DCTPP1 drives immunosuppression and poor prognosis in breast cancer by promoting M2 macrophage polarization.

Introduction
Breast cancer (BRCA) remains the most commonly diagnosed malignancy in women worldwide and a leading cause of cancer-related mortality. In 2022, it accounted for approximately 2.3 million new cases, representing 11.6% of all newly diagnosed cancers1. Although multimodal therapeutic approaches—including surgery, chemotherapy, and endocrine therapy—have markedly improved outcomes2, approximately 20–30% of patients still present with or subsequently develop distant metastases, resulting in a 5-year survival rate below 30%3,4. Recent advances in bioinformatics and molecular biology have substantially improved early diagnosis, treatment-response evaluation, and prognosis monitoring5,6. Therefore, the identification and validation of novel therapeutic targets and prognostic biomarkers remain a priority.
Deoxycytidine triphosphate pyrophosphatase 1 (DCTPP1) localizes to the nucleus, cytoplasm, and mitochondria in highly proliferative cells7. It catalyzes the hydrolysis of deoxycytidine triphosphate (dCTP) to deoxycytidine monophosphate (dCMP) and pyrophosphate, thereby maintaining intracellular dCTP homeostasis. In addition, DCTPP1 hydrolyzes non-canonical deoxycytidine analogues, thereby contributing to DNA replication fidelity8. Aberrant DCTPP1 expression has been implicated in the progression of several solid tumors. In prostate cancer, its overexpression has been reported to promote tumor growth and is associated with poor prognosis9. In ovarian cancer, DCTPP1 upregulation decreases ROS levels, thereby protecting cancer cells from oxidative stress–induced apoptosis and reducing cisplatin cytotoxicity10,11. In gastric cancer, DCTPP1 overexpression reduces sensitivity to 5-fluorouracil, potentially by upregulating MDR112. However, the expression patterns and clinical relevance of DCTPP1 in BRCA, as well as its potential role in shaping the tumor immune microenvironment, remain insufficiently characterized.
The tumor microenvironment (TME) comprises a complex network of cellular and non-cellular components that can support tumor growth, invasion, metastasis, and therapeutic resistance, and includes tumor-associated macrophages (TAMs)13. Immune cells are major constituents of the TME and play critical roles in tumorigenesis and metastasis14,15. TAMs are among the most abundant infiltrating immune cell populations within the TME16. TAMs can adopt distinct polarization states, often described as classically activated M1 and alternatively activated M2 phenotypes17,18. M1 macrophages exhibit pro-inflammatory and antitumor activities, including supporting T-cell–mediated antitumor immunity19. In contrast, M2 macrophages exert immunosuppressive effects and can facilitate angiogenesis, invasion and migration, immune evasion, and stromal remodeling20. However, the molecular factors that shape macrophage polarization in BRCA remain incompletely understood. To date, whether DCTPP1 influences tumor progression through regulation of immune cell infiltration or macrophage polarization remains largely unexplored.
In this study, we systematically investigated the expression pattern, prognostic significance, and immunological relevance of DCTPP1 in BRCA using multi-omics datasets and TMA, including multiplex immunohistochemistry (mIHC). We further examined the relationship between DCTPP1 expression and immune cell infiltration, with a particular focus on macrophage polarization within the TME. Importantly, we performed Transwell-based co-culture experiments to determine whether tumor cell–intrinsic DCTPP1 modulates macrophage polarization. Together, these analyses provide integrative clinical, immunological, and functional evidence to evaluate the clinical relevance of DCTPP1 and its association with an M2-enriched immunosuppressive microenvironment in BRCA.

Materials and methods

Data acquisition and preprocessing
Transcriptomic data and clinical information for 1,180 samples (1,081 tumors and 99 normal tissues) were downloaded from The Cancer Genome Atlas (TCGA) breast cancer cohort (TCGA–BRCA). Data preprocessing and training set construction were conducted in R (version 4.4.1) using the TCGAbiolinks and SummarizedExperiment packages. For external validation, microarray gene expression datasets GSE42568 (104 tumors, 17 normal tissues) and GSE45255 (139 tumors) were retrieved from the Gene Expression Omnibus (GEO) database (accessed April 4, 2024). Pan-cancer expression patterns of DCTPP1 were analyzed using TIMER2.0 (http://timer.cistrome.org/), correlation analyses were performed using TIMER3.0. Protein expression of DCTPP1 in BRCA versus normal breast tissue was evaluated using the Human Protein Atlas (HPA; https://www.proteinatlas.org/). Single-cell DCTPP1 expression profiles were investigated using the Tumor Immune Single Cell Hub 2 (TISCH2; http://tisch.comp-genomics.org/home).

