M2 macrophages promote lymphatic metastasis by regulating PKM2 nuclear translocation in triple-negative breast cancer
Yuqin Yang, Honghui Ye, Di Zhong, Jian Gao, Miao Yu, Lei Chen, Ruoshi Zhou, Liguo Zhang, Yunyan Cong, Zhen Qiao, Lixin Guan, Yinyan Mao, Zhiping Li, Wenjing Tian, Bin Zhao, Hong Zhao
TL;DR
This study shows how M2 macrophages help triple-negative breast cancer spread to lymph nodes by influencing a protein called PKM2, offering a new target for treatment.
Contribution
The study identifies a novel mechanism by which M2 macrophages drive lymphatic metastasis in TNBC through PKM2 regulation.
Findings
M2 macrophage-derived TGF-β increases glycolysis and lymphatic metastasis in TNBC via PKM2.
Pharmacological inhibition of PKM2 reduces lymphatic metastasis by blocking VEGFC/D expression.
High M2 macrophage infiltration correlates with poor survival in TNBC patients.
Abstract
Triple-negative breast cancer (TNBC), the most aggressive breast cancer subtype, is characterised by poor prognosis and frequent lymph node metastasis (LNM), a hallmark of disease progression. Crosstalk between TNBC cells and M2-polarized macrophages drives malignant progression, but the specific mechanisms underlying M2 macrophage-mediated LNM in TNBC remain poorly defined. This study revealed that M2 macrophage-derived TGF-β increases glycolysis and lymphatic metastasis in TNBC via a PKM2-centred axis. TGF-β dually regulates PKM2 by transcriptionally upregulating its expression and posttranslational phosphorylation. This dual regulation drives PKM2-mediated metabolic reprogramming to increase tumour glucose uptake while promoting the nuclear translocation of p-PKM2, which transcriptionally activates the lymphatic growth factors VEGFC/D. VEGFC/D subsequently stimulates VEGF-dependent…
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Figure 8- —https://doi.org/10.13039/501100001809National Natural Science Foundation of China (National Science Foundation of China)
- —Guangdong Medical Science and Technology Research Foundation (No. A2022462)
- —Zhuhai science and technology plan project in the field of social development (No. 2420004000202)
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Taxonomy
TopicsImmune cells in cancer · Lymphatic System and Diseases · Cancer, Hypoxia, and Metabolism
Introduction
As a special molecular subtype of breast cancer, triple-negative breast cancer (TNBC, which is characterised by the absence of oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2), is characterised by its highly aggressive and metastatic properties [1–3]. At initial diagnosis, TNBC patients exhibit a significantly higher incidence of lymph node metastasis (LNM) compared with that of patients with other breast cancer subtypes [4, 5]. As LNM not only facilitates distant organ colonisation by disseminating tumour cells but also serves as one of the most informative prognostic indicators for solid malignancies [6, 7], elucidating the molecular mechanisms driving LNM pathogenesis in TNBC holds significant translational value. Such insights could accelerate the development of novel therapeutic strategies and improve the identification of promising molecular targets to mitigate metastatic progression.
Emerging evidence highlights the critical role of vascular endothelial growth factor C and D (VEGFC/D), key mediators of lymphangiogenesis, in promoting regional LNM and predicting adverse clinical outcomes across multiple cancer types [8–12]. Mechanistically, VEGFC/D binding induces vascular endothelial growth factor receptor 3 (VEGFR3) homodimerization and subsequent tyrosine kinase autophosphorylation, initiating a signalling cascade that drives lymphatic endothelial cell differentiation and tumour-associated lymphangiogenesis [7]. Preclinical studies further demonstrated that blockade of the VEGFC/D/VEGFR3 axis effectively suppressed tumour dissemination through lymphatic vessels [12, 13]. However, despite their well-established prometastatic functions, the precise contributions of VEGFC/D to LNM pathogenesis in TNBC remain poorly characterised. Elucidating the TNBC-specific regulatory mechanisms of VEGFC/D and their therapeutic relevance may not only reveal novel biomarkers for early LNM detection but also guide the development of targeted antilymphangiogenic therapies to improve patient survival.
Tumour-associated macrophages (TAMs), particularly the protumoral M2-polarized subset, constitute a dominant immune population within the tumour microenvironment (TME) and serve as independent predictors of adverse clinical outcomes across various malignancies [14, 15]. These cells functionally orchestrate multiple protumorigenic processes through sustained immunosuppression [16], angiogenesis [17], extracellular matrix remodelling [18] and immune checkpoint ligand upregulation [19], collectively enabling metastatic dissemination and treatment resistance. In TNBC, spatial enrichment of M2-like TAMs (CD163+ phenotype) is correlated with aggressive clinicopathological features—including epithelial–mesenchymal transition (EMT) signature activation [20], cancer stem cell enrichment [21] and compromised responses to chemotherapy and immune checkpoint blockade [22, 23]. Paradoxically, while M2 macrophages are mechanistically linked to metastatic progression, their functional crosstalk with TNBC cells in the context of LNM remains elusive.
In this study, an unbiased screening revealed pyruvate kinase M2 (PKM2) as the central effector of M2 macrophage-driven VEGFC/D upregulation and lymphangiogenesis in TNBC. Through integrative mechanistic dissection, we revealed that transforming growth factor beta (TGF-β) derived from M2 macrophages coordinates lymphatic metastasis through dual PKM2-centric mechanisms—inducing the overexpression of PKM2 to amplify glycolytic flux while simultaneously driving its phosphorylation-dependent nuclear translocation. Within the nucleus, PKM2 functions as a transcriptional activator to directly potentiate VEGFC/D expression, thereby fuelling prometastatic lymphatic remodelling. The translational relevance of this PKM2/VEGFC/D axis was validated through targeted inhibition of PKM2, which effectively suppressed lymphangiogenic signalling and lymphatic metastasis, highlighting its potential value in clinical therapeutic strategies.
