Prussian blue analogue-mineralized ginseng-derived vesicles promote PPARγ nuclear translocation to suppress tumor vasculogenic mimicry and reverse the immunosuppressive microenvironment

Abstract

Highly aggressive tumor cells fulfill their metabolic demands by forming vascular-like channels through a process of cellular deformation and extracellular matrix (ECM) remodeling, known as vasculogenic mimicry (VM). This phenomenon contributes to the limited efficacy of anti-angiogenic therapies and promotes tumor progression, making VM inhibition a promising yet challenging therapeutic strategy. To address this, we developed a biomimetic nanoplatform, termed GDVs@CuPBA-iRGD, through the in-situ mineralization of a copper-based Prussian blue analogue (CuPBA) onto ginseng-derived vesicles (GDVs), followed by conjugation with the tumor-penetrating peptide iRGD. The resulting nanocomposite exhibited excellent pH-responsive degradation, enabling controlled drug release within the tumor microenvironment. In vitro, GDVs@CuPBA-iRGD was efficiently internalized by hepatocellular carcinoma (HCC) cells, significantly suppressing their viability, invasion, and VM formation while simultaneously inducing cuproptosis and ferroptosis. Consistent with these findings, in vivo studies confirmed that GDVs@CuPBA-iRGD exhibits superior accumulation in the liver, resulting in potent inhibition of both VM and tumor progression, all while maintaining high biosafety. Mechanistically, the anti-VM effect is primarily mediated by the nuclear translocation of PPARγ. This key event triggers a transcriptional reprogramming that downregulates critical VM-associated genes, thereby disrupting the ECM remodeling essential for VM. Moreover, single-cell RNA sequencing (scRNA-seq) analysis indicated that VM suppression by GDVs@CuPBA-iRGD triggered the subsequent activation of antitumor immunity. This work highlights a novel bioinspired and synergistic therapeutic strategy for the precise treatment of VM-dependent aggressive tumors.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-026-04263-y.

Introduction

Hepatocellular carcinoma (HCC) is the most common pathological type of primary liver cancer and the third leading cause of cancer-related death worldwide [1]. HCC has the characteristics of insidious occurrence, rapid development, and easy metastasis [2, 3]. Tumor vasculature has a profound impact on tumor growth and metastasis [4]. The abnormal structure and function of tumor blood vessels pose an important threat to the treatment of tumors [5]. At present, targeted drugs designed based on traditional tumor angiogenesis pathways have been put into clinical use, but the effect is not satisfactory [6, 7]. This may be due to the activation of other angiogenesis-related processes, such as vasculogenic mimicry (VM). VM is a recently discovered angiogenic process that appears in many malignancies and unlike conventional angiogenic processes involving the vascular endothelium, it involves the formation of microvascular channels composed of tumor cells [8–10]. Therefore, VM is considered as a new model of neovascularization in aggressive tumors that can provide a blood supply for tumor growth [9]. VM is implicated in the malignant behaviors of proliferation and invasion across various tumors, including HCC [11], laryngeal carcinoma (LC) [12], and uveal melanoma (UM) [13], and fosters an immunosuppressive tumor microenvironment (TME) [8]. VM mediates the effects of chemotherapy, radiotherapy and immunotherapy through complex mechanisms, and is closely related to the poor prognosis of cancer patients [14, 15].

The advancement of nanotechnology offers promising new strategies to overcome challenges in cancer treatment, particularly for addressing drug resistance in specific phenotypes such as VM [11]. Among various nanomaterials, Prussian blue analogue nanoparticles (PBA NPs) have garnered significant attention due to their excellent stability, pH-responsive drug release, and remarkable biocompatibility, rendering them highly promising for oncological applications [16, 17]. Moreover, the enzyme-mimicking catalytic properties of PBA NPs, such as their peroxidase-like activity, can be leveraged to trigger potent, catalytic-induced death of tumor cells [18]. These multifaceted capabilities allow PBA NPs to function not merely as passive drug carriers, but as active participants in anti-tumor processes-such as disrupting VM channels and inhibiting matrix metalloproteinases-thereby presenting considerable potential for targeted cancer therapy.

Peroxisome proliferator-activated receptor γ (PPARγ), a ligand-activated transcription factor, exerts its effects by forming a heterodimer with the retinoid X receptor (RXR) upon binding endogenous or synthetic ligands [19]. This activated PPARγ/RXR complex translocates to the nucleus and binds to specific DNA sequences known as PPAR response elements (PPREs) in the promoter regions of target genes [19, 20]. This binding regulates the transcription of genes involved in critical processes such as insulin sensitization, lipid metabolism, and cell proliferation and differentiation [21]. Due to these central roles, PPARγ is a well-established therapeutic target for metabolic diseases. For instance, thiazolidinediones (TZDs), a class of PPARγ agonists, are clinically used to treat type 2 diabetes by improving insulin sensitivity and modulating adipocyte function [22]. Besides, PPARγ plays a complex role in cancer development and progression [23, 24]. Its effect on tumors remains controversial, and the specific role of PPARγ in VM formation remains unclear.

In this study, we meticulously designed Prussian blue analogue-biomineralized ginseng-derived vesicles (GDVs@CuPBA-iRGD) to inhibit VM formation and delay the malignant progression of HCC. The nanoplatform was constructed by isolating GDVs and subjecting them to biomineralization with a copper-based Prussian blue analogue (CuPBA), followed by surface functionalization with the iRGD tumor-penetrating peptide. This rational design conferred excellent tumor-targeting ability and potent VM-inhibiting capability. After being efficiently taken up by HCC cells, the nano-shell responsively degraded under acidic conditions, leading to its dissociation and the release of GDVs. This process triggered strong inhibition of HCC cell viability, migration, and VM formation along with inducing multiple cell death pathways, effectively impeding HCC progression. In vivo, GDVs@CuPBA-iRGD specifically accumulated in the liver and exerted powerful therapeutic effects while demonstrating excellent histocompatibility and safety. Mechanistic investigation elucidated that GDVs@CuPBA-iRGD promotes the translocation of PPARγ to the nucleus. Following nuclear entry, PPARγ interacts with numerous pro-VM genes, suppressing the expression of MMP9, PTGS2, ICAM1, and other related genes, thereby inhibiting tumor VM formation. By fusing natural vesicles with biomimetic nanomaterials, this design presents a promising therapeutic paradigm against aggressive tumors through targeted inhibition of VM.

