SPDEF downregulation promotes tumor aggressiveness and poor prognosis in triple-negative breast cancer

Introduction

Breast cancer remains the most prevalent malignancy among women worldwide, posing a substantial threat to women’s health (1). Based on molecular profiling, breast cancer is classified into distinct subtypes including luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)-positive, and triple-negative breast cancer (TNBC). Among these, TNBC is characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and HER2 expression, rendering it unresponsive to endocrine therapy and HER2-targeted treatments (2,3). TNBC accounting for approximately 10–15% of all breast cancer cases, and associating with aggressive clinical behavior, high rates of metastasis, early recurrence, and limited therapeutic options due to the lack of actionable molecular targets, underscoring the urgent need to identify novel prognostic biomarkers and therapeutic vulnerabilities (4,5).

SAM pointed domain-containing ETS transcription factor (SPDEF) belongs to the ETS transcription factor family and is expressed in various epithelial tissues (6), where it participates in the regulation of cellular differentiation, proliferation, and apoptosis (7). Accumulating evidence indicates that SPDEF displays tissue-specific expression patterns and exerts diverse biological functions across different malignancies (8-10). In head and neck squamous cell carcinoma, SPDEF functions as a tumor suppressor, with its downregulation correlating with disease progression (11). Conversely, in prostate cancer and gastric cancer, elevated SPDEF expression promotes tumor invasion and metastasis (12,13). In breast cancer, SPDEF expression is associated with patient prognosis (14), yet its precise mechanisms remain unclear.

Recent studies have demonstrated high SPDEF expression in hormone receptor-positive breast cancer, with established associations to ER signaling pathways (7). Nevertheless, systematic investigations examining SPDEF expression variations across breast cancer subtypes and their clinical implications remain limited. Specifically, in TNBC—the subtype with the most unfavorable prognosis (15)—the expression levels of SPDEF, its correlations with clinicopathological features, and its impact on tumor biological behaviors have not been comprehensively explored. Furthermore, the molecular mechanisms underlying SPDEF-mediated regulation of TNBC cell proliferation, migration, and apoptosis warrant further investigation.

Given this context, this study aimed to investigate the expression pattern of SPDEF in TNBC tissues and cell lines, as well as to evaluate its association with clinicopathological features and patient survival outcomes. Furthermore, we sought to delineate the functional roles of SPDEF in regulating TNBC cell migration, invasion, and apoptosis, and to explore the underlying molecular mechanisms. These findings may provide novel theoretical foundations and potential therapeutic targets for TNBC diagnosis and treatment. We present this article in accordance with the MDAR reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0130/rc).

Methods

Patient clinical data

A total of 199 Breast cancer tissue samples (TNBC: n=109, HER2+: n=30, luminal A: n=30, and luminal B: n=30) were collected from Gansu Provincial Cancer Hospital between June 2020 and June 2024. All breast cancer patients were definitively diagnosed with breast cancer by pathologists, had not received neoadjuvant therapy preoperatively, and those with concomitant other malignancies or immune system diseases were excluded. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Institutional Review Board of Gansu Provincial Cancer Hospital (approval No. P202005120031). Informed consent was waived in this retrospective study.

Cell lines and main reagents

Human TNBC cell lines (HCC-1937, MDA-MB-231, and MDA-MB-468), the human normal breast epithelial cell line MCF-10A, and MCF-10A-specific culture medium (catalog numbers: iCell-h327, iCell-h129, iCell-h138, iCell-h131, and iCell-h131-001b) were obtained from Shanghai iCell Bioscience Inc. (Shanghai, China). Human breast cancer cell lines including ER⁺ MCF-7 cells, as well as MEM culture medium (catalog numbers: CL-0152 and PM150410), were purchased from Wuhan Procell Life Science & Technology Co., Ltd. (Wuhan, China). RPMI-1640 and Dulbecco’s Modified Eagle Medium (DMEM) culture media (catalog numbers: SH30027 and SH30243.01B) were purchased from HyClone (Logan, UT, USA).

An immunohistochemistry kit (catalog number: PV-9000) was purchased from Beijing Zhongshan Golden Bridge Biotechnology Co., Ltd. (Beijing, China). The jetPRIME transfection reagent (catalog number: 101000046) was obtained from Polyplus (Illkirch, France). RNA extraction kits, reverse transcription kits, and SYBR Green qPCR Mix (catalog numbers: TSP413, TSK314M, and TSE501) were purchased from Beijing Qingke Biotechnology Co., Ltd. (Beijing, China). The SPDEF overexpression plasmid (OE-SPDEF) and its corresponding negative control (OE-NC), as well as SPDEF small interfering RNAs (si-SPDEF-1, si-SPDEF-2, and si-SPDEF-3) and negative control siRNA (si-NC), were synthesized by Jiangsu Suosaifu Biotechnology Co., Ltd. (Jiangsu, China).

A Cell Counting Kit-8 (CCK-8) assay kit (catalog number: CK04) was obtained from Dojindo Laboratories (Kumamoto, Japan). An Annexin V-FITC/PI apoptosis detection kit (catalog number: 40302ES60) was purchased from Shanghai Yeasen Biotechnology Co., Ltd. (Shanghai, China). Crystal violet, RIPA lysis buffer, and a BCA protein concentration assay kit (catalog numbers: C0121, P0013B, and P0010) were purchased from Shanghai Beyotime Biotechnology Co., Ltd. (Shanghai, China). Paraformaldehyde fixative (catalog number: G1101) was obtained from Wuhan Servicebio Technology Co., Ltd. (Wuhan, China).