Association of DCTPP1 expression with clinical features and overall survival (OS) in BRCA
Patients were divided into high- and low-DCTPP1 expression groups based on the median expression value to examine associations with clinicopathological parameters. Kaplan–Meier survival curves were generated, and log-rank tests were conducted using the survminer R package. Time-dependent receiver operating characteristic (ROC) curves were constructed using the timeROC package to assess the prognostic performance of DCTPP1 for OS in BRCA. Univariate and multivariate Cox proportional hazards regression models were fitted, incorporating DCTPP1 expression and TCGA clinicopathological variables, to determine whether DCTPP1 remained an independent prognostic factor and to evaluate its prognostic value across clinical subgroups.

Association of DCTPP1 with tumor immunity
The ESTIMATE R package21 was used to evaluate immune cell infiltration, stromal content, the ESTIMATE composite score, and tumor purity in BRCA samples. The CIBERSORT R package22 was used to estimate the relative fractions of 22 immune cell types in BRCA. Spearman’s correlation analysis was conducted to assess associations between DCTPP1 expression and immune cell fractions, with results visualized using the ggstatsplot R package.

Association of DCTPP1 with immunotherapy response
Immune checkpoint gene expression differences between high- and low-DCTPP1 expression groups were analyzed using limma (P < 0.05), with associations assessed and visualized by Spearman’s correlation analysis. The immunophenoscore (IPS) for BRCA samples was retrieved from The Cancer Immunome Atlas (TCIA) database (https://tcia.at/, accessed October 27, 2024), and its association with DCTPP1 expression was analyzed as a proxy for predicted immunotherapy response.

Identification of DCTPP1-related differentially expressed genes and functional enrichment analysis
TCGA-BRCA patients (n = 1,081) were stratified into high- and low-DCTPP1 expression groups based on the median expression value. DEGs were identified using the DESeq2 R package23. DEGs were screened using the criteria of |log2FoldChange| > 0.5 and P < 0.05. The ggplot2 and ComplexHeatmap R packages were used to generate volcano plots and heatmaps, respectively, to visualize DEGs. Functional enrichment analyses of DEGs, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses24,25, were performed using the clusterProfiler R package. Gene Set Enrichment Analysis (GSEA) was conducted using the GSEA and clusterProfiler R packages with the hallmark gene set collection from MSigDB to explore biological processes associated with DCTPP1 expression.

Tissue microarray (TMA) construction and patient follow-up
A breast cancer TMA obtained from Shanghai Outdo Biotech Co., Ltd. contained 143 BRCA tissues and 18 adjacent non-tumor tissues collected between January 2007 and October 2008; tissues were paraffin-embedded with 1.5 mm cores. Four samples with insufficient tumor cells were excluded, leaving 139 samples for DCTPP1 expression analysis. Clinicopathological characteristics, including survival status, recurrence, age, pathological grade, tumor size (T), lymph node metastasis (N), distant metastasis (M), TNM stage, lymphovascular invasion (LVI), and molecular subtype, were summarized in Table 1. Follow-up duration ranged from 1 to 11 years after surgery. OS was defined as the time from BRCA diagnosis to death or the end of follow-up, with non–tumor-related deaths excluded. This study complied with the ethical guidelines of Shanghai Outdo Biotech Co., Ltd. (No. SHXC2021YF02) and the principles of the Declaration of Helsinki. Informed consent was waived by the Ethics Committee of Shanghai Outdo Biotech Co., Ltd. due to the retrospective nature of the study.