Results
M2 macrophages correlate with LNM and poor prognosis in TNBC
As a first approach, we applied imaging mass cytometry (IMC) to 6 TNBC tissues to profile the TME between patients with and without LNM. The immune microenvironment landscape significantly differed between the groups and tumour-infiltrating CD163 + M2 macrophages were among the markedly increased infiltrating immune cells in patients with LNM (Figs. 1A, B and S1). This finding aligns with the established roles of M2-polarized macrophages in fostering metastatic progression [20].Fig. 1M2 macrophages correlate with LNM and poor prognosis in TNBC patients.A Representative IMC images of the TNBC tissues of patients with/without LNM. Scale bar: 100 μm. B t-SNE visualisation of the spatial distribution of CD163+ macrophages in 6 TNBC patients (3 LNM+ vs. 3 LNM−). C Representative images (left panels) and percentages (middle and right panels) of tissue samples from 64 patients with TNBC with high and low numbers of CD163 + M2 macrophages and LYVE1+ microlymphatic vessels. Scale bar: 100 μm. D, E Correlations of CD163+ macrophage infiltration with T stage and vimentin level in 64 TNBC cases analysed by IHC staining. F The DFS and OS of 64 patients with TNBC based on the levels of CD163+ macrophages. Analysis was performed using Kaplan–Meier estimates and two-sided log-rank tests. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
To validate these findings, immunohistochemical (IHC) analysis was extended to an independent 64-case TNBC cohort. Consistent with the IMC results, LNM tumours exhibited significantly higher infiltration of CD163 + M2 macrophages compared with those in non-LNM patients, while the CD86 + M1 macrophage level did not differ between the two groups (Figs. 1C and S2A). Moreover, elevated M2 macrophage infiltration correlated with increased tumour diameter and upregulated expression of vimentin, a hallmark of EMT (Figs. 1D, E and S2B).
Clinically, high M2 macrophage infiltration was significantly associated with a shorter disease-free survival (DFS) and overall survival (OS) (Fig. 1F). Bioinformatics validation using bc-GenExMiner v5.1 further revealed that elevated CD163 expression was strongly correlated with adverse prognosis in TNBC (Fig. S2C). Notably, compared with other breast cancer subtypes, TNBC exhibited significantly higher M2 macrophage infiltration levels (quantified by CD163/CD206 staining) (Fig. S2D). These convergent findings collectively reinforce the tumour-promoting role of M2 macrophages, particularly in TNBC pathogenesis.
M2 macrophages facilitate lymphangiogenesis and LNM in TNBC
Tumour-associated lymphangiogenesis, a recognised independent prognostic factor in TNBC patients, is significantly associated with LNM [24]. IHC analysis revealed a significant correlation between CD163 + M2 macrophage infiltration and microlymphatic vessel density (MVD) quantified through lymphatic vessel endothelial hyaluronan receptor-1 (LYVE1)–positive microvessels in TNBC specimens (Figs. 1C and 2A), suggesting the potential involvement of M2 macrophages in tumour-associated lymphangiogenesis.Fig. 2M2 macrophages facilitate lymphangiogenesis and LNM in TNBC.A Correlation of CD163+ macrophage infiltration with LYVE1+ microlymphatic vessels in 64 TNBC specimens. B qPCR validation of M2 polarization: upregulated CD163, CD206 and ARG1 expression and downregulated CD80, CD86 and iNOS expression compared with those in M0 controls. C ICC confirming CD163 membrane localisation (green) in polarized M2 macrophages. Nuclei were counterstained with DAPI (blue). D Representative images (left panels) and histogram quantification (right panel) of the Matrigel tube formation assay with HLECs. HLECs were cultured with CM derived from TNBC cancer cells that were treated as indicated. Scale bars: 200 μm. E Representative images (left panels) and histogram quantification (right panel) of the results of the Transwell migration assay with HLECs. Scale bars: 100 μm. F Left: Representative images of popliteal LNs from mice injected with 4T1 cells with/without preexposure to M2 macrophages (n = 6/group). Right: histogram analysis of the LN volumes. G Representative images of popliteal LNs analysed by H&E staining and IHC staining using an anti-CK antibody. Scale bars: 100 μm. H The ratio of metastatic to total enucleated popliteal LNs in the indicated groups. I Left: Representative images of H&E staining and IHC staining with anti-LYVE1 in footpad tumours; right: histogram analysis of the MVD in different groups. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
We next constructed an M2 macrophage model in vitro and confirmed its successful construction by quantitative reverse transcription PCR (qPCR) and immunocytochemical (ICC) analysis (Fig. 2B, C), which revealed a proper model for further coculture with TNBC cells (4T1 and EMT6).
The prolymphangiogenic potential of M2 macrophages was systematically evaluated through functional assays. Conditioned medium (CM) from M2 macrophage-cocultured TNBC cells significantly increased the tube formation capacity of human lymphatic endothelial cells (HLECs) (Fig. 2D) and accelerated HLEC migration, as determined by Transwell assays (Fig. 2E). To further investigate LNM regulation, we used a footpad tumour-popliteal LNM model. Macroscopic analysis revealed substantially enlarged popliteal LNs in M2 macrophage-cocultured mice compared with those in control mice (Fig. 2F). Pancytokeratin (CK) immunostaining confirmed the increased metastatic potential to popliteal LNs, as evidenced by the increased metastatic ratio (Fig. 2G, H). Consistent with these findings, xenografted tumours from the M2 coculture group exhibited elevated MVD (Fig. 2I). Collectively, these findings demonstrate the critical involvement of M2 macrophages in TNBC lymphangiogenesis and LNM.