Materials and methods

Cell culture

Cells were purchased from KeyGen Biotech. Hep3B, MHCC97H, and Hepa1-6 cells were cultured in Dulbecco’s modified eagle medium (DMEM) containing 10% fetal bovine serum, and 100U/ml penicillin/streptomycin. All the cells were cultured in 5% CO2 at 37℃.

Isolation and characterization of GDVs

Fresh ginseng was thoroughly washed with phosphate-buffered saline (PBS) and homogenized. The crude homogenate was sequentially subjected to a series of differential centrifugations to isolate GDVs. Briefly, the homogenate was first centrifuged at 3,000 g for 30 min at 4 °C to remove large debris. The resulting supernatant was then centrifuged at 10,000 g for 1 h at 4 °C. The final supernatant was ultracentrifuged at 150,000 g for 90 min at 4 °C to collect the GDVs. The obtained GDVs were resuspended in an appropriate volume of sterile, pre-cooled PBS. GDVs electron microscopy was performed with a cryo-TEM system (Talos F200C, Czechia) to obtain morphology information. The particle size and zeta potential of GDVs were measured by zeta sizer Nano ZS90 (Malvern Instruments). GDVs were quantified using the BCA Protein Assay kit and stored at -80 °C until further use.

Synthesis of GDVs@CuPBA-iRGD

The GDVs@CuPBA-iRGD was synthesized via an in-situ mineralization method. Typically, a purified GDVs suspension was dispersed in 200 μL HEPES buffer (pH 7.4). An aqueous solution of copper chloride (CuCl₂, 1 mM) was then added to the GDVs suspension under gentle stirring, and the mixture was incubated for 30 min at room temperature. Subsequently, an aqueous solution of potassium ferrocyanide (K₄[Fe(CN)₆],0.4 mM) was added dropwise into the mixture. The reaction was allowed to proceed for 2 h under continuous gentle stirring. Following this, the iRGD targeting peptide was added to the solution and incubated for 2 h. The resulting product was centrifuged at 12,000 g for 30 min and washed twice with ultrapure water. Finally, the product was stored at 4 °C for further use.

Western blotting

Proteins were extracted with RIPA lysis buffer, and the concentration of proteins was determined using the BCA kit (Thermo Scientific, USA). Proteins were separated on SDS–polyacrylamide gels and then transferred to PVDF membranes. After blocking with 5% skim milk, the primary antibodies used for western blot analysis were as follows: VE-cadherin (# HA721943, HUABIO, China), Fibronectin (A12932, ABclonal, China), MMP2 (#ET1606-4, HUABIO, China), MMP9 (10,375–2-AP, Proteintech, China), LIAS (#DF14836, Affinity, USA), GPX4 (sc166570, Santa Cruz Biotechnology, USA), PPARγ (#AF6284, Affinity, USA), Lamin B1 (sc377000, Santa Cruz Biotechnology, USA), RTGS2 (#ET1610-23, HUABIO, China), ICAM1 (10,831–1-AP, Proteintech, China), EGFR (#ET1604-44, HUABIO, China), and GAPDH (#AF7021, Affinity, USA) at 4 °C overnight. After incubating with horseradish peroxidase-conjugated secondary antibody at room temperature for 1 h, detection was performed using an enhanced chemiluminescence kit ((Millipore, MA, USA).

Tube formation assay

Briefly, Matrix (#354,262, Corning, USA) and serum-free medium were mixed in a 1:2 ratio and transferred to 24-well plates. The plate was then placed at 37 °C for 2 h until Matrigel solidified. The cells were resuspended in serum-containing medium and seeded on the surface of Matrigel at a density of 3 × 10⁵ cells /mL. incubated in at 37 °C incubator for 1 h. Live cell dynamic imaging under a fluorescent microscope Qi2 (Nikon). The images were digitized with ImageJ and the AngiogenesisAnalyzer.ijm and AutoMeasure. ijm scripts were employed to analyze the time series images of the VM.

Migration and invasion assays

Transwell migration and invasion assays were performed using a transwell plate (Corning, USA) coated with or without Matrigel (Corning, USA). 200 μL of serum-free medium (1 × 10⁵ cells) was added to the upper chamber and 500 μL of medium containing 10% FBS was added to the lower chamber. Cells were incubated at 37 °C for 24 h. The cells were fixed with 4% paraformaldehyde for 20 min, stained with crystal violet for 15 min, rinsed with PBS and dried, and finally photographed under a microscope.

Gelatin degradation assay

Porcine skin gelatin (#G13187, Thermo Fisher, USA) was diluted with 2% sucrose in PBS to a final gelatin concentration of 0.2 mg/mL. The working solution was protected from light, and heated to 60 °C to evenly cover the slides. After drying,1 mL of pre-cooled glutaraldehyde solution was added and incubated on ice for 15 min. A total of 1 mL of freshly prepared sodium borohydride solution was then added, and the solution was incubated at room temperature for 3 min. After inoculating the cells and culturing them for 24 h, the cells were fixed and stained with F-Actin using SF647 Phalloidin (#CA1760, Solarbio, China). Finally, the slides were mounted with DAPI and observed and analyzed using a laser confocal microscope.

Real-time quantitative reverse transcription PCR

Total RNA was extracted using a MolPure Cell RNA kit (Yeasen, China). and then RNA reverse-transcribed into cDNA using Hifair III 1st Strand cDNA Synthesis SuperMix (Yeasen, China). qRT-PCR was conducted with the SYBR Green detection reagent on the LightCycler® 96 real-time PCR system (Bio-Rad, USA). The 2-^ΔΔCt method was used to quantify relative gene expression compared to GAPDH as an internal control. qRT-PCR primers are listed in the Table S1.