Multiplex immunohistochemical staining
Multiplex fluorescence immunohistochemistry was performed on BRCA TMA sections to enable simultaneous visualization of multiple protein markers. Briefly, paraffin sections were baked, dewaxed, hydrated, and subjected to antigen retrieval in heated 1× EDTA solution (600 mL) for 15 min. After cooling, sections were incubated with 3% hydrogen peroxide for 15 min to block endogenous peroxidase activity and then blocked with blocking solution for 10 min. Target proteins were sequentially labeled using a cyclic staining protocol consisting of: (1) incubation with diluted primary antibody at 37 °C for 1.5 h; (2) PBS rinses followed by incubation with HRP-conjugated secondary antibody at 37 °C for 30 min; and (3) washes with 1× PBST followed by incubation with Opal working solution at 37 °C for 10 min. Antibody stripping was performed by microwave heating in 1× AR9 buffer (high power until boiling, followed by medium power for 10 min). After cooling to room temperature, sections were rinsed with PBS. CD68, Cytokeratin (CK), CD163, and DCTPP1 were labeled sequentially using this procedure. Nuclei were counterstained with DAPI for 5 min, and slides were mounted with anti-fade mounting medium.
Stained sections were scanned using the Olympus VS200 system with UPLXAPO20X objective lenses. Multidimensional quantitative analysis of multispectral images was performed using QuPath (v0.3.0) with TUMOR and STROMA classifiers, based on five metrics (area, cell count, density, ratio, and H-score). Metrics were defined as follows: area, fluorescence signal area of the marker; cell count, number of marker-positive cells; density, number of positive cells per mm²; ratio, proportion of positive cells among total cells; H-score = [(1 × percentage of cells with weak intensity) + (2 × percentage of cells with moderate intensity) + (3 × percentage of cells with strong intensity)] × 100, giving greater weight to higher-intensity staining. Marker wavelengths and assigned colors were: CD68 (480 nm, cyan), CK (520 nm, green), CD163 (620 nm, yellow), and DCTPP1 (690 nm, red). Phenotypes were defined as: CD68⁺ (pan-macrophages), CK⁺ (tumor epithelium), CK⁻ (stroma), CD68⁺CD163⁺ (M2-like macrophages), and CD68⁺CD163⁻ (M1-like macrophages).

Selection of MCF-7 as the experimental BRCA cell line
To select an appropriate BRCA cell line for in vitro functional studies, basal DCTPP1 mRNA expression was evaluated in commonly used BRCA cell lines (MCF-7, MDA-MB-468, MDA-MB-231, SK-BR-3, and ZR-75-1) by quantitative real-time PCR (qRT-PCR). MCF-7 cells exhibited stable, moderate endogenous DCTPP1 expression, making them suitable for knockdown-based functional experiments. Additionally, MCF-7 is a well-characterized luminal A subtype model widely used in tumor–immune interaction studies. Therefore, MCF-7 cells were selected for subsequent experiments.

Lentiviral-mediated knockdown of DCTPP1 in MCF-7 cells
MCF-7 cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) in a humidified incubator with 5% CO₂ at 37 °C. Lentiviral particles carrying three independent shRNAs targeting DCTPP1 (KD1–KD3) and a non-targeting shRNA control (NC) were used for infection. Cells were seeded at approximately 20% confluence in 6-cm dishes and infected at a multiplicity of infection (MOI) of 20 in the presence of HiTransG P according to the manufacturer’s instructions. The medium was replaced 16 h after infection. For stable selection, puromycin was added 72 h after infection at a final concentration of 1.0 µg/mL for 48 h, followed by maintenance in medium containing 0.5 µg/mL puromycin. Stable knockdown cells were used for downstream analyses 120 h after infection.

Validation of knockdown efficiency and selection of KD3
Total RNA was extracted using TRIzol reagent according to the manufacturer’s instructions. cDNA was synthesized using a reverse transcription kit (PrimeScript RT Master Mix, TaKaRa), and qPCR was performed using TB Green® Premix Ex Taq™ (Tli RNaseH Plus, TaKaRa). ACTB was used as the internal control. Relative mRNA expression was calculated using the 2⁻ΔΔCt method, with the NC group used as the calibrator. Knockdown efficiency was evaluated for KD1–KD3 relative to NC, and KD3 was selected for subsequent co-culture experiments because it showed the greatest knockdown efficiency.

THP-1 differentiation into M0 macrophages
THP-1 cells were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS) and 55 µM β-mercaptoethanol. To induce differentiation into unpolarized (M0) macrophages, THP-1 cells were seeded in 24-well plates at 2 × 10⁵ cells/well in 0.5 mL medium and treated with phorbol 12-myristate 13-acetate (PMA; 50 ng/mL) for 48 h. No resting period was applied after PMA treatment. Successful differentiation was confirmed by morphological transition from suspension to adherence and by increased CD11b mean fluorescence intensity (MFI) assessed by flow cytometry.

