of TNBC cells in vitro.

Using the TUNEL assay, we observed that CCNA2-si promoted apoptosis in both MDA-MB-231 and MDA-MB-468 cells (Fig. 3F); moreover, the expression of cell cycle-related proteins, including SURVIVIN, CCNB1, and CCND1, was significantly reduced in the CCNA2-si group, compared to that in the NC group (Fig. 3G).

3.4 Pathway enrichment analysis in TNBC tissues

Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that upregulated differentially expressed genes (DEGs) in TNBC included those genes that are involved in the spliceosome formation, pyrimidine metabolism, and cell cycle pathways (Fig. 4A). Functional annotation was performed using representative Gene Set Enrichment Analysis (GSEA) (Fig. 4B). Among the gene sets, G2 M_CHECKPOINT, CLEE_CYCLE, and MTTOTIC_SPINDLE pathways were well established in TNBC (Fig. 4C–E).

Figure 4.

Pathway enrichment analysis in TNBC tissues. (A) KEGG analysis of TNBC. (B) Enrichment analysis of genes that target CCNA2. (C–E) Representative Gene Set Enrichment Analysis (GSEA) plots enriched in TCGA database of a TNBC group with high levels of CCNA2 expression. Data were compared using a Student’s $t$ -test; ${}^{*}P<$ 0.05, ${}^{**}P<$ 0.01, and ${}^{***}P<$ 0.001.

3.5 CCNA2 promotes cell proliferation in vivo

To investigate the effect of CCNA2 on TNBC cell proliferation in vivo, we generated MDA-MB-468 cells stably overexpressing CCNA2, which were injected subcutaneously into the upper abdomens of nude mice. The volumes and weights of tumors from the MDA-MB-468/NC cells were significantly smaller than those from the MDA-MB-468/CCNA2-si cells ( $P<$ 0.01) (Fig. 5A and B). In addition, immunohistochemical staining showed that CCNA2 downregulation inhibited the expression of Ki-67, a proliferation index marker ( $P<$ 0.01) (Fig. 5C). Overall, these findings suggest that CCNA2 promotes the tumorigenesis of TNBC in vivo.

Figure 5.

CCNA2 promotes cell proliferation in vivo. (A, B) Knockdown of CCNA2 reduces tumor weight and volume in mice. (C) CCNA2, and Ki-67 staining of subcutaneous xenograft tumors from the NC and CCNA2-si groups. Data were compared using a Student’s $t$ -test; ${}^{*}P<$ 0.05, ${}^{**}P<$ 0.01, and ${}^{***}P<$ 0.001.

3.6 CCNA2 is a transcriptional target of E2F1

GSEA plots enriched in TCGA showed that CCNA2 is a target gene of E2F1 (Fig. 6A). Results from 25 cancer databases suggested that there is a notable correlation between CCNA2 and E2F1 (Fig. 6B). We further analyzed its correlation through TCGA BRCA cohort database and found that there was a significant correlation between CCNA2 and E2F1, and the correlation coefficient was as high as 0.80 (Fig. 6C). Similarly, using our TNBC cohort, we observed a similar trend and found that CCNA2 expression significantly correlated with E2F1 ( $R=$ 0.53) (Fig. 6D). We used HOMER software to predict the binding between the CCNA2 promoter (5 ${}^{\prime}$ region GGCGCC sequence) and E2F1 (Fig. 6E). Using a luciferase reporter assay, we examined the association between E2F1 and the promoter sequence for CCNA2. With the wild-type CCNA2 promoter, we observed luciferase activity with E2F1. However, when the $+$ 677 promoter sequence was mutated, there was a marked decrease in activity with E2F1. These data indicate that E2F1 binds to the CCNA2 promoter at the $+$ 677 position (Fig. 6F). Finally, we knocked down endogenous E2F1 and exogenously overexpressed E2F1, and found that the expression of CCNA2 was significantly downregulated in the E2F1 knockdown group (Fig. 6G). Again, it was not surprising that E2F1 expression was upregulated when it was being overexpressed. (Fig. 6H). Therefore, we believe CCNA2 is a transcriptional target of E2F1.

Figure 6.

CCNA2 is a transcriptional target of E2F1. (A) Representative Gene Set Enrichment Analysis (GSEA) plots enriched in TCGA database showed that CCNA2 is the target gene of E2F1. (B) Correlation between CCNA2 and E2F1 in 25 cancer databases; the red mark represents invasive breast cancer. (C) Correlation between CCNA2 and E2F1 mRNA levels in TCGA BRCA cohort. (D) Correlation between CCNA2 and E2F1 mRNA levels in TNBC tissues. (E) Predicted E2F1 binding sequence, GGCGCC, in the CCNA2 promoter 5 ${}^{\prime}$ -region through motif analysis. (F) Identification of the E2F1 binding site in the CCNA2 promoter region using deletion mutants via a luciferase reporter assay. (G, H) Expression of E2F1 affected the expression of CCNA2, knockdown of E2F1 inhibited CCNA2 expression, and overexpression of E2F1 upregulated the expression of CCNA2. Data were compared using a Student’s $t$ -test; ${}^{*}P<$ 0.05, ${}^{**}P<$ 0.01, and ${}^{***}P<$ 0.001.