M2 macrophages drive lymphangiogenesis via a VEGFC/D-dependent mechanism
The lymphangiogenic factors VEGFC and VEGFD are critically involved in mediating tumour-associated lymphangiogenesis [8–12]. To investigate their potential role in M2 macrophage-driven lymphangiogenesis in TNBC, we systematically analysed their expression patterns under macrophage–TNBC coculture conditions. Coculture with M2 macrophages induced significant upregulation of VEGFC/D at both the transcriptional and translational levels in TNBC cells, as evidenced by the results of qPCR and WB analyses (Fig. 3A, B). Secretion of these cytokines was further quantified via ELISA, which revealed substantial increases in the levels of both factors in M2 macrophage-cocultured CM (Fig. 3C), confirming that M2 macrophages regulate the expression of these prolymphangiogenic mediators.Fig. 3M2 macrophages drive lymphangiogenesis via a VEGFC/D-dependent mechanism.A qPCR, B WB and C ELISA assessing the expression and secretion of VEGFC/D after coculture with M0 or M2 macrophages. D qPCR, E WB and F ELISA analysis of the efficiency of shRNA-mediated knockdown of VEGFC/D in 4T1 cells. G Representative images (upper panels) and histogram quantification (lower panels) of the Matrigel tube formation assay with HLECs. HLECs were cultured with CM derived from TNBC cells that were treated as indicated. Scale bars: 200 μm. H Representative images (upper panels) and histogram quantification (lower panels) of the results of the Transwell migration assay with HLECs. Scale bars: 100 μm. I Left: representative images of H&E staining and IHC staining for VEGFC/D in footpad tumours; right: histogram of the quantification of the H-score of VEGFC/D. Scale bars: 100 μm. J Left: representative images of IHC staining of CD163 and VEGFC/D in TNBC specimens; right: correlation analysis between the infiltration of CD163+ macrophages and VEGFC/VEGFD expression levels. Scale bars: 100 μm. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
Functional validation through dual genetic and pharmacological approaches demonstrated their effects on lymphangiogenic processes. shRNA-mediated knockdown of VEGFC or VEGFD (validation of the transfection efficiency is shown in Figs. 3D–F and S3A–C) partially attenuated M2 macrophage-induced tube formation and HLEC migration, whereas combined silencing nearly abolished these lymphangiogenic effects (Fig. 3G, H). Consistent with these results, the results of complementary antibody neutralisation experiments using specific antibodies revealed the synergistic suppression of lymphatic endothelial activation (Fig. S3D, E), confirming the functional contribution of VEGFC/D signalling to prolymphangiogenic processes.
In vivo validation through 4T1 xenograft models revealed a significant increase in VEGFC/D expression in footpad tumours from the M2 macrophage-cocultured group (Fig. 3I). Clinical correlation analyses using a 64-patient TNBC cohort demonstrated strong positive associations between CD163 + M2 macrophage infiltration and VEGFC/D expression levels (Fig. 3J), which was further corroborated through TIMER 2.0 database mining (Fig. S3F). Notably, this association persisted across luminal A/B subtypes but was not statistically significant in HER2-enriched breast cancer (Fig. S3G–I). These findings reveal that VEGFC/D is a pivotal mediator of M2 macrophage-driven lymphangiogenesis during TNBC progression.
TGF-β is responsible for the M2 macrophage-mediated lymphangiogenesis of TNBC cells
To identify M2 macrophage-secreted factors responsible for VEGFC/D upregulation in tumours, we performed a qPCR array analysis targeting macrophage-associated cytokines that compared M0 and M2 macrophages. This analysis revealed that TGF-β was the most significantly increased cytokine in M2-polarized cells, with concurrent increases in the levels of interleukin-10 (IL-10) and IL-6 (Fig. S4A). ELISA quantification of the cellular supernatants confirmed that compared with the M0 controls, M2 macrophages secreted more TGF-β protein (Fig. S4B). Immunofluorescence colocalization further suggested that M2 macrophages were among the important sources of TGF-β in the TME of TNBC (Fig. 4A).Fig. 4TGF-β is responsible for M2 macrophage-mediated lymphangiogenesis in TNBC cells.A Immunofluorescence staining of TNBC tissue sections. The colocalization of CD163 and TGF-β is indicated in yellow. B qPCR and C WB assessing the expression and secretion of VEGFC/D in 4T1 and EMT6 cells after treatment with rTGF-β. D qPCR, E WB and F ELISA analysis of VEGFC/D in 4T1 and EMT6 cells after neutralisation of TGF-β. G, H Representative images (left panels) and histogram quantification (right panel) of the Matrigel tube formation assay (scale bars: 200 μm) and Transwell migration assay (scale bars: 100 μm) with HLECs. HLECs were cultured with CM derived from TNBC cells that were treated with or without rTGF-β. I, J Representative images (left panels) and histogram quantification (right panels) of the Matrigel tube formation assay (scale bars: 200 μm) and Transwell migration assay (scale bars: 100 μm) with HLECs. HLECs were cultured with CM derived from TNBC cells that were treated as indicated. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
Mechanistic studies demonstrated that rTGF-β treatment upregulated both VEGFC and VEGFD expression in TNBC cells at the mRNA and protein levels (Figs. 4B, C and S4C). Conversely, antibody-mediated neutralisation or knockdown (via siRNA) of TGF-β significantly attenuated M2 macrophage-induced upregulation of VEGFC/D expression in TNBC cells (Figs. 4D–F and S4D–G).