Tumor cell–macrophage co-culture and flow cytometry analysis
To assess whether tumor cell–intrinsic DCTPP1 modulates macrophage polarization, a Transwell-based tumor cell–macrophage co-culture system was employed. THP-1–derived M0 macrophages were maintained in the lower chamber of 24-well Transwell plates (8 μm pore size), while MCF-7 cells transduced with a non-targeting shRNA control (NC) or DCTPP1 shRNA (KD3) were seeded in the upper chamber at a 1:1 ratio (2 × 10⁵ cells per well/compartment). Prior to co-culture, MCF-7 cells were cultured for 48 h in puromycin-free medium to avoid potential antibiotic carryover effects, and NC and KD3 cells were processed in parallel. Co-cultures were maintained for 48 h in RPMI-1640 medium supplemented with 10% FBS and 55 µM β-mercaptoethanol. After co-culture, only macrophages from the lower chamber were harvested for downstream analyses.
For flow cytometry, adherent macrophages were detached by brief trypsinization (~ 1 min), neutralized with complete medium, centrifuged at 300 × g for 3 min, and washed once with PBS. For each sample, 2 × 10⁵ cells were stained in 100 µL BD Stain Buffer (BD, Cat. 554657). Surface staining was performed at room temperature for 20 min in the dark using APC-conjugated anti-human CD11b (clone M1/70; BioLegend, Cat. 101212; 1 µL/test), BV421 anti-human CD86 (BD, Cat. 562432; 3 µL/test), and PE anti-human CD206 (BD, Cat. 555954; 20 µL/test). Cells were washed twice with BD Stain Buffer (200 µL per wash). Viability was assessed using 7-AAD (eBioscience, Cat. 00–6993-50; 2 µL/test) with a 5-min incubation at room temperature prior to acquisition. No Fc receptor blocking was applied.
Data were acquired on a CytoFLEX flow cytometer (Beckman Coulter) and analyzed using CytoExpert software (version 2.5). A minimum of 10,000 singlet events were acquired per sample. Compensation and threshold settings were established using single-stained controls, blank controls, and 7-AAD controls (details provided in the project report). The gating strategy consisted of FSC/SSC gating, singlet discrimination, exclusion of 7-AAD⁺ dead cells, and identification of CD11b⁺ macrophages. Within live CD11b⁺ cells, CD11b⁺CD86⁺ and CD11b⁺CD206⁺ populations were quantified as M1-like and M2-like macrophages, respectively. Because CD86/CD206 double-positive intermediate populations were observed under the co-culture conditions, M1-like and M2-like populations were quantified using separate gates.

Macrophage marker gene expression analysis by qRT–PCR
After Transwell co-culture, macrophages from the lower chamber were harvested for RNA extraction. Total RNA was extracted using TRIzol reagent according to the manufacturer’s instructions and reverse-transcribed into cDNA. qRT–PCR was performed using TB Green® Premix Ex Taq™ (Tli RNaseH Plus, TaKaRa). ACTB was used as an internal control, and relative gene expression was calculated using the 2⁻ΔΔCt method with the NC group as the calibrator. The mRNA levels of M1-associated markers (CD86 and TNF-α) and M2-associated markers (CD163 and CD206) were quantified.

Statistical analysis
All statistical analyses were performed using GraphPad Prism (version 9.0) and R (version 4.4.1). Data are presented as mean ± SD or median (interquartile range), as appropriate. For comparisons between two groups, unpaired two-tailed Student’s t-test was used for approximately normally distributed data; otherwise, the Mann–Whitney U test was applied. When comparisons involved three or more groups, one-way ANOVA followed by appropriate post hoc multiple-comparison testing was used for approximately normally distributed data; otherwise, the Kruskal–Wallis test followed by Dunn’s post hoc test was applied. Categorical variables were compared using the χ² test or Fisher’s exact test, as appropriate. Kaplan–Meier survival curves were compared using the log-rank test, and univariate and multivariate Cox proportional hazards regression models were used to identify independent prognostic factors. Correlations were assessed using Spearman’s rank correlation coefficient. For high-dimensional analyses (e.g., differential expression and immune checkpoint comparisons), multiple testing was controlled using the Benjamini–Hochberg method when applicable. All statistical tests were two-sided. P < 0.05 was considered statistically significant. In figures, *P < 0.05, **P < 0.01, and ***P < 0.001.