EMCN-PAS staining

Endomucin (EMCN) staining and PAS immunohistochemical staining were used to evaluate the presence and extent of VM in tumors. Briefly, the tissue sections were first stained with EMCN (sc-65495, Santa Cruz Biotechnology, USA) immunohistochemical staining, treated with sodium periodate for 10 min, washed with distilled water for 5 min. All sections were counterstained with hematoxylin by incubation with PAS (#G1281, Solarbio, China), dehydrated and mounted. VM is characterised by tumorlined luminal structures. EMCN was negative and PAS was positive. Endothelial cells were positive for microvascular markers EMCN and PAS.

Animal experiment

Six-week-old male C57BL/6 mice were obtained from Beijing Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). For the bio-distribution assay of GDVs@CuPBA-iRGD, GDVs@CuPBA-iRGD were incubated with DiR (Selleck, USA) at room temperature for 20 min according to the instructions provided by the trial manufacturer. The supernatant was removed by centrifugation at 10,000 g for 10 min, and the DiR-GDVs@CuPBA-iRGD precipitate was resuspended in PBS. Mice were given 20 mg/kg DiR-GDVs@CuPBA-iRGD by intraperitoneal injection and tail vein injection, respectively. The main organs of mice were dissected at the corresponding time points and the distribution of DiR-GDVs@CuPBA-iRGD in vivo was detected using an in vivo animal imaging system (PerkinElmer, USA).

To evaluate the in vivo antitumor effect, the mouse model of HCC was established according to the previous method in our laboratory [25], and the tumor growth of mice was detected by in vivo imaging system. Mice were randomly divided into four groups, administration was performed via tail vein injection every 2 days. Mice were monitored for changes in their status, body weight, and survival rate throughout the experiments. Mice were sacrificed after six doses, and major organs and blood samples were obtained for subsequent analysis.

Immunohistochemistry (IHC) staining

The Paraffin-embedded tumor tissue was cut into 4 μm sections, antigen repair was performed with citrate buffer antigen repair solution, blocked with goat serum, and the sections were incubated with primary antibodies at 4 °C overnight. After incubation with secondary antibodies, the sections were stained with DAB and hematoxylin staining solution, sealed with neutral glue, dried, photographed under a microscope to obtain images, and were performed for IHC scoring.

H&E staining

Tissue sections were deparaffinized, hydrated, and stained with hematoxylin and eosin at room temperature. After staining, sections were dehydrated, transparent, and finally sealed with neutral resin. The images were acquired under a microscope.

Immunofluorescence (IF) staining

Cells were fixed with 4% paraformaldehyde, followed by blocking and permeabilizing with 5% BSA and 0.05% Triton X-100, and cells were incubated with primary antibodies overnight at 4 °C. The cells were incubated with fluorescein-labeled secondary antibodies for 1 h at room temperature, the nuclei were stained with DAPI (Beyotime, China), and finally the samples were imaged using a Zeiss LSM800 laser confocal microscope.

RNA sequencing

HCC cells were seeded in 6-well plates and divided into two groups: the Ctrl group and the GDVs@CuPBA-iRGD-treated group. After treatment, cells from both groups were collected, washed twice with PBS to remove residual medium and cytokines, and then lysed for total RNA extraction using TRIzol reagent. The purified RNA was subsequently submitted to Tsingke Biotechnology Co., Ltd. for RNA sequencing analysis. Differentially expressed genes (DEGs) were identified based on the thresholds of adjusted P < 0.05 and log2 fold change > 1.

Statistical analysis

All the data results were expressed as mean ± SD, Differences between groups were assessed via unpaired two-tailed t tests (for simple two-sample comparison) or one-way analysis of variance (ANOVA) with Dunnett’s test (for multiple comparisons). Significance criteria were set as P < 0.05, ns indicates no significance.

Results

Physicochemical characterization of GDVs@CuPBA-iRGD

According to the previously described experimental protocol, ginseng-derived vesicles (GDVs) were isolated from fresh ginseng. Transmission electron microscopy (TEM) imaging showed that the GDVs exhibited a near-spherical vesicular structure (Fig. 1A). Furthermore, dynamic light scattering (DLS) analysis revealed that the average particle size of GDVs was approximately 159.7 nm and exhibited a very uniform particle size distribution (Fig. 1B). Zeta potential analysis measured a value of -15.6 mV for the GDVs (Fig. S1, Supporting Information). Subsequent liquid chromatography-mass spectrometry (LC–MS) analysis detected over 600 metabolites in GDVs, including carboxylic acids and derivatives (17.11%), prenol lipids (9.17%), organooxygen compounds (8.91%), and various ketones, acids and terpenoids (Fig. 1C). These metabolites are involved in cellular biofunctions such as energy generation, cell migration, and regulation of cellular plasticity, which may play pivotal roles in inhibiting tumor vasculogenic mimicry (VM). To enhance their native functionality and stability, the GDVs were mineralized with a copper-based Prussian blue analogue (CuPBA) layer and further loaded with the tumor-penetrating iRGD peptide, resulting in the formation of nanoparticles designated as GDVs@CuPBA-iRGD. As shown in Fig. 1D, GDVs@CuPBA-iRGD exhibited a distinct core–shell structure, and the diameter increased to approximately 196 nm after mineralization (Fig. 1E). with a zeta potential of -10.4 mV (Fig. 1F). In addition, CuPBA nanoparticles were synthesized as a control using a protocol similar to that for GDVs@CuPBA-iRGD (without GDVs). The CuPBA control nanoparticles exhibited a spherical morphology with a coarse surface (Fig. S2, Supporting Information). Moreover, as shown in Fig. 1G, SDS-PAGE results indicated that the mineralization process did not alter the protein composition of the GDVs, as evidenced by the nearly identical band patterns. Elemental mapping analysis revealed well-overlapped distributions of the O, N, and P signals with those of Cu and Fe (Fig. 1H). Concurrently, energy-dispersive X-ray spectroscopy (EDS) results confirmed the coexistence of O, N, P, Cu, and Fe elements in the composite (Fig. 1I), collectively demonstrating the successful encapsulation of the GDVs within the CuPBA nanoshell. Additionally, we investigated the pH-responsive degradation behavior of the GDVs@CuPBA-iRGD was evaluated in PBS at different pH (7.4 and 5.5). As shown in Fig. 1J, the degradation rate of GDVs@CuPBA-iRGD at pH 5.5 was markedly faster than that at pH 7.4. Taken together, these results demonstrate that GDVs@CuPBA-iRGD exhibits excellent structural integrity and pH responsiveness, thus laying a solid foundation for its subsequent application in antitumor therapy.

