The Cancer Genome Atlas (TCGA) RNA-seq data and corresponding clinical data were downloaded from UCSC Xena platform (https://xena.ucsc.edu/) (Vivian et al., 2017). The differences in VEGFA mRNA expression between breast cancer and normal tissues were assessed using the Wilcoxon rank-sum test with a threshold of |log2FC| > 1 and P < 0.05. The difference in VEGFA protein level between breast cancer and normal tissues was evaluated using online Human Protein Atlas project (https://www.proteinatlas.org/) (Asplund et al., 2012).

Kaplan-Meier Plotter (http://kmplot.com) database was utilized to evaluate the prognostic value of VEGFA in BRCA (FDR < 0.05, P < 0.05) (Lánczky and Győrffy, 2021). Patients were stratified into high or low expression groups based on the median of VEGFA mRNA level. We assessed the impact of VEGFA on the overall survival (OS), relapse free survival (RFS), distant metastasis free survival (DMFS) and post-progression survival (PPS) of breast cancer patients by calculating hazard ratio (HR) and 95% confidence interval (95% CI).

Human breast cancer cells (MCF-7 and MDA-MB-231) were purchased from Procell (Wu Han, China). Cells were cultured in DMEM medium (Thermo Fisher Scientific, Waltham, MA, United States) containing 10% fetal bovine serum (FBS; Thermo Fisher Scientific, Waltham, United States) and 1% antibiotics (Solarbio, Beijing, China) in the presence of 5% CO₂ at 37°C. The antibiotics were added at a final concentration of 100 U/mL of penicillin and 100 μg/mL of streptomycin. All cell lines were used between passages 3 to 10 to maintain consistency in cellular characteristics.

Anlotinib was a gift from Chia Tai Tianqing Pharmaceutical Company (Nanjing, China). DDP was purchased from Haosen (Lianyungang, China). Anlotinib was dissolved in dimethyl sulfoxide (DMSO; Sigma, St. Louis, United States) and stored at −20°C shielded from light. BRCA cells were treated with anlotinib or DDP at concentrations of 0, 5, 10, 20 and 40 μM. The combined treatment group was administered 10 μM anlotinib and 8 μM DDP. For all in vitro experiments, triplicate wells were used to ensure the reliability and reproducibility of the results.

The effects of anlotinib and DDP on the proliferation of BRCA cells were detected by CCK-8 assay. MCF-7 or MDA-MB-231 cells were seeded at a density of 5 × 10³ cells/well in 96 well plates and cultured overnight, and then treated with or without anlotinib and DDP. CCK-8 (Dojindo, Kumamoto, Japan) was then added at the designated time. After 2 h at dark, the optical density (OD) at 450 nm was measured with a microplate reader (Tecan, Männedorf, Switzerland).

After treated with or without anlotinib and/or DDP, 1 × 10³ breast cancer cells were then seeded in a 60 mm dish and cultured for 14 days. After fixation with 4% paraformaldehyde and staining with 0.1% crystal violet, colonies (≥ 50 cells) were counted under an IX71 inverted microscope (Olympus, Tokyo, Japan).

Cell migration was measured using a wounding healing assay. Upon reaching 90% confluence, the cell monolayer was scratched using a 200 μL pipette tip, creating a linear wound perpendicular to the culture plate. Subsequently, cells were incubated in a medium containing anlotinib and/or DDP for 48 h. Photographs were taken with an IX71 inverted microscope at 0h, 24h and 48 h time point and the wound areas were measured by Image J.

BRCA cells treated with anlotinib and/or DDP were resuspended in serum-free DMEM medium. Matrigel coated or uncoated transwell chambers (Corning, Corning, NY, United States) were seeded with cell suspensions (1 × 10⁵ cells/200 μL) and cultured for 24 h or 48 h in DMEM medium with 20% FBS. Non-migrated cells were scraped off with a cotton swab. Cells in the bottom wall of chambers were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet, and then the migrated or invaded cells were photographed under an inverted microscope.