Figure 7.

Overexpression CCNA2 increases cell proliferation, invasion, and migration but inhibits apoptosis via E2F1-mediated regulation in TNBC cells. (A) E2F1 silencing downregulates the expression of CCNA2 in MDA-MB-231 and MDA-MB-468 cells, analyzed via WB. (B, C) E2F1 silencing inhibits cell proliferation by downregulating the expression of CCNA2 in MDA-MB-231 and MDA-MB-468 cells, as shown by CCK-8 and colony formation assays. (D) E2F1 silencing inhibits cell invasion by downregulating the expression of CCNA2 in MDA-MB-231 and MDA-MB-468 cells, as shown by transwell assays. (E) E2F1 silencing inhibits cell migration by downregulating the expression of CCNA2 in MDA-MB-231 and MDA-MB-468 cells, as shown by wound healing assays. (F) Silencing E2F1 promotes cell apoptosis by downregulating the expression of CCNA2 in MDA-MB-231 and MDA-MB-468 cells, as detected by TUNEL staining. Data were compared using a Student’s $t$ -test; ${}^{*}P<$ 0.05, ${}^{**}P<$ 0.01, and ${}^{***}P<$ 0.001.

Figure 8.

The scientific hypothesis of E2F1 mediates the transcriptional regulation of CCNA2 expression to promote TNBC cell proliferation.

3.7 Upregulated CCNA2 expression increases cell proliferation, invasion, and migration of TNBC cells in vitro via E2F1

Cell rescue experiments revealed that the expression of cyclin A2 was significantly downregulated between the E2F1-si and E2F1-si plus CCNA2 overexpression groups using both MDA-MB-231 and MDA-MB-468 cells ( $P<$ 0.001) (Fig. 7A). Compared with that in the NC group, the CCK-8 assay showed that cell proliferation was significantly inhibited in the E2F1-si and E2F1-si with CCNA2 overexpression groups ( $P<$ 0.01 and $P<$ 0.05, respectively) (Fig. 7B). Next, we examined the MDA-MB-231 and MDA-MB-468 cells under these different treatment conditions via a colony formation assay. We found that the number of colonies formed significantly increased after 14 days of culture in the NC and E2F1-si with CCNA2 overexpression groups compared with that in the E2F1-si group ( $P<$ 0.001) (Fig. 7C). The transwell assay indicated a significant difference in the invasive rate among the NC, E2F1-si, and E2F1-si with CCNA2 overexpression groups (Fig. 7D). The number of invading cells from the E2F1-si group significantly decreased compared with that in the NC and E2F1-si with CCNA2 overexpression groups ( $P<$ 0.001 and $P<$ 0.01, respectively). The wound-healing assay revealed that the E2F1-si group was significantly delayed in closing the wound area compared with the NC and E2F1-si with CCNA2 overexpression groups ( $P<$ 0.001) (Fig. 7E). Results from the TUNEL assay suggested that apoptosis was promoted in the E2F1-si group compared with the NC and CCNA2 groups ( $P<$ 0.001 and $P<$ 0.01, respectively) (Fig. 7F). Therefore, these results indicate that upregulating CCNA2 expression increases cell proliferation, invasion, and migration, but inhibits apoptosis in TNBC cells in vitro; moreover, these processes are dependent on regulation via E2F1.

3.8 Scientific hypothesis diagram

In summary, upregulation of the transcription factor E2F1 mediates the transcriptional regulation of CCNA2, which promotes an abundance of CCNA2 by increasing its transcription level leading to its high expression, which ultimately promotes the proliferation of TNBC cells (Fig. 8).

4. Discussion

Our study revealed that E2F1 and CCNA2 were overexpressed in TNBC cells; moreover, they showed a strong positive correlation. Using a luciferase reporter assay, we examined the association between E2F1 and the promoter sequence for CCNA2 and found that E2F1 binds to the CCNA2 promoter at the $+$ 677 position. The transcription factor E2F1 promotes cell proliferation, invasion, and migration by regulating CCNA2 in TNBC. E2F1 promotes TNBC proliferation and invasion by upregulating CCNA2 expression. E2F1 and CCNA2 are potential candidates that might be targeted for effective TNBC treatment. TNBC is negative for ER, PR, and HER2, has a high degree of invasion, and lacks effective therapeutic targets, resulting in a decreased overall survival period. Therefore, finding new and effective therapeutic targets is the key to treating this disease. Many cell cycle-related genes play a crucial role in tumor cell growth. Notably, the cell cycle protein CCNA2 appears for the longest period of time in the late G1-phase and can bind to the cyclin-dependent kinases, CDK1 and CDK2. It can affect the G1/S and G2/M phases of cells, and was first found in liver cancer cells [18]. Later studies found that it is differentially expressed in a variety of cancers and associated with patient prognosis, such as in colorectal [6], pancreatic [19], and prostate cancers [20]. Bioinformatics analysis found that CCNA2 is a prognostic biomarker in ER $+$ breast cancer [21, 22]. However, whether CCNA2 is highly expressed in TNBC and if it can be used as a prognostic indicator has not been reported. Our previous research demonstrated that CCNA2 is highly expressed in TNBC tissues based on bioinformatics analysis [10]. In this study, we further examined the relationship between CCNA2 and TNBC cells both in vitro and in vivo and explored the transcriptional mechanisms that promote TNBC progression. qPCR and western blotting revealed that expression of CCNA2 was significantly upregulated both transcriptionally and translationally, both in vitro and in vivo. Overexpression of CCNA2 promoted proliferation, invasion, and migration but inhibited apoptosis in TNBC cells.