Results

DCTPP1 expression in pan-cancer and BRCA
Analysis of the TIMER2.0 database showed increased DCTPP1 expression across multiple cancer types, including BRCA (Fig. 1). Within the TCGA–BRCA cohort, DCTPP1 mRNA levels were significantly higher in tumor tissues than in normal breast tissues (Fig. 2A, P < 0.001). This upregulation was further validated in 98 paired samples, where DCTPP1 expression was consistently higher in tumors than in adjacent non-tumor tissues (Fig. 2B, P < 0.001). Comparable results were observed in the GSE42568 dataset (104 tumor vs. 17 normal samples; Fig. 2C, P < 0.001). At the protein level, Human Protein Atlas (HPA) data supported higher DCTPP1 protein expression in BRCA tissues relative to normal controls (Fig. 2D–G). Single-cell transcriptomic profiling using the TISCH2 database revealed that DCTPP1 was predominantly expressed in malignant cells and proliferating T cells, suggesting a potential association with tumor cell proliferation and immune-related cellular programs (Fig. 2H–J).

Association of DCTPP1 expression with clinicopathological features in BRCA
DCTPP1 expression was significantly associated with selected clinicopathological characteristics in BRCA. Higher DCTPP1 expression was significantly associated with N stage (Fig. 3B,G) and PAM50 molecular subtype (Fig. 3F). In addition, patients aged > 65 years exhibited higher DCTPP1 expression than those aged ≤ 65 years (Fig. 3D, P = 0.0013). No significant associations were observed between DCTPP1 expression and T stage (Fig. 3A), M stage (Fig. 3C), or overall stage (Fig. 3E). Subtype-specific analyses revealed that, in basal-like tumors, DCTPP1 expression was significantly associated with T stage, N stage, and overall stage (Fig. 3H–J). In Luminal B tumors, DCTPP1 expression was significantly associated with overall stage (Fig. 3L).

Prognostic significance of DCTPP1 in BRCA
Kaplan–Meier analysis of the TCGA cohort showed that patients with high DCTPP1 expression had significantly shorter OS than those with low expression (Fig. 4A, P < 0.001). This finding was validated in the GSE42568 (P = 0.02) and GSE45255 (P = 0.0014) datasets (Fig. 4F–G). Subtype-specific analysis indicated that high DCTPP1 expression was significantly associated with shorter OS in basal-like tumors (Fig. 4B, P = 0.005), whereas no significant association was observed in Luminal A, Luminal B, or HER2 + subtypes (Fig. 4C–E).
Time-dependent ROC analysis further evaluated the prognostic performance of DCTPP1 expression. The AUC values for OS prediction were as follows (Fig. 4H–L): Luminal A (5 years: 0.515; 10 years: 0.604; 15 years: 0.706), Luminal B (1 year: 0.869; 3 years: 0.751; 5 years: 0.688), HER2+ (5 years: 0.729; 10 years: 0.876; 15 years: 0.950), basal-like (5 years: 0.709; 10 years: 0.793; 15 years: 0.726), and all patients (5 years: 0.619; 10 years: 0.674; 15 years: 0.692). Collectively, these results suggest that DCTPP1 may serve as a prognostic biomarker in BRCA. Univariate (P < 0.001) and multivariate (P = 0.011) Cox regression analyses showed that high DCTPP1 expression remained an independent prognostic factor for OS (Fig. 4M–N).
Subgroup analysis further showed that high DCTPP1 expression was associated with reduced OS in patients with T1–T2 (P = 0.001), T2 (P = 0.001), N1–N3 (P = 0.002), M0 (P < 0.001), stage I–II (P = 0.001), stage II (P < 0.001), and age ≤ 65 years (P < 0.001) (Fig. 4O–U).

Association of DCTPP1 expression with tumor immunity in BRCA
CIBERSORT analysis of inferred immune cell fractions (Fig. 5A) showed significant positive correlations between DCTPP1 expression and the estimated abundance of M0 macrophages (Fig. 5G, P < 0.001) and M2 macrophages (Fig. 5I, P < 0.001). In contrast, DCTPP1 expression showed significant negative correlations with γδ T cells (Fig. 5B, P = 0.03), activated dendritic cells (Fig. 5C, P < 0.05), CD8⁺ T cells (Fig. 5D, P = 0.02), resting memory CD4⁺ T cells (Fig. 5E, P = 0.005), activated memory CD4⁺ T cells (Fig. 5F, P < 0.001), and M1 macrophages (Fig. 5H, P = 0.002).
ESTIMATE analysis showed that tumors with low DCTPP1 expression had significantly higher immune scores (Fig. 5J, P < 0.001), stromal scores (Fig. 5K, P < 0.001), and ESTIMATE scores (Fig. 5L, P < 0.001), but lower tumor purity (Fig. 5M, P < 0.001) than those with high expression. These findings suggest higher immune and stromal content in the TME when DCTPP1 expression is low.