Primary antibodies against SPDEF (catalog number: 121119) were purchased from Chengdu ZENBIO (Chengdu, China). Antibodies against Bcl-2 and Bax (catalog numbers: ET1702-53 and ET1603-34) were obtained from Hangzhou HuaBio (Hangzhou, China). The BCL-XL antibody (catalog number: AF6414) was purchased from Jiangsu Affinity Biosciences (Jiangsu, China). Antibodies against cleaved caspase-3 and GAPDH (catalog numbers: 68773-1-Ig and 60004-1-Ig) were purchased from Wuhan Sanying Biotechnology Co., Ltd. (Wuhan, China), while the cleaved caspase-9 antibody (catalog number: 20750T) was obtained from Cell Signaling Technology (Danvers, MA, USA).

Bulk transcriptome analysis

To investigate SPDEF expression in different types of breast cancer, we analyzed data through the GEPIA2 website (http://gepia2.cancer-pku.cn/). Transcriptome data and corresponding clinical information from the breast cancer cohort (BRCA cohort) were obtained from The Cancer Genome Atlas (TCGA) database. Transcriptome data were converted to FPKM format for analysis. Data on SPDEF expression in breast cancer were processed using R software to generate box plots showing expression differences and to analyze inter-group differences. The identification of differentially expressed genes (DEGs) between the high and low SPDEF subtypes was performed utilizing the “limma” package, with a false discovery rate (FDR) threshold of <0.05 and an absolute log₂ fold change (FC) (|log₂FC|) of ≥1 set as the criteria for statistical and biological significance (16). To further interpret the functional implications of the identified DEGs, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was carried out, aiming to delineate the key regulatory pathways.

Spatial transcriptomic analysis

To investigate the spatial distribution of gene expression across different breast cancer subtypes, four matched 10× Genomics Visium spatial transcriptomics datasets of breast cancer were retrieved from the Gene Expression Omnibus database (GSE218951). Data integration, normalization, and downstream analyses were performed using R software (version 4.5.1) with the Seurat and SpatialExperiment packages. The spatial expression patterns of representative genes, including SPDEF, CASP3, and CASP9, were visualized across tissue sections using the SpatialFeaturePlot function. Violin plots were generated to compare the expression levels of EPCAM, ESR1, SPDEF, CASP3, and CASP9 in tumor tissues from ER-positive breast cancer and TNBC patients.

Immunohistochemical detection

Clinical paraffin-embedded samples were sectioned at 4 µm thickness using a microtome, followed by slide baking, deparaffinization, antigen retrieval, and blocking of endogenous peroxidase with 3% H₂O₂. After washing three times with phosphate-buffered saline (PBS), diluted primary antibody was added and incubated overnight at 4 ℃ in a humidified chamber. Following three PBS washes, diluted secondary antibody was added and incubated at 37 ℃ for 20 min. 3,3'-Diaminobenzidine (DAB) chromogenic development was performed, followed by hematoxylin counterstaining, dehydration, and mounting. Slides were observed under a microscope, and results were analyzed using ImageJ software.

Cell culture and baseline validation

HCC-1937 cells were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin. MDA-MB-468 and MDA-MB-231 cells were cultured in DMEM medium containing 10% FBS and 1% P/S. MCF-7 cells were cultured in MEM medium supplemented with 10% FBS, 1% P/S, and human insulin (10 µg/mL). MCF-10A cells were cultured in MCF-10A cell-specific culture medium. All cells were maintained in a humidified incubator at 37 ℃ with 5% CO₂.

Reverse transcription quantitative polymerase chain reaction (RT-qPCR) detection of SPDEF mRNA expression

Total RNA from each group of cells was extracted using a kit-based method, and RNA concentration and purity were assessed. cDNA was synthesized by reverse transcription, and PCR amplification was performed using a fluorescent quantitative reagent kit. Using GAPDH as the internal reference, the relative expression of SPDEF mRNA was calculated by the 2^−ΔΔCt method. PCR primers were synthesized by Beijing Qingke Biotechnology Co., Ltd., with the following sequences: SPDEF: 5'-CCACTCCCACCCATCTCAAC-3' (forward), 5'-AAACATTCCTGCGCCCTGAT-3' (reverse); GAPDH: 5'-TCAAGAAGGTGGTGAAGCA GG-3' (forward), 5'-TCAAAG GTGGAGGAGTGGGT-3' (reverse).

Western blot detection of SPDEF protein expression

Cells from each group were collected, and total cellular protein was extracted and quantified. Proteins were denatured in a heating block, separated by electrophoresis, and transferred to membranes. After blocking and washing twice with Tris Buffered Saline with Tween 20 (TBST) for 2 min each, primary antibody (diluted 1:1,000) was added and incubated overnight at 4 ℃. Secondary antibody (diluted 1:5,000) was then added, followed by color development. Results were observed using a gel imaging system, and band intensity was analyzed. This method was used to detect the expression of SPDEF protein and apoptosis-related proteins Bax, Bcl-2, Bcl-xL, cleaved caspase-3, and cleaved caspase-9.

Cell transfection and experimental grouping

Logarithmic-phase TNBC cells were seeded in 6-well culture plates. When cell confluence reached 70%, transfection was performed. At 48 h post-transfection, SPDEF mRNA expression was detected by RT-qPCR and SPDEF protein expression was detected by Western blot to verify overexpression and knockdown efficiency and to determine the optimal siRNA. MDA-MB-231 cells were divided into si-NC and si-SPDEF groups, while MDA-MB-468 cells were divided into OE-NC and OE-SPDEF groups. Transfection was performed according to grouping, and subsequent experiments were conducted 48 h post-transfection.