BRCA cells (MCF-7 and MDA-MB-231) were treated with anlotinib (10 µM) for 24 h, while control groups received DMSO. After treatment, cells were harvested, fixed in 70% ethanol at −20°C for 2 h, and then washed with PBS. Cells were stained with propidium iodide (50 μg/mL) and RNase A (100 μg/mL) in PBS, incubating at 37°C for 30 min in the dark. DNA content was measured by flow cytometry (Beckman Coulter, Brea, United States).

Hoechst 33,324 staining was used to observe nuclear morphology. After treated with anlotinib and/or DDP, BRCA cells were fixed with 4% paraformaldehyde, and then stained with Hoechst33324 (Solarbio, Beijing, China). Cell size and nuclear morphology were observed using IX71 fluorescence microscope (Olympus, Tokyo, Japan).

We used Annexin V-PE/7-AAD kit (BD Biosciences, San Jose, CA, United States) to evaluate cell apoptosis. According to the manufacturer’s protocol, cells were stained with 5 μL Annexin V-PE and 5 μL 7-AAD working solution for 15min in the dark. Flow cytometric analysis was then performed using a flow cytometer (Beckman Coulter, Brea, United States).

Total RNA was extracted using Trizol reagent (Invitrogen, CA, United States), and then reversed transcribed into cDNA using the RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, United States). The qPCR was conducted using the ABIPRISM^® 7900HT fast real-time PCR system (Applied Biosystems, Foster City, United States). For each gene, 2^−ΔΔCT was calculated to determine its relative expression (Amuthalakshmi et al., 2022). Primers were listed in Supplementary Table S1.

The cells were inoculated on the cover slide at a density of 2 × 10⁴ cells/well and incubated at 37°C overnight. The cells were fixed with 4% paraformaldehyde at room temperature for 15 min and closed with 10% goat serum for 30 min. Anti-BAX, anti-BCL2, anti-P62 (Affinity, Jiangsu, China) antibodies were incubated at 4°C overnight. Subsequently, the cover slides were incubated with FITC-conjugated Goat Anti-Rabbit IgG (H + L) antibodies (Affinity, Jiangsu, China) at room temperature for 1 h. The specimens were then stained with DAPI. The stained samples were observed and analyzed using a fluorescence microscope (Zeiss, Germany).

MCF-7 or MDA-MB-231 cells were lysed using RIPA lysis buffer, and the protein concentrations were subsequently determined. Protein samples with equal mass were subjected to separation using 6%, 10% or 12% SDS polyacrylamide gel electrophoresis and then transferred onto polyvinylidene fluoride (PVDF) membranes. The membranes were incubated with the indicated primary antibodies and then the corresponding horseradish peroxidase (HRP) conjugated secondary antibodies. Proteins were finally visualized with enhanced chemiluminescence (ECL) luminescence reagents (Amersham, United Kingdom). β-actin served as a reference control. Anti-β-actin, anti-phospho-VEGFR2 and anti-LC3B were purchased from Cell Signaling Technology (CST, Massachusetts, United States). Antibodies (anti-BAX, anti-BCL2, anti-PARP1, anti-SQSTM1/p62, anti-JAK2, anti-STAT3, anti-phospho-JAK2 and anti-phospho-STAT3) were obtained from Abcam (Eugene, United States).

Female BALB/c-nu mice (4 weeks of age) were purchased from Beijing Huafukang Biotechnology Co., LTD. After 1 week of adaptive feeding, the mice received a subcutaneous injection of 3 × 10⁶ MDA-MB-231 cells into the right armpit. The tumor volumes were calculated according to the formula: length × width² × 0.5. When the tumor volumes reached about 100 mm³, the mice were randomly divided into control group (sterile PBS loaded with drugs) and anlotinib treatment group (5 mg/kg) (Zhu et al., 2022). The mice were then given PBS or anlotinib intragastric treatment daily for 14 days. Tumor volumes and the mice body weights were recorded every 2 days. After 14 days of treatment, the mice were euthanized via cervical dislocation. The subcutaneous tumor tissue was excised, photographed and subjected to staining. The animal experiment was approved by the Experimental Animal Ethics Committee of North China University of Science and Technology (2023-SY-016).