Functional validation through lymphangiogenesis assays demonstrated that CM from rTGF-β-treated TNBC cells robustly stimulated HLEC tube formation (Fig. 4G) and migration (Fig. 4H). These prolymphangiogenic effects were abolished by TGF-β blockade through the use of either neutralising antibodies (Fig. 4I, J) or siRNA silencing (Fig. S4H, I). Clinical correlation analysis utilising the TIMER 2.0 database further revealed robust positive associations between TGF-β1 expression and VEGFC/D/LYVE1 levels in TNBC specimens (Fig. S4J), thereby validating the clinical significance of this regulatory axis. Notably, this axis was also identified in the luminal A/B- and HER2-enriched subtypes, with the expression of TGF-β1 significantly correlated with the expression of VEGFC and/or VEGFD and with LYVE1 levels (Fig. S4K–M).
These data collectively establish TGF-β as a critical M2 macrophage-secreted factor that drives VEGFC/D-dependent lymphangiogenesis during TNBC progression.
Nuclear translocation of PKM2 is required for TGF-β-induced VEGFC/D expression in TNBC
To elucidate the mechanisms underlying TGF-β-mediated VEGFC/D expression in TNBC, we performed RNA sequencing analysis to compare the transcriptomic profiles of control and rTGF-β-treated 4T1 cells. Differential expression analysis (P < 0.05, |fold change (FC)|> 2) revealed 1126 significantly regulated genes, including 356 upregulated and 770 downregulated genes (Fig. 5A, B). Gene set enrichment analysis (GSEA) demonstrated pronounced enrichment of glycolytic pathway genes in rTGF-β-treated cells (Fig. 5C) a finding corroborated by functional validation showing increased glucose uptake capacity (Fig. 5D).Fig. 5. Nuclear translocation of PKM2 is required for TGF-β-induced VEGFC/D expression in TNBC.A Volcano plot of RNA sequencing data from 4T1 cells treated with rTGF-β. B Heatmap clustering of DEGs enriched in rTGF-β-treated vs. control cells. Significance was defined as a P < 0.05 and a fold change >2. C GSEA showing the activation of glycolytic pathways. D Effects of rTGF-β on glucose uptake in 4T1 and EMT6 cells. E qPCR screening of glycolytic genes in 4T1 and EMT6 cells treated with or without rTGF-β. F WB analysis of the PKM2 protein in rTGF-β-treated 4T1 and EMT6 cells. G WB analysis of VEGFC/D expression in 4T1 and EMT6 cells after the deletion of PKM2. H WB and I ICC analysis assessed the nuclear translocation of PKM2 in 4T1 and EMT6 cells treated with rTGF-β. J WB assessment of VEGFC and VEGFD expression in TNBC cells after inhibition of PKM2 nuclear translocation with shikonin. K Representative images (left panels) and histogram quantification (right panel) of the Matrigel tube formation assay with HLECs. HLECs were cultured with CM derived from 4T1 and EMT6 cells that were treated as indicated. Scale bars: 200 μm. L Representative images (left panels) and histogram quantification (right panel) of the results of the Transwell migration assay with HLECs. HLECs were cultured with CM as indicated. Scale bars: 100 μm. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
To identify the key glycolytic genes that might be important for the overexpression of VEGFC/D, we conducted comparative qPCR screening of rTGF-β- versus PBS-treated TNBC cells. The results revealed significant differences in several metabolic enzymes, including PKM2, glucose transporter 1 (GLUT1) and lactate dehydrogenase A (LDHA) (Fig. 5E). PKM2 functions as both a cytosolic metabolic enzyme and a transcriptional coactivator, affecting downstream signalling pathways in tumour cells [25]. Thus, we focused on investigating whether PKM2 regulates VEGFC/D expression in TNBC cell lines. We found that the expression of PKM2 and VEGFC/D was significantly upregulated by the addition of rTGF-β to TNBC cells and that PKM2 deletion partly reversed this effect (Figs. 5F, G and S5A, B).
It has been reported that PKM2, in the form of phospho-PKM2, enters the nucleus as a transcriptional coactivator to regulate the expression of targeted genes [26]. WB of the subcellular fractions revealed that rTGF-β promoted PKM2 phosphorylation and nuclear translocation (Fig. 5H). Immunofluorescence staining also clearly demonstrated the phenomenon of PKM2 nuclear translocation after rTGF-β treatment (Fig. 5I). Moreover, pharmacological inhibition of PKM2 phosphorylation and nuclear translocation using shikonin (a selective PKM2 inhibitor) significantly attenuated VEGFC/D expression in both rTGF-β-treated cells (Figs. 5J and S5C, D) and M2 macrophage-CM-exposed TNBC cells (Fig. S5E–G). Furthermore, the tube formation and migration of HLECs were both significantly promoted after treatment with CM from rTGFβ-treated cells, while PKM2 knockdown or pharmacological blockade diminished the prolymphangiogenic effect (Fig. 5K, L and S5H, I). To further investigate this regulatory axis, bioinformatics validation by TIMER 2.0 was conducted, which demonstrated a positive correlation between TGF-β1 and PKM2 expression in luminal A/B breast cancer patients, whereas no significant association was observed in patients with the HER2-enriched subtype (Fig. S5J–L).
These findings mechanistically establish that M2 macrophage-derived TGF-β drives VEGFC/D-mediated lymphangiogenesis in TNBC through a PKM2 phosphorylation/nuclear localization-dependent axis.