CCK-8 assay

Logarithmic-phase TNBC cells were seeded in 96-well plates at 100 µL per well and cultured overnight. Cell transfection was performed according to the grouping described in section 1.8. After culturing for 0, 24, 48, 72, and 96 h, 10 µL of CCK-8 solution was added to each well, followed by an additional 3 h incubation. Absorbance at 450 nm was measured using a microplate reader, with absorbance values representing cell proliferation capacity.

Colony formation assay

Cells from each group were collected and adjusted to the appropriate cell density, then seeded at 500 cells/well in 6-well plates. Culture medium was changed every 3 days, and cells were cultured continuously for 2 weeks. Cells were then removed, washed twice with PBS, fixed with 4% paraformaldehyde for 10 min, and stained with crystal violet for 10 min. After washing with PBS, plates were photographed and colonies were counted.

Wound healing assay

Cells were seeded in 6-well plates and cultured for 24 h. Wounds were created perpendicular to the plate using a sterile pipette tip, followed by three PBS washes. Serum-free culture medium was added, and plates were placed in an incubator. Photographs were taken at 0, 24, and 48 h, and cell migration distance was analyzed.

Transwell invasion assay

Cells from each group were digested and centrifuged at 1,200 rpm for 3 min. Culture medium was discarded, cells were washed with PBS and resuspended in serum-free culture medium, and cell density was adjusted to 1.5×10⁵ cells/mL. A volume of 200 µL cell suspension was added to Transwell chambers previously coated with 50 µL Matrigel, and 600 µL of culture medium containing 10% FBS was added to the lower chamber of the 24-well plate. After 24 h of culture, Transwell chambers were removed, washed with PBS, fixed, and stained with crystal violet. Migrated cells were observed under a microscope, photographed, and counted.

Flow cytometry detection of apoptosis level

Cell supernatants from each group were collected, and cells were digested with trypsin. After discarding the supernatant, cells were washed twice with pre-chilled PBS. Cells were then collected and resuspended in 100 µL of 1× binding buffer. After adding 5 µL Annexin V-FITC and 10 µL PI staining solution, the mixture was incubated at room temperature in the dark for 15 min. Subsequently, 400 µL of 1× binding buffer was added, mixed, and immediately analyzed by flow cytometry.

Statistical analysis

GraphPad Prism 9.0 software was used for analysis and visualization of cellular data. Clinical data analysis and bioinformatics analysis were performed using R software. Normally distributed data were expressed as mean ± standard deviation (x¯±s), and Student’s t-test was used for comparisons between two groups, while one-way analysis of variance (ANOVA) was used for multiple group comparisons. Non-normally distributed data were expressed as median (interquartile range), and Wilcoxon rank-sum test was used for comparisons between two groups, while Kruskal-Wallis H test was used for multiple group comparisons. A two-tailed P<0.05 was considered statistically significant.

Results

SPDEF is specifically downregulated in TNBC tissues and cell lines

To investigate SPDEF expression in different types of breast cancer tissues, we analyzed data through the GEPIA2 website, which revealed that compared with normal breast tissue, SPDEF expression was significantly decreased in TNBC, whereas it was significantly elevated in HER2+, luminal A, and luminal B subtypes (Figure 1A, all P<0.05). To validate this observation, we examined SPDEF protein expression in different breast cancer subtypes from our hospital through immunohistochemical staining. The results similarly demonstrated that SPDEF expression in TNBC was significantly lower than in HER2+, luminal A, and luminal B subtypes (Figure 1B,1C, all P<0.05).

Figure 1 Differential expression analysis of SPDEF in breast cancer tumor tissues and cell lines across different subtypes. (A) Box plot analysis of SPDEF expression differences in adjacent normal samples and four breast cancer subtypes (TNBC, HER2+, luminal A, and luminal B) from TCGA-BRCA data. (B,C) Immunohistochemical images of SPDEF expression in four breast cancer subtypes from our institutional breast cancer cohort and quantitative analysis bar graph. Left: low magnification (×40); right: high magnification (×200). (D) RT-qPCR detection of SPDEF mRNA expression in different cell lines. (E,F) Western blot detection of SPDEF protein expression band intensity diagram (E) and protein quantitative analysis bar graph (F) in different cell lines. *, P<0.05; **, P<0.01; ***, P<0.001. BRCA, breast invasive carcinoma; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; IHC, immunohistochemistry; N, normal; RT-qPCR, reverse transcription quantitative polymerase chain reaction; SPDEF, SAM pointed domain-containing ETS transcription factor; T, tumor; TCGA, The Cancer Genome Atlas; TNBC, triple-negative breast cancer; TPM, transcripts per million.

We further examined SPDEF expression in TNBC cell lines. RT-qPCR results showed that compared with the normal human breast epithelial cell line MCF-10A, both SPDEF mRNA and protein were expressed at lower levels in TNBC cells HCC-1937, MDA-MB-468, and MDA-MB-231, whereas SPDEF mRNA and protein expression levels were higher in the non-TNBC cell line MCF-7 (Figure 1D, all P<0.01). Western blot analysis similarly revealed that SPDEF expression in TNBC cell lines (HCC-1937, MDA-MB-468, MDA-MB-231) was significantly lower than in the non-TNBC cell line (MCF-7) (Figure 1E,1F, all P<0.01).