GraphPad Prism 8 software was used to draw statistical graphs. One-way ANOVA and Student’s t-test were used to analyze the statistical significance of the measured variables. P < 0.05 was considered statistically significant.

In this study, we analyzed TCGA transcriptome data to evaluate VEGFA expression across various cancers and normal tissues. The results revealed that VEGFA was up-regulated in several cancer types, including BRCA, but downregulated in KIRP, PRAD and THCA (Figure 1A). Additionally, VEGFA transcript levels were higher in both unpaired and paired samples from TCGA-BRCA compared to normal tissues (Figures 1B, C). We also found that VEGFA protein expression was significantly elevated in BRCA tissues compared to normal tissues (Figure 1D).

Next, we evaluated VEGFA expression in different subgroups. In relation to ER, PR and HER2, we found that VEGFA expression was significantly higher in ER⁻ and PR⁻ breast cancer tissues compared to ER⁺ and PR⁺ tissues (Figures 1E, F). However, there was no significant difference of VEGFA between HER2⁻ and HER2⁺ tissues (Figure 1G). According to the TNM staging system, our data showed a significant increase in VEGFA expression in patients at stage Ⅰ, Ⅱ and Ⅲ, but not at stage Ⅳ (Figure 1H), which suggests that the elevated expression of VEGFA is prominent in the earlier stages of BRCA but not in the advanced stage.

Based on the data from Kaplan-Meier Plotter database, we found a strong association between higher VEGFA expression and the poor prognosis in BRCA patients (Figures 2A–D) with HR (95% CI) for OS, RFS and PPS of 1.41 (1.17–1.71), 1.39(1.25–1.53) and 1.59 (1.25–2.00), respectively. We further analyzed the relationship between VEGFA expression and OS of BRCA patients in different subgroups. The results indicated that (Figure 2E) high VEGFA expression correlated with poor prognosis in both ER⁺ (HR = 1.37, 95% CI = 1.08–1.73, P = 0.0096) and HER2⁻ (HR = 1.48, 95% CI = 1.18–1.84, P = 0.00058) BRCA patients. However, no significant correlation was found between VEGFA expression and OS, regardless of the PR status. These findings suggest that high VEGFA expression, when associated with specific clinicopathological features, correlates with the poor prognosis in BRCA patients.

To evaluate the impact of anlotinib on BRCA cell proliferation, we performed CCK-8 assays using MCF-7 and MDA-MB-231 cells. The results indicated that anlotinib significantly inhibited cell viability in a dose- and time-dependent manner (Figures 3A, B). We also performed flow cytometry analysis to assess cell cycle distribution. The results indicate that treatment with anlotinib leads to a significant increase in the percentage of cells in the G1 phase and a corresponding reduction in the G2/M phase, compared to the control group (Figure 3C; Supplementary Figure S1), which supporting the observed inhibition is primarily due to reduced cell proliferation. To evaluate the in vivo therapeutic effect of anlotinib on BRCA, we established a mouse model of tumor transplantation by subcutaneous injection of MDA-MB-231 cells into the armpits of nude mice. Compared to the control group, anlotinib significantly inhibited tumor growth, with no weight loss (Figures 3D–F). HE stain and Ki-67 immunohistochemistry were used to evaluate cell proliferation. The results showed more nuclear mitotic images in control group than in anlotinib group, and the expression of Ki-67 was significantly reduced in the anlotinib-treated group (Figures 3G, H). These findings suggested that anlotinib had a strong anti-tumor effect both in vivo and in vitro.