PKM2 inhibition abrogates M2 macrophage-induced LNM in vivo
Mechanistic studies demonstrated that pharmacological inhibition of PKM2 effectively attenuated VEGFC/D expression and cancer-associated lymphangiogenesis in vitro. We subsequently evaluated the therapeutic potential of PKM2 targeting in our established popliteal LNM model (Fig. 6A). Shikonin treatment effectively attenuated M2 macrophage-driven tumour progression in draining LNs, as demonstrated by significant reductions in the volume and metastatic ratio of popliteal LNs. (Fig. 6B–D). The time-weight curve of the mice suggested that the drug did not exhibit significant toxicity towards growth in the mice (Fig. 6E). IHC analysis further demonstrated shikonin-mediated suppression of VEGFC/D expression and decreased intratumoral lymphatic vessel density in M2 macrophage-cocultured xenografts (Figs. 6F and S6A–C). These findings collectively establish PKM2 inhibition as an effective strategy to counteract M2 macrophage-driven lymphangiogenesis and LNM in TNBC.Fig. 6PKM2 inhibition abrogates M2 macrophage-induced LNM in vivo.A Schematic of the popliteal LNM model with shikonin intervention. B Images of enucleated popliteal LNs (left panel) inoculated with the indicated cells (n = 6 per group) and histogram analysis of LN volume (right panel). C Representative images of popliteal LNs analysed by H&E staining and IHC staining using an anti-CK antibody. Scale bars: 100 μm. D The ratio of metastatic to total enucleated popliteal LNs in the indicated groups. E Mouse body weight trajectories during treatment. F Representative images of H&E staining and IHC staining for VEGFC, VEGFD and LYVE1+ lymphatic vessels in footpad tumours. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
Clinical relevance of the CD163 + M2 macrophage/TGF-β/PKM2/VEGFC–
VEGFD axis in TNBC patients
The associations among CD163 + M2 macrophages, PKM2, VEGFC, VEGFD and LYVE1 were further analysed in human TNBC samples. Representative cases are indicated in Fig. 7A. Significant positive correlations were detected between intratumoral CD163 + M2 macrophage infiltration and elevated PKM2/VEGFC/D expression levels, accompanied by increased MVD, as quantified by the presence of LYVE1+ structures (Figs. 2A, 3J and S7A). Patients with high CD163 + M2 macrophage infiltration had significantly shorter DFS and OS (Fig. 1F), with similar prognostic patterns observed in cohorts stratified by PKM2, VEGFC, VEGFD, or MVD levels (Fig. 7B–E).Fig. 7. Clinical relevance of the CD163 + M2 macrophage/TGF-β/PKM2/VEGFC–VEGFD axis in TNBC patients.A Representative IHC staining of sequential TNBC tissue sections showing the expression of CD163, PKM2, VEGFC, VEGFD and LYVE1. Scale bars: 100 μm. Kaplan–Meier survival analysis of the DFS and OS for TNBC patients with low versus high B PKM2, C VEGFC, D VEGFD and E LYVE1 expression/density. The median expression/density was used as the cut-off value. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
Serum analysis in a separate 40-patient TNBC cohort established the clinical significance of TGF-β levels, with significantly higher circulating TGF-β concentrations in patients with LNM than in nonmetastatic patients (Fig. S7B). These observations align with tissue-based findings in which elevated TGF-β signalling correlated with advanced metastatic potential.
Discussion
The propensity of axillary LNs to serve as primary metastatic sites in breast cancer underscores the critical need to elucidate molecular drivers of LNM [27]. Although LNM is a hallmark of disease progression and poor prognosis [6, 7], mechanistic insights into its biological underpinnings—particularly in aggressive TNBC—remain limited. The predilection of TNBC for early lymphatic dissemination [2], coupled with very limited therapeutic options [28], highlights an urgent unmet need to identify actionable targets within the LN metastatic cascade.
Our study identified a novel regulatory axis connecting M2 macrophages, metabolic reprogramming and lymphatic remodelling in TNBC. Specifically, we demonstrated that M2 macrophage-derived TGF-β regulates PKM2 expression through transcriptional upregulation and posttranslational phosphorylation in TNBC cells. This coordinated regulation drives tumour glycolytic flux through PKM2-mediated metabolic reprogramming while simultaneously promoting nuclear translocation of p-PKM2 to activate the transcription of the lymphatic growth factors VEGFC and VEGFD. The resultant VEGFC/D overexpression facilitates VEGF-dependent lymphangiogenesis, ultimately promoting lymphatic metastasis. This integrated pathway, encompassing metabolic adaptation (PKM2-dependent glycolysis), transcriptional activation (p-PKM2 nuclear function) and microenvironment remodelling (VEGF-mediated lymphangiogenesis), provides a mechanistic foundation for the preferential lymphatic metastasis tropism of TNBC. Nevertheless, given the heterogeneous ecosystem of the tumour microenvironment, identifying the potential regulatory roles of other cell types (e.g., cancer-associated fibroblasts and adipocytes) in TNBC lymph node metastasis remains critical, as evidenced by their demonstrated contributions to angiogenesis and metastasis [29, 30]. Future investigations should elucidate the functional contributions and intercellular crosstalk mechanisms underlying distinct cellular components within the TME.