Transcriptional regulation plays an important role in promoting cancer cell proliferation. We used UCSC (http://genome.ucsc.edu/) and JASPAR (http://jaspar. genereg.net/genome-tracks/) online databases to predict the transcriptional regulatory factors of CCNA2, and then we analyzed the correlation between CCNA2 and its related transcription factor. We found that CCNA2 and E2F1 were closely combined in the promoter region and had a high correlation. E2F1 is a member of the E2F transcription factor family, which is involved in cell cycle control and apoptosis. Abnormal E2F1 expression has been linked to bladder, stomach, and lung cancers [23, 24, 25]. Li et al discovered that the overexpression of E2F1 significantly reduced the overall survival in patients with ER $+$ breast cancer through Kaplan-Meier database analysis (HR: 1.49, 95% CI: 1.25–1.77, $P<$ 0.001) [26]. Hollern et al. suggested that E2F1 upregulates the expression of the target gene FGF13 and promotes breast cancer metastasis [27]. Through qPCR analysis, we found that E2F1 and CCNA2 were highly correlated ( $R=$ 0.53, $P<$ 0.001), which is consistent with findings from online databases. Furthermore, we discovered that the mRNA and protein levels of E2F1 were highly expressed in MDA-MB-231 and MDA-MB-468 cells as demonstrated by qPCR and western blotting, respectively. Therefore, we theorized that E2F1 mediates the transcriptional regulation of CCNA2, thereby promoting TNBC progression. We used a luciferase reporter gene assay to demonstrate that E2F1 binds to the $+$ 677 position within the CCNA2 promoter region, which further confirms that E2F1 regulates the transcription of CCNA2. In addition, we further verified that E2F1 transcriptionally regulates CCNA2 through rescue experiments. Through this approach, our results illustrated that the overexpression of CCNA2 increased cell proliferation, invasion, and migration, which were regulated via E2F1 in TNBC cells. Previous studies have confirmed that E2F1, as a transcription factor, is involved in the regulation of various biological activities, including cell cycle, apoptosis, and proliferation [24, 28]. Based on these results, we demonstrated that E2F1, as an oncogene, might increase the transcriptional activity of CCNA2.

In conclusion, for the first time, we demonstrated that E2F1 actively regulates the expression of CCNA2 by binding to a specific region in its promoter. We revealed that overexpressed E2F1 promotes tumor cell proliferation by regulating the transcription of CCNA2 both in vitro and in vivo. Therefore, E2F1 and CCNA2 could be attractive therapeutic targets for effectively inhibiting tumor growth in TNBC.

Abbreviations

CCK-8: cell counting kit-8; DAPI: 4 ${}^{\prime}$ ,6-diamidino-2-phenylindole; DEG: differentially expressed gene; E2F1: E2F transcription factor 1; ER: estrogen receptor; FBS: fetal bovine serum; GSEA: gene set enrichment analysis; HER2: human epidermal growth factor receptor 2; OD: optical density; PBS: phosphate-buffered saline; qPCR: quantitative polymerase chain reaction; SE: standard error; TMA: tissue microarray; TNBC: triple-negative breast cancer; TUNEL: terminal deoxynucleotidyl transferase dUTP nick end labeling.

Author contributions

Interpretation or analysis of data: Yongbin Lu,Tao Zhang and Yi Xiao.

Preparation of the manuscript: Yongbin Lu, Fei Su and Hui Yang.

Revison for important intellectual content: Xiaoling Ling and Yana Bai.

Supervision: Xiaobin Zhang, Hongxin Su and Taozhang.

Funding

This work was founded by the Gansu Provincial Innovation team Funding project (No. 20JR5RA352 and 20JR10FA686), the Lanzhou Guidance Plan Project (No. 2019-ZD-42 and 2020-ZD-75), the First Hospital of Lanzhou University Hospital Found (NO. ldyyyn2019-82 and ldyyyn2018-66).

Competing interests

The authors have declared that no competing interest exists.

Supplementary data

The supplementary files are available to download from http://dx.doi.org/10.3233/CBM-210149.

sj-pdf-1-cbm-10.3233_CBM-210149.pdf - Supplemental material

Supplemental material, sj-pdf-1-cbm-10.3233_CBM-210149.pdf

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