High SPDEF expression in TNBC patients is associated with earlier tumor-node-metastasis (TNM) stage and better patient prognosis

To clinically investigate the relationship between SPDEF expression and patient prognosis in TNBC, we retrospectively collected samples from 109 TNBC patients who underwent radical surgery at our hospital and examined SPDEF protein expression through immunohistochemical staining (Figure 2A). Analysis of clinical baseline characteristics revealed that a significantly higher proportion of TNBC patients with TNM stage I and II disease exhibited high SPDEF expression, whereas patients with TNM stage III were more prevalent in the low SPDEF expression group (Figure 2B, Chi-squared test, P=0.04). Tumor recurrence rates were significantly higher in the SPDEF-low group compared with the SPDEF-high group (Figure 2B, Chi-squared test; 30.9% vs. 9.8%, P=0.02). Box plot analysis of SPDEF expression demonstrated that SPDEF expression significantly decreased with TNM stage progression (Figure 2C, all P<0.05). Further survival analysis showed that TNBC patients in the high SPDEF expression group had significantly superior recurrence-free survival (Figure 2D, log-rank test, P=0.02) and overall survival (Figure 2E, log-rank test, P=0.03) compared to the low SPDEF expression group, suggesting that SPDEF is associated with better patient prognosis.

Figure 2 Low SPDEF expression indicates better prognosis in TNBC patients. (A) Immunohistochemical images showing high and low SPDEF expression in triple-negative breast cancer cohort from our hospital. Left: low magnification (×40); right: high magnification (×200). (B) Comparison of SPDEF expression with patient clinical baseline characteristics. (C) Box plot of SPDEF expression in TNBC patients at different TNM stages. (D,E) Survival curve distribution of recurrence-free survival and overall survival in TNBC patients with high versus low SPDEF expression groups. *, P<0.05. IDC, invasive ductal carcinoma; ILC, invasive lobular carcinoma; SD, standard deviation; SPDEF, SAM pointed domain-containing ETS transcription factor; TNBC, triple-negative breast cancer; TNM, tumor-node-metastasis.

Enrichment analysis of SPDEF-associated DEGs and the effect of SPDEF regulation on TNBC cell proliferation

To further analyze the functional role of SPDEF, we first extracted mRNA data from TNBC patients in TCGA-BRCA and stratified patients into SPDEF-high and SPDEF-low groups based on SPDEF expression. DEGs between the two groups are shown in volcano plot (Figure 3A) and heatmap (Figure 3B). Pathway enrichment analysis of DEGs between low- and high-SPDEF TNBC tumors. The enriched pathways (PI3K-AKT, cAMP, and cell adhesion signaling) are associated with the low-SPDEF expression phenotype (Figure 3C).

Figure 3 Enrichment analysis of SPDEF-associated differentially expressed genes and effects of SPDEF regulation on TNBC cell proliferation. (A,B) Volcano plot (A) and heatmap (B) showing differentially expressed genes between SPDEF-high and SPDEF-low groups in TNBC patients from TCGA-BRCA. (C) Bubble plot of KEGG pathway enrichment analysis of differentially expressed genes. (D) RT-qPCR validation of SPDEF overexpression efficiency in MAD-MB-468 cell line. (E,F) Western blot validation of SPDEF overexpression efficiency. (G) RT-qPCR validation of SPDEF knockdown efficiency in MAD-MB-231 cell line. (H,I) Western blot validation of SPDEF knockdown efficiency. (J) CCK-8 assay results detecting regulatory effects of SPDEF expression on cell proliferation. (K) Colony formation assay observing regulatory effects of SPDEF expression on cell proliferation. Magnification (×400). *, P<0.05; **, P<0.01; ***, P<0.001. BRCA, breast invasive carcinoma; CCK-8, Cell Counting Kit-8; FC, fold change; FDR, false discovery rate; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; KEGG, Kyoto Encyclopedia of Genes and Genomes; NC, negative control; OD, optical density; OE, overexpression; RT-qPCR, reverse transcription quantitative polymerase chain reaction; SPDEF, SAM pointed domain-containing ETS transcription factor; TCGA, The Cancer Genome Atlas; TNBC, triple-negative breast cancer.

We further modulated SPDEF expression to observe its effect on TNBC cell proliferation. RT-qPCR and Western blot results demonstrated that transfection with OE-SPDEF significantly upregulated SPDEF mRNA and protein expression in MDA-MB-468 cells (Figure 3D-3F, P<0.01), while transfection with si-SPDEF significantly inhibited SPDEF mRNA and protein expression in MDA-MB-231 cells (Figure 3G-3I, P<0.01).

CCK-8 assay results showed that cell absorbance in the si-SPDEF group was significantly higher than in the si-NC group, whereas cell absorbance in the OE-SPDEF group was significantly lower than in the OE-NC group (Figure 3J, P<0.01). Colony formation assay results demonstrated that the colony formation rate in the si-SPDEF group was significantly higher than in the si-NC group, while the colony formation rate in the OE-SPDEF group was significantly lower than in the OE-NC group (Figure 3K, P<0.01). These findings suggest that SPDEF knockdown promotes breast cancer cell proliferation, whereas SPDEF overexpression inhibits breast cancer cell proliferation.

Effect of SPDEF regulation on migration and invasion capacity of TNBC cells

We further assessed cell migration and invasion capabilities through wound healing assay and Transwell invasion assay. Wound healing assay results showed that cell migration capacity in the si-SPDEF group was significantly higher than in the si-NC group whereas cell migration capacity in the OE-SPDEF group was significantly lower than in the OE-NC group (Figure 4A-4D, si-group: P<0.05, OE-group: P<0.01). Transwell invasion assay results demonstrated that the number of invaded cells in the si-SPDEF group was significantly higher than in the si-NC group, while the number of invaded cells in the OE-SPDEF group was significantly lower than in the OE-NC group (Figure 4E,4F, si-group: P<0.001, OE-group: P<0.01). These findings suggest that SPDEF knockdown promotes breast cancer cell migration and invasion, whereas SPDEF overexpression inhibits breast cancer cell migration and invasion.