Fig. 1.

Preparation and characterization of the GDVs@CuPBA-iRGD. (A) TEM image of GDVs. (B) Size distribution analysis of GDVs. (C) The top 12 metabolites observed in GDVs. (D) TEM image of GDVs@CuPBA-iRGD. (E) Hydrodynamic sizes of GDVs, GDVs@CuPBA, and GDVs@CuPBA-iRGD measured by DLS. (F) Zeta potentials of GDVs, GDVs@CuPBA, and GDVs@CuPBA-iRGD. (G) Protein composition of GDVs, and GDVs@CuPBA-iRGD were separated by SDS-PAGE. (H) Elemental mapping analysis of GDVs@CuPBA-iRGD. Scale bar: 150 nm. (I) EDS analysis of GDVs@CuPBA-iRGD. (J) Cumulative Cu²⁺ release profiles of GDVs@CuPBA-iRGD in PBS solutions at different pH levels

GDVs@CuPBA-iRGD inhibits the formation of VM

Previous studies have shown that the uptake and internalization of nanomedicines by cells is a key factor affecting their efficacy [26]. Since GDVs lacked fluorescence but possessed lipophilic properties, they could bind to lipophilic dye (DiO). Therefore, we labeled GDVs with DiO, and incubate the DiO-GDVs with HCC cells. The results showed that as the incubation time increased, the green fluorescence signal in HCC cells gradually increased, and the uptake of GDVs was mainly distributed in the cell membrane and cytoplasm. Subsequently, significantly stronger fluorescence was observed in HCC cells incubated with DiO- GDVs@CuPBA-iRGD, which was primarily localized in the cytoplasm and nuclear. Concurrently, the cellular morphology of HCC cells underwent notable changes, characterized by loss of plasma membrane integrity and blurring of nuclear structure, indicating that the decoration of the iRGD peptide on the GDVs@CuPBA surface was beneficial for enhancing tumor-specific targeting and endocytosis (Fig. 2A). Subsequently, we recorded the VM formation process by live cell imaging, and counted the VM related data, including the number of junctions, tubes, nodes, and the total length, using our established VM evaluation method [27]. The results demonstrated that GDVs@CuPBA-iRGD inhibited VM formation more effectively than either GDVs or GDVs@CuPBA (Fig. 2B). Specifically, GDVs@CuPBA-iRGD significantly reduced the number of VM tubes, nodes, and total length of VM formed by MHCC97H cells on Matrigel. (Fig. 2C). We were inclined to shed light on whether GDVs@CuPBA-iRGD could regulate the expression levels of VM-related proteins. VE-cadherin and Fibronectin are widely recognized as markers of VM [9], while MMP2 and MMP9 are key enzymes known to degrade various protein substrates in the extracellular matrix (ECM), such as collagen and elastin, playing crucial roles in VM formation. It was shown that the expression levels of VM-related markers including VE-cadherin, Fibronectin, MMP2, and MMP9 were significantly decreased after GDVs@CuPBA-iRGD treatment (Fig. 2D). Further experiments showed that GDVs@CuPBA-iRGD significantly inhibited the migration and invasion abilities of HCC cells (Fig. S3A, B, Supporting Information). Given that VM represents a manifestation of tumor cell evolution and the epithelial-mesenchymal transition (EMT) [28], we sought to validate whether GDVs@CuPBA-iRGD could inhibit the migratory potential of HCC cells. To this end, we performed a fluorescent gelatin degradation assay. As shown in Figs. 2E, F, our results clearly showed that GDVs@CuPBA-iRGD significantly suppressed the gelatin degradation capability of HCC cells. Taken together, GDVs@CuPBA-iRGD exhibits a potent capacity to suppress VM.

Fig. 2.

GDVs@CuPBA-iRGD inhibits the formation of tumor VM. (A) Images and fluorescence distribution curves of GDVs, GDVs@CuPBA, and GDVs@CuPBA-iRGD uptake by HCC cells at different times. (B, C) Representative images of VM status of HCC cells treated with CuPBA, GDVs, GDVs@CuPBA, and GDVs@CuPBA-iRGD for 2, 4, 8, and 16 h and quantitative plots of the four measured parameters (tubes, junctions, nodes, and total length). (D) The levels of VM-related proteins were detected by Western blot in Hep3B and MHCC97H cells with Matrigel 3D culture treated as indicated. (E, F) Fluorescent gelatin degradation of HCC cells treated as indicated and quantification of degradation area. G1: Ctrl, G2: CuPBA, G3: GDVs, G4: GDVs@CuPBA, G5: GDVs@CuPBA-iRGD. Data were presented as mean ± SD (n = 3), ns indicates no significance