Lymphangiogenesis, a common early metastatic event, serves as both a prognostic biomarker and a promising therapeutic target in solid malignancies because of its indispensable role in LNM [6, 31]. Tumour cells drive pathological lymphangiogenesis through hypersecretion of lymphangiogenic factors, generating structurally defective lymphatic vessels characterised by discontinuous endothelial junctions and deficient mural cell coverage, which are architectural features that facilitate cancer cell intravasation and nodal dissemination [7]. Evidence across multiple cancer types has demonstrated that therapeutic inhibition of lymphangiogenesis significantly reduces regional LNM and improves survival outcomes [32–34]. Our study extends these observations by revealing that, mechanistically, PKM2 nuclear translocation blockade exerts antimetastatic effects through dual lymphangiogenesis suppression: transcriptional inhibition of prolymphangiogenic factor expression and functional impairment of microlymphatic vessel formation. Clinical correlation analyses further revealed PKM2 overexpression as a prognostic indicator of poor TNBC outcomes. Notably, these results provide the first experimental evidence that M2 macrophages promote TNBC lymphatic metastasis by the nuclear shuttling of PKM2, establishing PKM2 as both a metastasis regulator and a candidate therapeutic target through its dual role in tumour-intrinsic metabolic reprogramming and paracrine lymphangiogenic signalling. However, while we focused on investigating lymphangiogenesis and LNM in TNBC, we specifically characterised the role of M2 macrophages in modulating PKM2 expression and nuclear translocation. Notably, although PKM2 has been demonstrated to promote M2 polarization in pancreatic cancer [35], its role in TNBC and potential reciprocal signalling with macrophages remain unexplored.
VEGFC and VEGFD, the two most well-known lymphatic vessel-specific growth factors, critically mediate metastatic progression by disrupting the endothelial lymphatic barrier and facilitating the lymphatic invasion of cancer cells [36–39]. Although their roles in lymphatic metastasis have been established across malignancies, the regulatory specificity of these factors in TNBC remains poorly defined. Our findings demonstrated that M2 macrophage-derived TGF-β drives TNBC-specific VEGFC/D overexpression through a PKM2-dependent transcriptional mechanism, corroborated by markedly elevated VEGFC/D expression in lymph node-metastatic TNBC tissues compared with that in their nonmetastatic counterparts. Functional studies using genetic ablation (shRNA) or antibody neutralisation revealed that concurrent suppression of both VEGFC and VEGFD synergistically attenuated the lymphangiogenic capacity of HLECs. Although TNBC lymphangiogenesis critically depends on the M2 macrophage/TGF-β/VEGFC/D axis, whether TGF-β from other TME cells contributes to LNM remains unclear, as TGF-β is widely expressed in the TME [40–42]. Genetically engineered mouse models with macrophage-specific TGF-β ablation are necessary for further confirmation.
With respect to the specific mechanisms through which M2 macrophages regulate VEGFC/D expression and LNM in TNBC, we identified the core regulatory role of PKM2, a key enzyme in glycolysis [43]. Compared with other key enzymes of glycolysis, PKM2 has diverse structural forms with different functions in tumour progression [25]. It has been reported that PKM2 expression is upregulated in most types of cancer cells and dynamically changes between its tetrameric and dimeric forms [44–47]. The PKM2 tetramer mainly exerts glycolytic enzymatic activity in the cytoplasm [43], whereas the PKM2 dimer, in the form of phosphorylation, has weak enzymatic activity but can act as a transcriptional coactivator in the nucleus to activate targeted molecules and may be the common form in cancer cells, leading to the accumulation of PKM2 upstream intermediates for glycolysis and further providing high levels of metabolic precursors for synthesis [48, 49]. Interestingly, in our study, we found that TGF-β could regulate VEGFC/D expression by promoting PKM2 phosphorylation and nuclear translocation in TNBC cells. Shikonin inhibited the nuclear translocation of PKM2, which prevented VEGFC/D expression and tumour-associated lymphangiogenesis and, thus, LNM in TNBC. Therefore, inhibition of PKM2 by shikonin may play a regulatory role in lymphangiogenesis to inhibit TNBC progression. Another study also demonstrated that blocking PKM2 with shikonin inhibited the proliferation, invasion and migration ability of tumour cells and induced apoptosis. These findings collectively highlight the critical role that PKM2 plays in the progression of TNBC and its inhibition as a promising target for tumour therapy. In our study, although rTGF-β also increased the expression of multiple other glycolysis-related genes and, thus, glucose uptake in TNBC cells, its potential regulation of these genes via the transcriptional coactivation of PKM2 remains unexplored.
Our findings established that M2 macrophage-derived TGF-β orchestrates lymphatic metastasis in TNBC through a PKM2-centred regulatory axis. We demonstrated that TGF-β drives PKM2 overexpression to amplify glycolytic flux while simultaneously inducing its phosphorylation-mediated translocation to the nucleus, where PKM2 functions as a transcriptional coactivator to upregulate VEGFC/D expression to establish prometastatic microlymphatic vessels. Therapeutic targeting of PKM2 with shikonin achieved an effective antimetastatic efficacy by disrupting PKM2-dependent lymphangiogenic signalling (Fig. 8) [50]. In summary, our present study provides mechanistic and translational insights into the lymphatic metastasis of TNBC and suggests that the inhibition of lymphangiogenesis using shikonin may serve as a potential tailored treatment for TNBC patients with a high risk of LNM. Furthermore, this mechanism may extend beyond TNBC to luminal subtypes, as suggested by database mining, indicating the broader therapeutic potential of PKM2 targeting.Fig. 8. Proposed mechanism through which the CD163 + M2 macrophage/TGF-β/PKM2/VEGFC/D axis drives lymphangiogenesis and LNM in TNBC.
Materials and methods
Clinical specimens
The specimens were obtained from patients at the Fifth Affiliated Hospital of Sun Yat-sen University (Zhuhai, China), with histopathological confirmation performed by two independent pathologists. The study received approval from the Ethics Committee of the Fifth Affiliated Hospital of Sun Yat-sen University (K23-1) and written informed consent was obtained from all patients. The clinical and pathological characteristics of the patients are summarised in Table S1.
IMC
Formalin-fixed paraffin-embedded (FFPE) tissue sections (4 µm) were processed using standardised protocols established in our previous methodology [51] and stained with antibody mixtures, including anti-CD163 (1:2000; ab87099; Abcam) and anti-E-cadherin (1:400; 3158029D; Fluidigm) antibodies. Three nonoverlapping regions of interest (ROIs) measuring 500 × 500 μm were systematically selected per slide. Antibody information is detailed in Table S2.