Figure 4 Effects of SPDEF expression regulation on migration and invasion capacity of triple-negative breast cancer cells. (A,B) Bright-field photographs (A) and migration distance statistical bar graph (B) of wound healing assay detecting regulatory effects of SPDEF knockdown on cell migration function in MAD-MB-231 cell line. Magnification (×200). (C,D) Bright-field photographs (C) and migration distance statistical bar graph (D) of wound healing assay detecting regulatory effects of SPDEF overexpression on cell migration function in MAD-MB-468 cell line. Magnification (×200). (E,F) Transwell invasion assay results of SPDEF knockdown and overexpression in MAD-MB-231 (E) and MAD-MB-468 (F) cell lines. Magnification (×400). *, P<0.05; **, P<0.01; ***, P<0.001. NC, negative control; OE, overexpression; SPDEF, SAM pointed domain-containing ETS transcription factor.

Regulatory effect of SPDEF modulation on TNBC cell apoptosis

We investigated the regulatory effect of SPDEF modulation on TNBC cell apoptosis using flow cytometry. Results of MDA-MB-231 cells showed that compared with the si-NC group, the apoptosis rate was significantly decreased in the si-SPDEF group (Figure 5A,5B, P<0.05). We further validated this finding in the SPDEF overexpression group, and results of MDA-MB-468 cells demonstrated that compared with the OE-NC group, the apoptosis level was significantly increased in the OE-SPDEF group (Figure 5C,5D, P<0.001). These findings suggest that SPDEF knockdown inhibits breast cancer cell apoptosis, whereas SPDEF overexpression promotes breast cancer cell apoptosis.

Figure 5 Regulatory effects of SPDEF expression intervention on triple-negative breast cancer cell apoptosis. (A,B) Flow cytometry detection results (A) and quantitative analysis bar graph (B) of MAD-MB-231 cells in SPDEF knockdown group versus control group. (C,D) Flow cytometry detection results (C) and quantitative analysis bar graph (D) of MAD-MB-468 cells in SPDEF overexpression group versus control group. *, P<0.05; ***, P<0.001. NC, negative control; OE, overexpression; SPDEF, SAM pointed domain-containing ETS transcription factor.

Regulatory effect of SPDEF expression on apoptosis-related protein expression in TNBC cells

To investigate the potential molecular mechanisms by which SPDEF regulates cell apoptosis, we examined the expression of pro-apoptotic and anti-apoptotic proteins by Western blot (Figure 6A). Quantitative Western blot analysis revealed that the expression of pro-apoptotic proteins Bax, cleaved caspase-3, and cleaved caspase-9 was significantly downregulated in SPDEF knockdown cells but significantly upregulated in SPDEF overexpression cells (Figure 6B-6D, all P<0.05). Expression of anti-apoptotic proteins Bcl-2 and Bcl-xL was significantly upregulated in SPDEF knockdown cells but significantly downregulated in SPDEF overexpression cells (Figure 6E,6F, both P<0.01). These findings suggest that SPDEF knockdown inhibits breast cancer cell apoptosis by modulating the expression of apoptosis-related proteins, whereas SPDEF overexpression promotes breast cancer cell apoptosis by regulating the expression of apoptosis-related proteins.

Figure 6 Regulatory effects of SPDEF expression on apoptosis-related protein expression in triple-negative breast cancer cells. (A) Western blot detection of apoptosis-related protein expression in MAD-MB-468 and MAD-MB-468 cell lines. (B-D) Quantitative analysis bar graphs of pro-apoptotic protein expression: Bax (B), cleaved caspase-3 (C), and cleaved caspase-9 (D). (E,F) Quantitative analysis bar graphs of anti-apoptotic protein expression: Bcl-2 (E) and Bcl-xL (F). *, P<0.05; **, P<0.01; ***, P<0.001. GAPDH, glyceraldehyde-3-phosphate dehydrogenase; NC, negative control; OE, overexpression; SPDEF, SAM pointed domain-containing ETS transcription factor.

Spatial expression distribution of SPDEF and apoptosis-related genes in TNBC tumor tissues

To verify the spatial expression distribution of SPDEF in TNBC tumor tissues and its relationship with apoptosis-related protein expression, we performed spatial expression analysis using spatial transcriptomics data from ER-positive and TNBC patients (Figure 7A). Results showed that in tumor tissue regions of ER-positive patients (high EPCAM expression regions), ESR1 and SPDEF were highly expressed, whereas they were downregulated in TNBC patients (Figure 7B). Furthermore, spatial expression of apoptosis-related molecules CASP3 and CASP9 was enriched in TNBC tumor tissues and markedly higher compared to ER-positive breast cancer tumor tissues. These results suggest that in TNBC, SPDEF may promote breast cancer cell apoptosis and inhibit tumor progression through regulation of apoptosis-related protein expression.

Figure 7 Comparative spatial expression distribution of SPDEF and apoptosis-related genes in tumor tissues of ER-positive and TNBC breast cancer patients. (A) Spatial expression distribution of SPDEF and apoptosis-related molecules CASP3 and CASP9 in TNBC breast cancer patient tumor tissues. (B) Violin plots of expression levels of EPCAM, ESR1, SPDEF, and apoptosis-related molecules CASP3 and CASP9 in tumor tissues of ER-positive breast cancer and TNBC breast cancer patients. ER, estrogen receptor; SPDEF, SAM pointed domain-containing ETS transcription factor; TNBC, triple-negative breast cancer.