Association of DCTPP1 expression with immune checkpoints and immunotherapy response in BRCA
Considering the therapeutic potential of immune checkpoint inhibitors (ICIs) in BRCA, we examined the relationship between DCTPP1 expression and major immune checkpoint genes. The high DCTPP1 expression group exhibited significantly lower expression of several immune checkpoint genes (Fig. 6A), including CD274 (PD-L1) (P = 0.007), CTLA4 (P < 0.001), PDCD1 (PD-1) (P = 0.006), and PDCD1LG2 (PD-L2) (P = 0.001) (Fig. 6B–F).
IPS analysis showed that the low DCTPP1 expression group had significantly higher IPS values across various anti-PD-1 and anti-CTLA4 therapy scenarios (Fig. 6G–J; all P < 0.001), suggesting a higher predicted likelihood of response to ICIs in patients with low DCTPP1 expression.

Functional enrichment analysis of DCTPP1-related DEGs in BRCA
Differential expression analysis identified 282 upregulated and 1,487 downregulated DEGs between the high- and low-DCTPP1 expression groups (|log2FC| > 0.5, P < 0.05), visualized using a volcano plot and heatmap (Fig. 7A,B). GO enrichment analysis showed that these DEGs were enriched in biological processes (BP) including immune effector regulation, lymphocyte differentiation, humoral immune response, T-cell activation, and cytotoxicity (Fig. 7C), cellular components (CC) primarily involving transmembrane transporter and ion channel complexes (Fig. 7D), and molecular functions (MF) related to cytokine activity, G-protein-coupled receptor binding, and immunoreceptor activity (Fig. 7E). KEGG pathway analysis indicated enrichment in pathways such as neuroactive ligand–receptor interaction, primary immunodeficiency, cell adhesion molecules, and cytokine–cytokine receptor interaction (Fig. 7F). GSEA further highlighted enrichment of hallmark gene sets, including MYC targets v2, DNA repair, interferon-γ response, and IL6–JAK–STAT3 signaling (Fig. 7G–J).
Given the pivotal role of MYC in tumor progression, we examined its correlation with DCTPP1 using the TIMER3.0 database, showing significant positive correlations in basal-like (P < 0.001), HER2+ (P = 0.0058), and luminal B (P = 0.0015) subtypes (Fig. 7K–M). Based on the enrichment of MYC targets v2 and the observed positive correlation between DCTPP1 and MYC, we further explored the Wnt/β-catenin signaling pathway, a known upstream regulator of MYC. Correlation analyses across various BRCA cohorts showed that DCTPP1 expression was significantly positively correlated with AXIN1 in the pan-BRCA cohort and across all molecular subtypes (HER2-enriched, luminal A, luminal B, and basal-like) (Fig. 7N–R). Similarly, DCTPP1 expression was significantly correlated with AXIN2 in the pan-BRCA cohort and the HER2-enriched subtype (Fig. 7S,T). Furthermore, a significant positive correlation was observed between DCTPP1 and CCND1 expression in all BRCA patients (Fig. 7U). Collectively, these correlations across multiple Wnt/β-catenin pathway components are consistent with a potential association between DCTPP1 expression and Wnt/β-catenin pathway activity in BRCA, which may contribute to tumor progression.

DCTPP1 expression assessed by mIHC and its association with macrophage infiltration
TMA analysis showed significantly higher DCTPP1 protein expression in BRCA tissues compared with adjacent non-tumor tissues (Fig. 8A, P < 0.01). Immunofluorescence staining further supported this differential expression between tumor and matched adjacent non-tumor tissues (Fig. 9A–F). mIHC evaluating the co-expression of CK, CD68, CD163, and DCTPP1 showed that DCTPP1 was expressed in both tumor cells (CK⁺) and macrophages (CD68⁺) (Fig. 10A–H). Tissues with high DCTPP1 expression exhibited significantly higher CD68⁺CD163⁺ (M2-like) macrophage levels than the low-expression group (Fig. 8B, P = 0.03). Furthermore, Spearman correlation analysis showed a significant positive correlation between DCTPP1 expression and CD68⁺CD163⁺ (M2-like) macrophage abundance (Fig. 8C, P = 0.025).