Therapeutic mechanisms of GDVs@CuPBA-iRGD on VM

To further understand the molecular mechanism by which GDVs@CuPBA-iRGD affected VM formation in HCC cells, we performed RNA sequencing (RNA-seq) on GDVs@CuPBA-iRGD-treated HCC cells (Fig. 3A). Principal Component Analysis (PCA) demonstrated significant differences in genes between different groups as well as replication reproducibility within groups (Fig. 3B). We found that 608 genes were significantly up-regulated and 880 genes were significantly down-regulated after GDVs@CuPBA-iRGD treatment compared with the Ctrl (Fig. 3C). In accordance with the obtained sequencing results, we conducted gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses as well. Based on GO analysis, the results highlighted cell adhesion, angiogenesis, extracellular matrix, cell junction, and other biological processes related to VM formation and migration (Fig. 3D). The KEGG pathways were enriched for cellular processes and signaling pathways related to VM, including focal adhesion, ferroptosis, ECM-receptor interaction, PI3K-AKT signaling pathway, and PPAR signaling pathway (Fig. 3E). Among these enriched GO terms, extracellular space attracted particular attention. Further heatmap analysis of the differentially expressed genes related to the extracellular space demonstrated that in GDVs@CuPBA-iRGD-treated cells, a multitude of genes that promote VM formation were significantly downregulated, while those that inhibit VM were upregulated (Fig. 3F). For instance, we observed a notable upregulation of TIMP1, a classic endogenous inhibitor of matrix metalloproteinases (MMPs), which can impede ECM degradation, a crucial step for VM formation. Conversely, the expression of FN1 (Fibronectin 1), a well-established marker that facilitates VM, was markedly suppressed (Fig. 3G). Collectively, these results demonstrate that GDVs@CuPBA-iRGD exhibits a potent capacity to suppress VM formation at the cellular level. Additionally, we observed alterations in genes associated with cuproptosis and ferroptosis (Fig. 3H). For example, the cuproptosis-related gene FDX1 reduces Cu.²⁺ to the more toxic Cu⁺, leading to the inhibition of Fe-S cluster protein synthesis and thereby inducing cell death. We also noted the downregulation of glutathione peroxidase 4 (GPX4), a key suppressor of ferroptosis. These changes suggest that GDVs@CuPBA-iRGD may trigger multiple forms of cell death. As shown in Fig. 3I, the cuproptosis-related protein LIAS and the characteristic anti-ferroptosis protein GPX4 were both significantly suppressed. Similarly, Immunofluorescence staining confirmed a marked decrease in LIAS expression (Fig. 3J). This effect is likely attributable to the responsive release properties of GDVs@CuPBA-iRGD, which result in the localized release of copper and iron ions within tumors, thereby inducing simultaneous activation of multiple cell death pathways. Notably, even at a sublethal concentration that does not compromise cell viability (Fig. S4A, Supporting Information), GDVs@CuPBA-iRGD still potently suppressed VM formation (Fig. S4B, C, Supporting Information), confirming that this inhibition is a specific effect independent of cytotoxicity. Taken together, these data indicate that GDVs@CuPBA-iRGD suppresses VM formation by altering VM-related biological processes and signaling pathways, while the gradual accumulation of released copper and iron ions induces the activation of multiple cell death pathways. Acting cooperatively, these two mechanisms lead to an enhanced antitumor efficacy.

Fig. 3.

RNA sequencing to explore biological mechanisms of GDVs@CuPBA-iRGD. (A) Schematic illustration of RNA-seq and subsequent bioinformaticsanalysis. (B) PCA analysis of the Ctrl and GDVs@CuPBA-iRGD groups. (C) Volcano plot displaying the differentially expressed genes. (D, E) Differentiallyexpressed genes were analyzed using GO and KEGG databases to explore the main functions and signaling pathways affected by GDVs@CuPBA-iRGD.(F) Heatmap of genes with extracellular space in GO analysis. (G) Gene expression levels of TIMP1, MMP11, and FN1 in different groups of treatments. (H)Expression levels of FDX1 and GPX4. (I) Protein expression levels of LIAS and GPX4. (J) Representative Immunofluorescence images for LIAS (green)/DAPI(blue) in the HCC cells. Data were presented as mean ± SD (n = 3)

GDVs@CuPBA-iRGD suppressed VM formation by enhancing linoleic acid metabolism to promote PPARγ nuclear translocation

Based on the premise that lipid metabolites contained within GDVs may alter the lipid metabolism of HCC cells, and considering that the cell death pathways involved are associated with lipid peroxidation-both factors suggesting potential lipid metabolic reprogramming-untargeted metabolomics was employed to profile the metabolic alterations in response to GDVs@CuPBA-iRGD treatment. Volcano plot analysis revealed 271 significantly upregulated and 64 downregulated metabolites in the treatment group compared to the Ctrl group. (Fig. 4A). KEGG pathway enrichment analysis of these differential metabolites indicated that GDVs@CuPBA-iRGD primarily impacted linoleic acid metabolism and biosynthesis of unsaturated fatty acids (Fig. 4B). We next performed a cluster analysis via heatmap focusing on linoleic acid and its derivatives, including linoleic acid, oleic acid, heptadecanoic acid, pentadecanoic acid, and the linoleic acid derivative 9R,10S-EPOME. These metabolites were significantly elevated in the GDVs@CuPBA-iRGD-treated group (Fig. 4C-E). The coordinated upregulation of these metabolites may reveal a key mechanism, as linoleic acid and its derivatives are known to act as endogenous activators of Peroxisome Proliferator-Activated Receptor γ (PPARγ)-a transcription factor closely associated with tumor EMT and VM [28, 29]. PPARγ is a type of ligand-activated transcription factor belonging to the nuclear receptor superfamily. PPARγ regulates gene transcription and is widely involved in processes such as lipid metabolism, inflammatory response, and tumor cell differentiation [30, 31].

Fig. 4.