Discussion

This study systematically analyzed the expression patterns of SPDEF across different breast cancer subtypes and comprehensively investigated its biological functions and clinical significance in TNBC. We found that SPDEF exhibits specific downregulation in TNBC, which contrasts sharply with HER2-positive and hormone receptor-positive breast cancers. More importantly, TNBC patients with high SPDEF expression demonstrated earlier TNM stage, lower recurrence rates, and superior overall survival, suggesting that SPDEF may serve as an important prognostic marker for TNBC. Through in vitro functional experiments, we further confirmed that SPDEF exerts tumor-suppressive effects in TNBC progression by regulating key biological processes including cell proliferation, migration, invasion, and apoptosis.

This study systematically compared SPDEF expression differences across various breast cancer molecular subtypes. Both bioinformatics analysis and immunohistochemical results from tumor tissues of breast cancer patients in our clinical cohort consistently demonstrated that SPDEF is significantly downregulated in TNBC while upregulated in hormone receptor-positive and HER2-positive breast cancers. This finding aligns with previous reports regarding SPDEF’s association with ER signaling pathways (7). However, in TNBC lacking ER expression, this regulatory axis is disrupted, which may represent one of the primary mechanisms underlying SPDEF downregulation.

In head and neck squamous cell carcinoma, SPDEF functions as a tumor suppressor, with its downregulation correlating with disease progression (11). Conversely, in prostate cancer and gastric cancer, elevated SPDEF expression promotes tumor invasion and metastasis (12,13). However, the expression profile and biological role of SPDEF in breast cancer, particularly in TNBC, remain incompletely elucidated.

Notably, our clinical cohort study revealed an important association between SPDEF expression and prognosis in TNBC patients. Patients with high SPDEF expression presented with earlier TNM stage, lower tumor recurrence rates, and significantly superior recurrence-free survival and overall survival compared to those with low expression. These results suggest that SPDEF not only serves as a potential prognostic biomarker for TNBC but may also participate in regulating tumor invasion and metastasis. Similar to our findings, Wang et al. observed that SPDEF suppresses head and neck squamous cell carcinoma progression by transcriptionally activating NR4A1 (11). However, SPDEF’s role exhibits heterogeneity across different tumor types (14); for instance, high SPDEF expression promotes tumor invasion in gastric cancer (12) and pancreatic adenocarcinoma (17), which may be attributed to differences in tissue microenvironment and molecular contexts.

Our functional experiments confirmed that SPDEF downregulation significantly promotes TNBC cell proliferation, migration, and invasion capacity, while SPDEF overexpression produces opposite effects. This finding validates SPDEF’s tumor-suppressive function in TNBC at the cellular level. Through differential gene enrichment analysis, we discovered that SPDEF primarily participates in regulating biological processes including the PI3K-AKT signaling pathway, cAMP signaling pathway, and cell-cell adhesion. The PI3K-AKT signaling pathway represents one of the critical pathways in tumorigenesis and development (18), and its aberrant activation is closely associated with tumor cell proliferation, survival, invasion, and metabolic reprogramming (19,20). Our study suggests that SPDEF may exert tumor-suppressive effects by inhibiting PI3K-AKT pathway activation. Previous studies have shown that SPDEF can influence cellular behavior through transcriptional regulation of multiple target genes (11,17); for example, by upregulating E-cadherin expression to enhance cell-cell adhesion and inhibit the epithelial-mesenchymal transition (EMT) process (21). In our study, SPDEF overexpression significantly inhibited TNBC cell migration and invasion capacity, which may be related to its regulation of cell adhesion molecule expression and EMT suppression, although the specific molecular mechanisms require further investigation.

Furthermore, flow cytometry analysis revealed that SPDEF overexpression significantly promotes TNBC cell apoptosis, while SPDEF downregulation inhibits cell apoptosis. Mechanistic studies further demonstrated that SPDEF activates the mitochondrial apoptotic pathway by upregulating expression of pro-apoptotic proteins Bax, cleaved caspase-3, and cleaved caspase-9, while simultaneously downregulating anti-apoptotic proteins Bcl-2 and Bcl-xL. The Bcl-2 family of proteins plays a central role in regulating mitochondrial outer membrane permeability and cell apoptosis (22,23). Pro-apoptotic protein Bax promotes mitochondrial outer membrane permeabilization, releasing cytochrome c and subsequently activating the caspase cascade (24,25); whereas anti-apoptotic proteins Bcl-2 and Bcl-xL maintain mitochondrial membrane integrity by inhibiting Bax activity (26,27). Our research indicates that SPDEF may transcriptionally regulate Bcl-2 family member expression, altering the balance between pro-apoptotic and anti-apoptotic proteins, thereby promoting TNBC cell apoptosis. This mechanism is similar to SPDEF’s role in prostate cancer, although the specific regulatory network in breast cancer requires deeper investigation.

More importantly, we validated these findings at the tissue level through spatial transcriptomics analysis. In TNBC tumor tissues, regions with low SPDEF expression exhibited significant enrichment of apoptosis-related molecules CASP3 and CASP9, while this phenomenon was not evident in ER-positive breast cancer. This result suggests that in the TNBC microenvironment, loss of SPDEF expression may lead to apoptosis resistance, promoting tumor cell survival and proliferation. The application of spatial transcriptomics technology provided us with spatial distribution information of gene expression, enabling us to understand SPDEF’s function within the context of tissue architecture.