Association of DCTPP1 expression with pathological features and prognosis in BRCA
TMA analysis showed significant associations between high DCTPP1 protein expression and both N stage (Fig. 11A) and TNM stage (Fig. 11B). Kaplan–Meier survival analysis indicated a trend toward shorter OS in patients with high DCTPP1 expression, although this did not reach statistical significance (Fig. 11C). Univariate Cox regression analysis showed that TNM stage (P < 0.001, HR = 4.480, 95% CI: 2.544–7.887) and LVI (P = 0.002, HR = 2.724, 95% CI: 1.453–5.106) were associated with increased risk of death, whereas CD68⁺CD163⁻DCTPP1⁺ (P = 0.032, HR = 0.444, 95% CI: 0.211–0.932) and CK⁻DCTPP1⁺ (P = 0.040, HR = 0.294, 95% CI: 0.092–0.944) were associated with reduced risk. Notably, positive DCTPP1 expression in tumor parenchyma (CK⁺DCTPP1⁺) showed a trend toward worse OS, although this did not reach statistical significance (P = 0.091, HR = 3.416, 95% CI: 0.822–14.188). Multivariate Cox regression analysis showed that TNM stage (P = 0.022, HR = 2.37, 95% CI: 1.13–4.98) remained an independent prognostic factor for OS in this cohort (Table 2).

DCTPP1 knockdown in BRCA cells modulates macrophage polarization–related gene expression
To further investigate whether tumor cell–intrinsic DCTPP1 modulates macrophage polarization–related gene expression, DCTPP1 was silenced in MCF-7 BRCA cells using lentiviral shRNA. Quantitative real-time PCR confirmed efficient DCTPP1 knockdown, and KD3 showed the greatest reduction relative to the negative control (NC) and was therefore used in subsequent experiments (Fig. 12A, P < 0.001).
THP-1–derived unpolarized macrophages (M0) were then co-cultured with NC or DCTPP1-knockdown (KD3) MCF-7 cells using a Transwell system, and macrophage polarization–related gene expression was quantified by qRT-PCR. Co-culture with DCTPP1-knockdown tumor cells altered the expression of macrophage polarization–related genes. The mRNA levels of M1-associated markers (CD86 and TNF-α) were higher in macrophages co-cultured with DCTPP1-knockdown cells than in the NC group (Fig. 12B,C, P < 0.001). In contrast, the mRNA levels of M2-associated markers (CD163 and CD206) were lower after co-culture with DCTPP1-knockdown MCF-7 cells (Fig. 12D,E, P < 0.001).
To determine whether these transcriptional changes were accompanied by phenotypic alterations, we next quantified M1-like and M2-like macrophage populations by flow cytometry.

Flow cytometric analysis of macrophage polarization following DCTPP1 knockdown in BRCA cells
Consistent with the qRT-PCR findings, we next evaluated macrophage polarization at the phenotypic level by flow cytometry following Transwell co-culture with blank, NC, or KD MCF-7 cells. Within 7-AAD⁻ CD11b⁺ macrophages, M1-like macrophages were identified based on CD86 expression. Representative flow cytometry plots of CD11b⁺CD86⁺ M1-like macrophages from the blank, NC, and KD groups are shown in Fig. 13A–C, respectively. Quantitative analysis showed that the proportion of CD11b⁺CD86⁺ M1-like macrophages was significantly increased in the KD group relative to the NC group (Fig. 13D, P < 0.01).
Similarly, M2-like macrophages were identified based on CD206 expression. Representative flow cytometry plots of CD11b⁺CD206⁺ M2-like macrophages from the blank, NC, and KD groups are shown in Fig. 13E–G, respectively. Statistical analysis showed that the proportion of CD11b⁺CD206⁺ M2-like macrophages was significantly reduced in the KD group relative to the NC group (Fig. 13H, P < 0.01).
Together, these data indicate that DCTPP1 knockdown in BRCA cells is associated with a shift toward an M1-like phenotype and reduced M2-like polarization in co-cultured macrophages.