GDVs@CuPBA-iRGD enhance linoleic acid metabolism to promote PPARγ nuclear translocation. (A) The volcano plot for different metabolites between Ctrl and GDVs@CuPBA-iRGD groups. (B) Enrichment analysis of the top 25 metabolic pathways based on significantly differential metabolites. (C) Hierarchical clustering heatmap of metabolites of Ctrl and GDVs@CuPBA-iRGD groups. (D) Quantitation for relative abundance of linoleic acid and its derivatives. (E) Network diagram between various differential metabolites and metabolic pathways, with yellow points representing pathways and other points representing metabolites. (F) A luciferase reporter assay was conducted to measure the transcriptional activity of PPARγ. (G) Immunofluorescence staining was performed to assess the subcellular localization of PPARγ in HCC cells. (H) Western blot analysis was performed to determine the changes in the expression levels of nuclear PPARγ and cytoplasmic VE-cadherin and Fibronectin. G1: Ctrl, G2: GDVs@CuPBA-iRGD, G3: GDVs@CuPBA-iRGD + GW9662. Data were presented as mean ± SD (n = 3)

To verify whether GDVs@CuPBA-iRGD activate the PPARγ signaling pathway, a PPARγ luciferase reporter assay was performed. The results showed that GDVs@CuPBA-iRGD treatment significantly enhanced its transcriptional activity, an effect that was substantially reversed by the PPARγ specific antagonist GW9662 (Fig. 4F). Similarly, Immunofluorescence staining confirmed that GDVs@CuPBA-iRGD promoted the nuclear translocation of PPARγ, however, this effect was significantly attenuated by the addition of GW9662 (Fig. 4G). These findings demonstrate that GDVs@CuPBA-iRGD effectively enhance PPARγ transcriptional activity. Next, to determine whether the anti-VM effect of GDVs@CuPBA-iRGD was mediated through the PPARγ pathway, we assessed the relationship between the subcellular distribution of PPARγ and the expression levels of VE-cadherin and Fibronectin by Western blot. As shown in Fig. 4H, GDVs@CuPBA-iRGD treatment significantly increased nuclear PPARγ levels while suppressing the expression of VE-cadherin and Fibronectin in HCC cells. As expected, the addition of GW9662 led to a significant reversed in the expression of VE-cadherin and Fibronectin. This observation was further corroborated by the VM formation process and the gelatin degradation assay. In both assays, the inhibitory effect of GDVs@CuPBA-iRGD on VM was significantly weakened by the addition of GW9662 (Fig. 5A-D). As a nuclear receptor, PPARγ exerts its function by regulating target gene transcription. Based on TRRUST database analysis revealed that MMP9, PTGS2, ICAM1, and EGFR are direct transcriptional targets of PPARγ (Fig. 5E), all of which are closely associated with the VM process. qPCR and Western blot results consistently demonstrated that GDVs@CuPBA-iRGD significantly suppressed the expression of these genes, whereas the addition of GW9662 markedly restored their expression levels (Fig. 5F-G). In summary, our results highlight the critical role of PPARγ in the suppression of VM by GDVs@CuPBA-iRGD, which acts through its nuclear translocation to inhibit key transcriptional regulators of VM.

Fig. 5.

PPARγ suppresses key transcriptional regulators of VM. (A, B) Representative plots of VM status of HCC cells at 2, 4, 8, and 16 h and quantitative plots of the four measured parameters. (C, D) Fluorescent gelatin degradation of HCC cells treated as indicated and quantification of degradation area. (E) PPARγ target genes from the TRRUST database. (F, G) qPCR and Western blot analyses were performed on HCC cells under the indicated treatments to detect alterations in the expression of MMP9, PTGS2, ICAM1, and EGFR. (H) Schematic diagram. G1: Ctrl, G2: GDVs@CuPBA-iRGD, G3: GDVs@CuPBA-iRGD + GW9662. Data were presented as mean ± SD (n = 3)

GDVs@CuPBA-iRGD suppress tumor progression by inhibiting VM formation

In the clinical treatment of cancer, intravenous (i.v.) injection is a widely used route of drug administration, which has the characteristics of rapid onset of action, but it is more traumatic. Oral administration is the most economical and convenient route of drug administration, but it takes effect slowly, and some drug effects will be destroyed by gastric acid. Intraperitoneal (i.p.) injection is in between and is by far the most commonly used mode of administration [32]. Here we mainly investigated the distribution of GDVs@CuPBA-iRGD in vivo after i.p. and i.v. injection of DiR-labeled GDVs@CuPBA-iRGD. We found that GDVs@CuPBA-iRGD accumulated in major organs regardless of the mode of administration approaches, and the fluorescence intensity reached its maximum at the time points of 8 h (i.v.) and 12 h (i.p.) (Fig. 6A, B; Fig. S5A, B, Supporting Information). To evaluate the antitumor effect of GDVs@CuPBA-iRGD in vivo, we established an orthotopic liver cancer mouse model (Fig. 6C). We found that, compared to the Ctrl group, both GDVs and GDVs@CuPBA slowed tumor growth, exhibiting partial inhibitory effects, while GDVs@CuPBA-iRGD demonstrated a more pronounced therapeutic efficacy. This was reflected by the lower tumor luciferase intensity and flatter tumor growth curves (Fig. 6D, E). Notably, GDVs@CuPBA-iRGD also significantly extended the survival of the mice (Fig. 6F), and there was no significant difference in the body weight of the mice throughout the treatment period (Fig. 6G). In mice, endomucin (EMCN) is an endothelial antigen predominantly localized to the venous and capillary endothelium. EMCN-PAS staining allows for quantitative and morphological assessment of VM in mouse tumor tissues, serving as the standard methodology for VM evaluation [33]. Subsequently, we performed EMCN-PAS double staining of tumor tissue from C57BL/6 mice. Notably, GDVs, GDVs@CuPBA, and GDVs@CuPBA-iRGD all significantly reduced the number of VM, with GDVs@CuPBA-iRGD demonstrating superior suppression (Fig. 6H, I). Consistently, Immunohistochemistry (IHC) staining of VM-associated proteins in tumor tissues showed that GDVs@CuPBA-iRGD more potently downregulated their expression (Fig. 6J, K). These results revealed that GDVs@CuPBA-iRGD exerted enhanced antitumor effects by inhibiting VM formation.

Fig. 6.