Cell culture
All the cell lines used in our study were purchased from iCell Bioscience, Inc. (Shanghai, China). 4T1 and EMT6 cells were cultured in RPMI-1640 (Gibco, Waltham, USA) and J774a.1 cells were cultured in DMEM (Gibco, Waltham, USA); both cell lines were supplemented with 10% foetal bovine serum (FBS) (Yeasen, Shanghai, China) and 1% penicillin/streptomycin (Yeasen, Shanghai, China). HLECs were kept in endothelial cell growth medium supplemented with 5% FBS and 1% matched growth factor (iCell, Shanghai, China). All the cell lines were cultured in a humidified incubator at 37 °C with 5% CO2. All the cell lines used in this study tested negative for mycoplasma contamination.
M2 macrophage induction and cell coculture model
J774a.1 cells were seeded in 6-well plates and recombinant murine interleukin-4 (mIL-4, 100 ng/mL) (PeproTech, Cranbury, USA) and mouse interleukin-10 (mIL-10, 100 ng/mL) (PeproTech, Cranbury, USA) were added for 24 h to obtain M2 macrophages for subsequent identification and experiments.
M2 macrophages and tumour cell coculture system: 4T1 or EMT6 cells were seeded in the lower chamber of a 6-well plate and M2 macrophages were added to the upper chamber of a 0.4 μm-pore Transwell insert. The ratio of tumour cells to M2 macrophages was 1:1.
Short hairpin RNA (shRNA) and lentiviral transduction
VEGFC-, VEGFD- and PKM2-specific shRNAs selected from the shRNA Library (originally developed by The RNAi Consortium (TRC) at the Broad Institute) were used. High-efficiency knockdown hairpins were chosen. All vectors were obtained from GenePharma (Shanghai, China). Lentiviruses were generated in HEK293FT cells using packaging plasmids (pMD2.G/psPAX2) and corresponding transfer plasmids. Briefly, psPAX2 (15 μg), pMD2.G (7.5 μg) and the transfer plasmid (15 μg) were mixed in 1500 μL of Opti-MEM (Gibco, Waltham, USA). This mixture was combined with Lipofectamine 3000 (30 μL diluted in 500 μL Opti-MEM) (Gibco, Waltham, USA) and incubated at room temperature for 20 min. The transfection complex was added to HEK293FT cells. After 6 h, the medium was replaced with 10 mL of fresh DMEM supplemented with 10% FBS. At 48 and 72 h post-transfection, the lentiviruses were collected and used for lentiviral transduction of cancer cells. Cancer cells were transduced with 5 × 10⁶ transducing units (TUs) of lentivirus. Forty-eight hours post-transduction, the cells were selected with puromycin (5 μg/mL) (Yeasen, Shanghai, China) for 72 h. Surviving cells were subsequently expanded in puromycin-free medium. The targeted sequences of the shRNA used were as follows: VEGFC, 5’-CAGACAAGTTCATTCAATTAT-3’;
VEGFD, 5’-CCCGAGTTAGTGCCTGTTAAA-3’;
PKM2, 5’-GACTGGAAACCCTGACTTTAT-3’.
Transfection of small interfering RNA (siRNA)
TGF-β siRNAs (sense: 5’-GCUGCUACUGCAAGUCAGAGA-3’; antisense: 5’-UCUGACUUGCAGUAGCAGCGG-3’) were purchased from Ruibo (Guangzhou, China) and tumour cells were transfected with Hieff Trans Universal Transfection Reagent (Yeasen, Shanghai, China) and siRNA (50 nM) in FBS-free RPMI 1640 for 6 h. The medium was then replaced with complete growth medium (10% FBS) for 24–36 h prior to harvest.
RNA sequencing and data analysis
4T1 cells were stimulated with 10 ng/mL recombinant TGF-β1 (Yeasen, Shanghai, China) for 12 h. Total RNA was extracted using TRIzol™ Reagent (Thermo Fisher Scientific, Waltham, USA), followed by quality assessment on an Agilent 2100 Bioanalyzer. Ribosomal RNA depletion was performed using the Ribo-Zero™ Gold rRNA Removal Kit (Illumina, San Diego, USA) according to the manufacturer’s protocol. Strand-specific RNA sequencing libraries were prepared and sequenced (150 bp paired-end reads) on an Illumina HiSeq 4000 platform, generating ~40 million reads per sample. P values (<0.05) and |FC| values (>2) were used to define the threshold of significance. The list of all ~19,000 genes was used to perform GSEA to identify significantly (NES > 2, FDR < 0.05) upregulated expression of pathway-associated genes.
Mouse popliteal LNM model and in vivo studies
BALB/c mice (~4–6 weeks old) were obtained from the Experimental Animal Center of Jilin University (Changchun, China) and used to construct a footpad tumour/popliteal LNM model, in which 5 × 10^5^ 4T1 cells were suspended in 20 μl of phosphate-buffered saline (PBS) and injected into the right hind footpad. For the shikonin–treatment assays, shikonin (2.5 mg/kg) (MCE, Monmouth, USA) or PBS was administered via intraperitoneal injection (100 μL volume) every 48 h. The footpad tumours and popliteal lymph nodes (LNs) were resected and embedded in paraffin for further analysis. Footpad tumours could not exceed 200 mm^3^. The tumour volume was calculated using digital calliper measurements and the following formula: tumour volume (mm^3^) = ½ × longest diameter^2^ × shortest diameter. All animal experimental protocols were approved by the Institutional Animal Care and Use Committee of Beihua University (20230152) (Jilin, China).