Discussion
DCTPP1, a key member of the NTP pyrophosphatase family, exhibits tissue-specific expression and functional diversity. Recent studies have reported upregulated DCTPP1 expression in clear cell renal cell carcinoma26 and its involvement in chemoresistance in luminal A BRCA27. In this study, integrated multi-omics analyses and TMA validation demonstrated that both mRNA and protein levels of DCTPP1 were significantly upregulated in BRCA tissues. High DCTPP1 expression was strongly associated with adverse clinicopathological features, including lymph node metastasis and advanced disease stage, and was associated with poor OS.
Beyond these clinical associations, our study provides convergent evidence that DCTPP1 is associated with an immunosuppressive TME in BRCA. Immune deconvolution and ESTIMATE analyses linked high DCTPP1 expression to reduced immune and stromal scores and to altered immune cell infiltration patterns, most notably an enrichment of M2 macrophages. mIHC further supported increased abundance of M2 macrophages in DCTPP1-high tumors. Importantly, functional tumor cell–macrophage co-culture experiments suggested that tumor cell–intrinsic DCTPP1 may modulate macrophage polarization: DCTPP1 knockdown in BRCA cells significantly suppressed M2 polarization while concomitantly promoting M1 polarization. Together, these findings support DCTPP1 as a potential contributor to an M2 macrophage–enriched, immunosuppressive microenvironment in BRCA.
DCTPP1 has previously been reported to promote BRCA cell proliferation through participation in DNA repair signaling and regulation of DNA methylation homeostasis28,29. Our results extend these findings by highlighting an immunological dimension of DCTPP1 in the TME. TAMs are key regulators of tumor progression, promoting angiogenesis, immune evasion, extracellular matrix remodeling, and metastatic dissemination30,31. In this context, the observed shift toward reduced M2 and increased M1 macrophage signatures following DCTPP1 knockdown supports a functional link between tumor cell–intrinsic DCTPP1 and macrophage-mediated immunosuppression in BRCA.
To explore potential mechanisms underlying the immunomodulatory effects of DCTPP1, we performed functional enrichment analyses. GSEA revealed a strong association between DCTPP1 expression and the MYC targets v2 pathway, and DCTPP1 expression was positively correlated with MYC expression in basal-like, HER2-positive, and luminal B BRCA subtypes. Prior studies have identified DCTPP1 as a MYC-responsive gene, with downregulation observed following MYC suppression32 and upregulation during MYC-driven malignant transformation33. DCTPP1 has also been reported to act as a positive regulator of the canonical Wnt/β-catenin signaling pathway through cooperation with USP734. Aberrant activation of Wnt/β-catenin signaling has been shown to suppress antitumor immunity, including inhibition of macrophage phagocytic activity35,36, and MYC activation downstream of Wnt signaling has been implicated in promoting M2 macrophage polarization37. In line with these reports, we observed consistent positive correlations between DCTPP1 expression and key Wnt/β-catenin pathway components, including AXIN1, AXIN2, and CCND1, across multiple BRCA subtypes. These findings suggest that DCTPP1 may contribute to macrophage polarization through a Wnt/β-catenin–MYC–associated regulatory axis. In addition, GSEA indicated associations between DCTPP1 and pathways related to DNA repair and interferon-γ response, suggesting broader roles for DCTPP1 in genomic stability and immune regulation38–40.
ICIs exert their antitumor effects by reversing tumor-mediated immune suppression and enhancing antitumor immune responses41–43. In this study, low DCTPP1 expression was associated with higher expression of immune checkpoint genes and elevated immunophenoscore (IPS) values, suggesting a higher predicted likelihood of response to ICI therapy. Given the established role of M2 macrophages in mediating resistance to immunotherapy, our findings further suggest that DCTPP1-driven macrophage polarization may represent a potential mechanism of immune evasion in BRCA. Thus, DCTPP1 expression levels may warrant further investigation as a potential predictor of immunotherapy response, and targeting DCTPP1 may represent a potential strategy to improve ICI efficacy in future studies.
This study has several limitations. The functional evidence is derived from in vitro co-culture systems, which may not fully recapitulate the complex TME in vivo. Additionally, mechanistic insights rely primarily on correlative pathway analyses rather than direct molecular validation. Future work should include cytokine profiling, targeted pathway perturbations, and in vivo models to identify the precise mediators of DCTPP1-driven macrophage reprogramming and confirm its translational relevance.

Conclusion
In summary, DCTPP1 is upregulated in BRCA at both the transcript and protein levels and is associated with unfavorable survival and a macrophage-related, immunosuppressive TME. Tumor cell–macrophage co-culture experiments further support that tumor cell–intrinsic DCTPP1 is linked to a shift toward M2-like polarization and reduced M1-like features in co-cultured macrophages. Collectively, these findings suggest that DCTPP1 may serve as a prognostic biomarker and a potential target for future studies aimed at modulating tumor immunity in BRCA.

Supplementary Information
Below is the link to the electronic supplementary material.