Based on our research findings, SPDEF may become a potential target for TNBC diagnosis, prognostic assessment, and treatment. First, SPDEF expression levels could serve as a prognostic biomarker for TNBC patients to assist clinical decision-making. Patients with low SPDEF expression have higher recurrence risk and poorer prognosis, potentially requiring more aggressive treatment strategies and closer follow-up monitoring. Second, restoring SPDEF expression or activating its downstream signaling pathways may represent novel therapeutic strategies. In recent years, the role of epigenetic modifications in tumorigenesis has received increasing attention (28,29). SPDEF downregulation in TNBC may be associated with promoter region DNA methylation or histone modifications (30). Using demethylating agents or histone deacetylase inhibitors to restore SPDEF expression could potentially reactivate its tumor-suppressive function. Additionally, targeting SPDEF’s downstream PI3K-AKT pathway, several inhibitors have demonstrated efficacy against TNBC in clinical trials (31), and combination therapy with SPDEF-targeted treatment and PI3K-AKT inhibitors may produce synergistic effects. Third, SPDEF’s function in promoting cell apoptosis suggests it may enhance sensitivity to chemotherapy or targeted therapy. TNBC’s resistance to chemotherapy represents one of the major challenges in clinical treatment (32), and apoptosis resistance is an important mechanism of chemotherapy resistance (33). By upregulating SPDEF expression or activating its mediated apoptotic pathway, it may be possible to overcome TNBC chemotherapy resistance and improve therapeutic efficacy. This hypothesis requires validation through further in vitro and in vivo experiments.

Although this study systematically elucidated SPDEF’s expression, function, and clinical significance in TNBC, several limitations remain. First, our clinical cohort sample size is relatively limited (n=109), necessitating further validation of SPDEF’s prognostic value in larger-scale multicenter cohorts. Second, this study was primarily based on in vitro cell experiments and lacks in vivo animal model validation of SPDEF’s effects on tumor growth and metastasis to more comprehensively evaluate its biological functions.

Conclusions

In summary, this study systematically revealed SPDEF’s specific downregulation in TNBC and its tumor-suppressive function. SPDEF inhibits TNBC progression by suppressing cell proliferation, migration, and invasion while promoting cell apoptosis. SPDEF expression levels are significantly associated with TNM stage, recurrence rate, and survival in TNBC patients, demonstrating important clinical prognostic value. Our research not only deepens understanding of TNBC molecular mechanisms but also provides a theoretical foundation for developing SPDEF-based diagnostic biomarkers and therapeutic strategies. Future work requires larger-scale clinical studies and in-depth mechanistic exploration to advance SPDEF-related research toward clinical translation.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0130/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0130/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0130/prf