Antitumor effects of GDVs@CuPBA-iRGD in vivo. (A, B) Fluorescence images of liver, lung, spleen, heart, kidney, and small intestine at different times were obtained by i.v. injection of DiR- GDVs@CuPBA-iRGD and quantitative analysis. (C) Schematic diagram of the establishment process and treatment plan of orthotopic liver cancer mouse model. (D, E) Bioluminescence imaging and quantification of Hepa1-6-luc-tumor-bearing C57BL/6 mice in different treatment groups. (F) Survival curves of C57BL/6 mice after treated with PBS, GDVs, GDVs@CuPBA, and GDVs@CuPBA-iRGD. (G) Body weight changes in C57BL/6 mice treated with PBS, GDVs, GDVs@CuPBA, and GDVs@CuPBA-iRGD. (H, I) Representative images and quantitative analysis of EMCN-PAS double staining in mice liver tumor tissues, VM is indicated by the red arrow (EMCN⁻PAS⁺). (J, K) IHC staining of VE-cadherin, Fibronectin, MMP2, and MMP9 in liver tumor tissues and quantitative analysis according to the staining results. G1: Ctrl, G2: GDVs, G3: GDVs@CuPBA, G4: GDVs@CuPBA -iRGD. Data in (A, B) are presented as mean ± SD (n = 3 mice). Data in (C-K) are presented as mean ± SD (n = 5 mice), ns indicates no significance

Evaluation of the biosafety of GDVs@CuPBA-iRGD in vivo

To further investigate the potential toxicity of GDVs@CuPBA-iRGD in vivo, we performed the analyses of biosafety associated toxicological serum and pathology. We investigated the blood compatibility of GDVs@CuPBA-iRGD by hemolysis assay and observed that these GDVs@CuPBA-iRGD did not cause hemolysis (Fig. S6A, B, Supporting Information). In the blood routine examination, there were no significant changes in the indicators of leukocytes, erythrocytes, lymphocytes, hemoglobin, and platelets (Fig. 7A). Correspondingly, the blood biochemical indicators were assessed, the results showed that the liver and kidney function indexes of C57BL/6 mice in each group were maintained within the normal range, and no obvious damage was found (Fig. 7B). Moreover, the pathology revealed by H&E staining also showed no significant injury in major organs including heart, liver, kidney, lung, and spleen (Fig. 7C). This evidence supports the biocompatibility of GDVs@CuPBA-iRGD therapy in vivo. To evaluate the intestinal distribution of GDVs@CuPBA-iRGD, DiO-labeled GDVs@CuPBA-iRGD were i.v. into mice. As shown in Fig. 7D, clear green fluorescence signals were detected in the stomach, jejunum, ileum, and cecum. These signals were primarily localized in the mucosa of the jejunum, ileum, and cecum, suggesting that GDVs@CuPBA-iRGD can reach the intestinal tract via systemic circulation and may be subsequently excreted from the body.

Fig. 7.

Biocompatibility evaluation. (A) Complete blood panel analysis results of C57BL/6 mice after PBS, GDVs, and GDVs@CuPBA-iRGD treatment. (B) Blood biochemistry indicates the liver (ALT, AST, T-Bil) and kidney (Cr, BUN) functions of C57BL/6 mice after PBS, GDVs, and GDVs@CuPBA-iRGD treatment. (C) H&E staining of major organs of C57BL/6 mice in each group after administration. (D) Distribution of DiO- GDVs@CuPBA-iRGD in different parts of the gastrointestinal tract in mice at the time point of 6 h. G1: Ctrl, G2: GDVs, G3: GDVs@CuPBA-iRGD. Data were presented as mean ± SD (n = 3 mice)

scRNA-seq reveals that GDVs@CuPBA-iRGD alleviates the tumor microvascular abnormality.

To further elucidate the mechanism by which GDVs@CuPBA-iRGD inhibit tumor load, we applied single-cell RNA sequencing (scRNA-seq) to study liver tumor tissue samples treated with PBS and GDVs@CuPBA-iRGD (Fig. 8A). After quality control and filtering, we obtained the transcriptomes of 5002 and 5653 single cells treated with PBS and GDVs@CuPBA-iRGD respectively, for downstream analysis. Ten major cell types were identified according to well-known canonical marker genes (Fig. 8B), including T cells (CD3E, CD3D), NK cells (KLRD1, NKG7), B cells (CD79A, CD79B), neutrophil cells (S100A8, S100A9), endothelial cells (PECAM1, VWF), Proliferating cells (TOP2A, MKI67), fibroblast cells (COL1A1, COL1A2), kupffer cells (C1QA, CSF1R), dendritic cells (CLEC9A, ITGAX), and HCC cells (ALB, ASS1) (Fig. 8C). We observed that the major cell subsets of the GDVs@CuPBA-iRGD tumors showed significantly different characteristics and composition compared with the Ctrl tumors. Specifically, the GDVs@CuPBA-iRGD tumors contained more T cells, along with fewer HCC and neutrophil cells (Fig. 8D, E). The pseudotime analysis on the differentiation status of HCC cells were performed. The results showed that there were three differentiation trajectories and state, mapping the cell subpopulation classification information onto the cells in the differentiation trajectories showed that state 1 mainly corresponds to GDVs@CuPBA-iRGD, and states 2 and 3 mainly correspond to Ctrl (Fig. 8F). The pseudotime trajectory differential gene expression analysis revealed that the pro-angiogenic gene STMN1 was upregulated along the transition towards States 2 and 3, whereas the VM inhibitor gene BTG2 was concomitantly downregulated (Fig. 8G). We focused on the changes of VM-related genes in tumor cells after different treatments. Notably, the GDVs@CuPBA-iRGD group showed significant down-regulation of the expression of key markers related to tumor VM (Fig. 8H). Further analysis revealed that the differentially expressed genes were enriched for VM related biological processes and signaling pathways, such as cell–cell adhesion, angiogenesis, ECM-receptor interaction, and focal adhesion (Fig. 8I, J). Notably, the differentially expressed genes were also enriched in immune-related biological processes and KEGG pathways such as T cell activation, and cytokine-cytokine receptor interaction. Previous studies have shown that abnormal tumor vasculature impairs the infiltration and migration of immune effector cells, creating an immunosuppressive TME [34, 35]. Taken together, these findings suggest that while suppressing VM, GDVs@CuPBA-iRGD may also involve cytokine-mediated tumor-immune cell interactions within the TME, indirectly reflecting the potential immunomodulatory function of GDVs@CuPBA-iRGD.