IHC analysis
IHC analysis was performed to detect target proteins in TNBC tissues, footpad tumours and popliteal LNs. Briefly, 4 µm FFPE sections were dewaxed, rehydrated and then boiled in antigen retrieval buffer (Yeasen, Shanghai, China). After they were incubated with 0.3% hydrogen peroxide (Boster, Wuhan, China), the slides were blocked with 3% BSA (Boster, Wuhan, China). The slides were incubated with primary antibody at 4 °C overnight and then probed with an HRP-conjugated secondary antibody (Boster, Wuhan, China) the next day. DAB chromogen (Boster, Wuhan, China) was applied for signal development, followed by counterstaining with haematoxylin (Macklin, Shanghai, China) and the sections were placed on a Leica DMI1 microscope (Leica, Wetzlar, Germany) to capture images. All antibody-related information is included in Table S2.
qPCR
Total RNA was isolated using TRIzol reagent (Vazyme, Nanjing, China) following the manufacturer’s protocol. First-strand cDNA synthesis was performed using cDNA Synthesis SuperMix (Yeasen, Shanghai, China). qPCR amplification was carried out in triplicate using qPCR SYBR Green Master Mix (Yeasen, Shanghai, China) on an Agilent AriaMx Real-Time PCR System (Agilent, Santa Clara, USA). DNA was amplified using the following thermal cycling conditions: 40 cycles of denaturation at 95 °C for 10 s, annealing at 60 °C for 20 s and extension at 72 °C for 20 s. The transcript levels of β-actin were used as internal controls. Relative mRNA expression was calculated using the 2^−ΔΔCt^ method. All the specific primers used are listed in Table S3.
Subcellular nuclear fractionation
Fractionation of nuclear extracts was performed according to the instructions of the Nuclear Protein Extraction Kit (Solarbio, Beijing, China) provided by the manufacturer.
Western blotting (WB)
Cells were harvested and total protein lysates were prepared and then quantified using a BCA protein assay kit (Vazyme, Nanjing, China). Equal amounts of the proteins were resolved on SDS polyacrylamide gels for separation and transferred onto PVDF membranes (Millipore, Billerica, USA). After blocking with 5% BSA, the membranes were incubated with primary antibodies at 4 °C overnight, followed by incubation with the corresponding secondary antibodies at room temperature for 1 h. The target proteins were detected by ECL reagent (Thermo Fisher Scientific, Rochester, USA) and visualised with a ChemiDoc™ XRS+ Imaging System (Bio-Rad, Hercules, USA). All antibody information is listed in Table S2.
Enzyme-linked immunosorbent assay (ELISA)
The concentrations of VEGFC, VEGFD and TGF-β were assessed using ELISA kits (all from FineTest, Wuhan, China) according to the kit instructions. Briefly, cell supernatants were diluted and then added to wells coated with specific antibodies. After the samples were incubated with enzyme-labelled antibodies at 37 °C for 60 min and chromogen solution at 37 °C for 15 min, the reaction was stopped and the absorbance of each well at 450 nm was measured. Marker concentrations in the samples were then calculated on the basis of the standard curve drawn using standard samples.
Glucose uptake assay
Glucose uptake was assessed by quantifying glucose utilisation following the manufacturer’s protocol (Jiancheng, Nanjing, China). Prior to the assessments, metabolic parameters were standardised on the basis of the protein concentration.
Immunofluorescence analysis (IF)
Formalin-fixed paraffin-embedded sections were first dewaxed in dimethylbenzene and then hydrated in ethanol along a concentration gradient. Antigen retrieval was performed in EDTA buffer under high pressure. Cultured cells in plates were fixed with 4% PFA at room temperature. The sections or cells were blocked with 5% BSA and incubated with primary antibodies overnight at 4 °C and then with secondary antibodies for 1 h. The primary antibodies, secondary antibodies and their catalogue numbers are listed in Table S2. Finally, images were obtained via a Zeiss LSM 800 confocal microscope system.
HLEC tube formation assay
CM was collected from 24-h cancer cell cultures and concentrated 10-fold using ultrafiltration spin columns (Millipore, Billerica, USA). HLECs were then seeded into 96-well plates (precoated with Matrigel) that contained concentrated media and incubated for 8 h. Lymphatic tubular networks were visualised via inverted microscopy and quantitatively analysed using ImageJ for morphometric measurements of tubule length.
HLEC transwell assay
The migratory capacity of HLECs was assessed using Transwell chambers (Jet, Guangzhou, China). Following 24 h of serum starvation, the cells were seeded in serum-free medium into the upper compartment. The bottom wells were filled with complete medium as a chemoattractant. After 48 h of incubation, the migrated cells that had adhered to the lower membrane were fixed and stained with crystal violet. The migrated cells from random fields were chosen and then counted using a computer-based microscopy imaging system.
Bioinformatic analysis
The prognostic relevance of CD163 in TNBC was determined through integrated analyses of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets via the bc-GenExMiner v5.1 platform. Intermarker or M2 macrophage-marker correlations were systematically assessed using the TIMER 2.0 website.
Quantification and statistical analysis
All the statistical analyses were conducted using GraphPad Prism version 10.1.2 (La Jolla, USA). Continuous variables were compared using two-tailed unpaired Student’s t tests (parametric) or Mann–Whitney U tests (nonparametric). The data is presented as mean ± SD. Survival differences in Kaplan–Meier curves (disease-free survival [DFS] and overall survival [OS]) were analysed by the log-rank test. Statistical significance was defined as p < 0.05 for all two-tailed analyses.
Supplementary information
Supplementary Material Original data Original data Pathways enrichment
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