Funding: This work was supported by grants from the Gansu Provincial Health Industry Research Program Project (No. GSWSKY2020-04) and Lanzhou Science and Technology Plan Project (No. 2023-2-50).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0130/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Institutional Review Board of Gansu Provincial Cancer Hospital (approval No. P202005120031). Informed consent was waived in this retrospective study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Coles CE, Earl H, Anderson BO, et al. The Lancet Breast Cancer Commission. Lancet 2024;403:1895-950. [Crossref] [PubMed]
2. Lebedeva V, Ebbinghaus M, Hidalgo JV, et al. Triple-Negative Breast Cancer Unveiled: Bridging Science, Treatment Strategy, and Economic Aspects. Int J Mol Sci 2025;26:9714. [Crossref] [PubMed]
3. Bianchini G, De Angelis C, Licata L, et al. Treatment landscape of triple-negative breast cancer - expanded options, evolving needs. Nat Rev Clin Oncol 2022;19:91-113. [Crossref] [PubMed]
4. Denkert C, Liedtke C, Tutt A, et al. Molecular alterations in triple-negative breast cancer-the road to new treatment strategies. Lancet 2017;389:2430-42. [Crossref] [PubMed]
5. Kumar N, Ehsan S, Banerjee S, et al. The unique risk factor profile of triple-negative breast cancer: a comprehensive meta-analysis. J Natl Cancer Inst 2024;116:1210-9. [Crossref] [PubMed]
6. Merkens L, Sailer V, Lessel D, et al. Aggressive variants of prostate cancer: underlying mechanisms of neuroendocrine transdifferentiation. J Exp Clin Cancer Res 2022;41:46. [Crossref] [PubMed]
7. Li J, Wan X, Xie D, et al. SPDEF enhances cancer stem cell-like properties and tumorigenesis through directly promoting GALNT7 transcription in luminal breast cancer. Cell Death Dis 2023;14:569. [Crossref] [PubMed]
8. Bao KC, Wang FF. The role of SPDEF in cancer: promoter or suppressor. Neoplasma 2022;69:1270-6. [Crossref] [PubMed]
9. Qiao Z, Lv Z, Song X, et al. SPDEF-mediated BIRC5 transcriptional activation enhances non-small cell lung cancer progression. Mutat Res 2025; Epub ahead of print. [Crossref] [PubMed]
10. Solanky M, Khosla M, Alahari SK. Assessing the Tumor Suppressive Impact and Regulatory Mechanisms of SPDEF Expression in Breast Cancer. Cancers (Basel) 2025;17:3556. [Crossref] [PubMed]
11. Wang Y, Ren X, Li W, et al. SPDEF suppresses head and neck squamous cell carcinoma progression by transcriptionally activating NR4A1. Int J Oral Sci 2021;13:33. [Crossref] [PubMed]
12. Meiners J, Schulz K, Möller K, et al. Upregulation of SPDEF is associated with poor prognosis in prostate cancer. Oncol Lett 2019;18:5107-18. [Crossref] [PubMed]
13. Wu J, Qin W, Wang Y, et al. SPDEF is overexpressed in gastric cancer and triggers cell proliferation by forming a positive regulation loop with FoxM1. J Cell Biochem 2018;119:9042-54. [Crossref] [PubMed]
14. Ye T, Li J, Feng J, et al. The subtype-specific molecular function of SPDEF in breast cancer and insights into prognostic significance. J Cell Mol Med 2021;25:7307-20. [Crossref] [PubMed]
15. Salas-Benito D, Pérez-Gracia JL, Ponz-Sarvisé M, et al. Paradigms on Immunotherapy Combinations with Chemotherapy. Cancer Discov 2021;11:1353-67. [Crossref] [PubMed]
16. Luo D, Li X, Wei L, et al. Ubiquitin-related gene markers predict immunotherapy response and prognosis in patients with epithelial ovarian carcinoma. Sci Rep 2024;14:25239. [Crossref] [PubMed]
17. Jiang H, Xue Z, Zhao L, et al. SPDEF drives pancreatic adenocarcinoma progression via transcriptional upregulation of S100A16 and activation of the PI3K/AKT signaling pathway. Biomol Biomed 2024;24:1231-43. [Crossref] [PubMed]
18. Zhang H, Zheng W, Li D, et al. MiR-379-5p Promotes Chondrocyte Proliferation via Inhibition of PI3K/Akt Pathway by Targeting YBX1 in Osteoarthritis. Cartilage 2022;13:19476035221074024. [Crossref] [PubMed]
19. Xu R, Lan H, Zhang L, et al. SALL4-targeted therapeutic peptide PEN-FFW suppresses PD-L1 and enhances CD8⁺ T cell cytotoxicity via regulating PI3K/AKT signaling in breast cancer. Immunol Res 2026;74:3. [Crossref] [PubMed]
20. Utama K, Khamto N, Halimi YF, et al. Gallic acid-conjugated 2',4'-dihydroxy-6'-methoxy-3',5'-dimethylchalcone induces apoptosis and downregulates PI3K/Akt signaling through VEGFR-2 targeting in non-small cell lung cancer (NSCLC). Biomed Pharmacother 2026;195:118968. [Crossref] [PubMed]
21. Chen WY, Tsai YC, Yeh HL, et al. Loss of SPDEF and gain of TGFBI activity after androgen deprivation therapy promote EMT and bone metastasis of prostate cancer. Sci Signal 2017;10:eaam6826. [Crossref] [PubMed]
22. Kumar N, Kumar S, Shukla A, et al. Mitochondrial-mediated apoptosis as a therapeutic target for FNC (2'-deoxy-2'-b-fluoro-4'-azidocytidine)-induced inhibition of Dalton's lymphoma growth and proliferation. Discov Oncol 2024;15:16. [Crossref] [PubMed]
23. Quarato G, Llambi F, Guy CS, et al. Ca(2+)-mediated mitochondrial inner membrane permeabilization induces cell death independently of Bax and Bak. Cell Death Differ 2022;29:1318-34. [Crossref] [PubMed]
24. Erdogan MK, Ozer G. Synergistic Anticancer Effects of Bleomycin and Hesperidin Combination on A549 Non-Small Cell Lung Cancer Cells: Antiproliferative, Apoptotic, Anti-Angiogenic, and Autophagic Insights. Pharmaceuticals (Basel) 2025;18:254. [Crossref] [PubMed]
25. Reece MD, Song C, Hancock SC, et al. Repurposing BCL-2 and Jak 1/2 inhibitors: Cure and treatment of HIV-1 and other viral infections. Front Immunol 2022;13:1033672. [Crossref] [PubMed]
26. Roghani M, Golchoobian R, Mohammadian M, et al. Time-Dependent Molecular Changes Following MDMA-Induced Nephrotoxicity. Iran J Pharm Res 2024;23:e145483. [Crossref] [PubMed]
27. Qiao L, Dou X, Song X, et al. Targeting mitochondria with antioxidant nutrients for the prevention and treatment of postweaning diarrhea in piglets. Anim Nutr 2023;15:275-87. [Crossref] [PubMed]
28. Kang Z, Wang J, Liu J, et al. Epigenetic modifications in breast cancer: from immune escape mechanisms to therapeutic target discovery. Front Immunol 2025;16:1584087. [Crossref] [PubMed]
29. Duan L, Hu D, Zhang H, et al. Microbiota and tumor epigenetics: deep interconnections and emerging therapeutic perspectives. Crit Rev Clin Lab Sci 2026; Epub ahead of print. [Crossref] [PubMed]
30. Ahmadianpour MV, Aleyasin SA. CpG dinucleotide methylation of the SPDEF gene as a blood-based epigenetic biomarker for prostate cancer diagnosis. BMC Urol 2025;25:145. [Crossref] [PubMed]
31. Basho RK, Gilcrease M, Murthy RK, et al. Targeting the PI3K/AKT/mTOR Pathway for the Treatment of Mesenchymal Triple-Negative Breast Cancer: Evidence From a Phase 1 Trial of mTOR Inhibition in Combination With Liposomal Doxorubicin and Bevacizumab. JAMA Oncol 2017;3:509-15. [Crossref] [PubMed]
32. Vishnubalaji R, Alajez NM. Transcriptional landscape associated with TNBC resistance to neoadjuvant chemotherapy revealed by single-cell RNA-seq. Mol Ther Oncolytics 2021;23:151-62. [Crossref] [PubMed]
33. Pu Z, Li Q, Lu C, et al. The biological roles of non-coding RNAs in triple-negative breast cancer: Therapeutic, diagnostic, drug resistance, and prognostic implications. Int J Biol Macromol 2025;328:147664. [Crossref] [PubMed]