To determine the combined impact of anlotinib and DDP on breast cancer cell proliferation, we conducted CCK-8 assays using MCF-7 and MDA-MB-231 cells. When used in combination, anlotinib and DDP exhibited a synergistic effect, significantly enhancing the inhibition of breast cancer cell proliferation (Figures 4A, B). Colony formation assays further corroborated this synergistic effect, demonstrating a greater reduction in the number of cell clones in the combination treatment group compared to the single-agent treatment groups (Figure 4C). Next, we performed transwell assays to evaluate the effects of the combination of anlotinib and DDP on the migration and invasion of BRCA cells. The results showed that both anlotinib and DDP significantly inhibited cell migration and invasion, with the combination treatment group showing the most pronounced inhibition (Figures 4D, E). Additionally, wound-healing assays also revealed a notable delay in wound closure under the influence of anlotinib and/or DDP (Figures 4F, G). These findings suggest that anlotinib and DDP, particularly when used in combination, effectively inhibit the proliferation and migration of breast cancer cells.

We employed flow cytometry and Hoechst33324 staining to evaluate the impact of anlotinib and DDP on the apoptosis of breast cancer cells. Flow cytometry analysis revealed that anlotinib and/or DDP significantly induced both early and late apoptosis of MCF-7 cells (Figure 5A). In BRCA cells treated with anlotinib and DDP, notable changes in nuclear morphology were observed (Figure 5B). Additionally, the qPCR results showed that the combination of anlotinib and DDP significantly upregulated the expression of BAX, PARP1; while no significant difference was observed in BCL2 expression (Figure 5C). Western blot analysis revealed a marked increase in BAX and PARP1 expression in cancer cells treated with anlotinib alone or in combination with DDP, accompanied by a decrease in BCL2 expression (Figure 5D). Immunofluorescence analysis corroborated these findings, demonstrating a significantly increase in BAX fluorescence intensity in cancer cells treated with anlotinib alone or in combination with DDP, while the fluorescence intensity of BCL2 was decreased (Figures 6A, B). These results indicate that anlotinib promotes apoptosis by upregulating pro-apoptotic genes and inhibiting anti-apoptotic genes.

Autophagy and apoptosis are crucial cellular processes that maintain homeostasis. The excessive autophagy can lead to cancer cell death through apoptosis (Tsujimoto and Shimizu, 2005). Therefore, we analyzed the expression of autophagy-regulating genes LC3B and SQSTM1/P62. Based on TCGA breast cancer data, there was a demonstrated low expression of LC3B and a high expression of P62 in BRCA tissues compared to normal tissues (Figures 7A–D). Additionally, higher expression of LC3B and P62 correlated with the poor prognosis for BRCA patients (Figures 7E, F). More importantly, through the immunofluorescence and western blot assays, we observed increased LC3B-Ⅱ and decreased P62 in MCF-7 and MDA-MB-231 cells co-treated with anlotinib and DDP (Figures 7G, H). These results suggest that anlotinib induces autophagy, contributing to the inhibition of breast cancer cell proliferation.

Bioinformatic analyses suggested a potential interaction between VEGFR2 and JAK2/STAT3 pathway (Figures 8A–C). Anlotinib, a highly selected small molecule inhibitor of VEGFR2, was evaluated for its effects on target gene expression using qPCR. The results showed that the combined of anlotinib and DDP significantly reduced the expression of VEGFR1 and VEGFR2, while increasing VEGFA expression. There was no significant difference in the mRNA levels of JAK2, STAT3 and PI3K/AKT. Interestingly, in MCF-7 treated solely with anlotinib, JAK2 expression was lower than that in the control group (Figure 8D ; P < 0.05). Western blot analysis further confirmed the interaction between VEGFR2 and the JAK2/STAT3 pathway. Treatment with anlotinib and DDP not only reduced the expression of VEGFR2, but also inhibited the phosphorylation of JAK2 and STAT3, without affecting their total protein levels (Figure 8E). These findings suggest that anlotinib inhibit the phosphorylation of JAK2/STAT3 pathway in BRCA cells, thereby impacting cancer progression.