Fig. 8.

Cell composition landscapes of GDVs@CuPBA-iRGD treatment in C57BL/6 mice by scRNA-seq analysis. (A) Overall experimental design for scRNA-seq analysis of liver tumor tissues from C57BL/6 mice treated with PBS or GDVs@CuPBA-iRGD. (B) Cell types of sequencing cells projecting on UMAP visualization. Colors indicate different cell types, which included T cells, NK cells, B cells, neutrophil cells (Neu), endothelial cells (Endo), Proliferating cells, fibroblast cells (Fib), kupffer cells, dendritic cells (DCs), and Hepatocellular carcinoma cells (HCC). (C) Dot plot depicting expression of classical marker in responding cell type. (D) UMAP graphs show the number of different cell types in PBS or GDVs@CuPBA-iRGD treated liver tumor tissues. (E) Bar plots showing the percentage (%) of cell types in PBS and GDVs@CuPBA-iRGD group. (F) Trajectory inference of HCC cells, with coloring based on differentiation states and groups. (G) The expression trends of key genes associated with HCC cell angiogenesis and migration along the pseudotime axis. (H) The expression of VM-related genes in different groups. (I, J) Differentially expressed genes in HCC cells were subjected to GO and KEGG enrichment analyses. G1: Ctrl, G2: GDVs@CuPBA-iRGD

GDVs@CuPBA-iRGD reverses the tumor immunosuppressive microenvironment

To determine the characteristics of T cells in different treatments, we extracted the information of T cells from scRNA-seq data (Fig. 9A), we re-clustered the T cells and obtained eight functional clusters (Tc1-Tc8) (Fig. 9B). Interestingly, the percentages of Tc2, Tc3, and Tc4 increased in the GDVs@CuPBA-iRGD, while decreased in the Ctrl group. Conversely, Tc1 exhibited the opposite trend (Fig. 9C). Interpretation of the up-regulated genes and biological features of each T cells type provides further insights into its unique functional characteristics. Tc1 cluster highly expressed CD4, indicating that it is a group of helper T cells that regulate immune responses by producing cytokines. The biological processes by GO analyzed were also mainly related to cell activation and immune process (Fig. 9D). Tc2 and Tc3 clusters showed cytotoxic characteristics, and the marker genes were mainly granzyme family members (GZMA, GZMK) and chemokines (CCL3, CCL4). GO analysis showed that Tc2 and Tc3 clusters were mainly related to response to stimulus and immune response (Fig. 9D). Lef1, an effector transcription factor downstream of the WNT signaling pathway, converting cytokine-derived signals into signals for protein synthesis and DNA replication, is a marker gene for the Tc4 clusters. GO analysis suggested that this cluster might be closely related to the process of protein synthesis (Fig. 9D). Tc5 clusters expresses genes associated with antitumor immunosuppression (ZBTB1, XCL1) and apoptotic process-related GO terms (Fig. 9D). Tc6 and Tc7 clusters express genes associated with γδT cells (SOX13, SCART1) and exert unique antitumor effects (Fig. 9D). FOXP3, the major regulator of regulatory T cells, is a marker gene of the Tc8 cluster, suggesting that this cluster is responsible for regulating the arrest of the immune system, thereby preventing the body from excessive immune response (Fig. 9D). We included the expression levels of specific molecules and found that Tc2 and Tc3 cells express antitumor effector molecules (GZMA, GZMB, and PRF1), which may enhance antitumor immunity. Tc1 and Tc8 cells preferentially express a variety of molecules that may drive T-cell exhaustion (CTLA4, TOX, and TNFRSF9) (Fig. 9E). In addition, we observed that genes upregulated in T cells were enriched in cytokine-mediated signaling pathways and positive regulation of immune responses (Fig. 9F). Overall, our study revealed that GDVs@CuPBA-iRGD enhanced T cells cytotoxicity and immune response, and reshaped the antitumor immune process.

Fig. 9.

GDVs@CuPBA-iRGD reshape the tumor immune microenvironment to enhance antitumor immunity. (A) UMAP plot displaying the re-clustering of T cells in scRNA-seq. (B) UMAP visualization of eight types of T cells. (C) Bar plot of the percentage (%) of each cell type in Ctrl and GDVs@CuPBA-iRGD group. (D) Heatmap showing the top 10 up-regulated genes for each cell type, with representative genes marked (left). Representative GO terms are highlighted (right). (E) UMAP plot showing expression levels of certain signature genes in T cells. (F) KEGG pathway enrichment analysis was performed on the up-regulated genes of T cells

Discussion

As a renowned medicinal plant, ginseng has a history of application spanning millennia, and its pharmacological anti-tumor effects have been extensively validated across various cancer types [36–38]. However, the therapeutic efficacy of single-component extracts is often limited by factors such as insufficient bioavailability and off-target effects [39]. In this study, we isolated GDVs as an integrated therapeutic platform, which natively encapsulate a diverse array of bioactive molecules, including lipids, proteins, and metabolites, thereby offering a synergistic advantage over monotherapeutic approaches. To functionally augment these natural vesicles, we employed a biomimetic mineralization strategy using a PBA. While PBAs are well-established in materials science and nanomedicine for their excellent biocompatibility, multifaceted catalytic activity, and unique pH-responsive degradation [16, 40, 41], their application in mineralizing natural exosome-like vesicles, such as GDVs, represents a novel and pioneering strategy. This design leverages the complementary strengths of the biological GDVs and the functional PBA coating. In this system, PBA not only acts as a carrier but also serves as a functional substance. Its stimuli-responsive degradation enables the controlled release of copper and iron ions, ultimately inducing both cuproptosis and ferroptosis in HCC cells. Furthermore, to achieve active tumor targeting, we functionalized the surface of this innovative GDV@CuPBA core–shell structure with the iRGD tumor-penetrating peptide. This final modification is anticipated to confer superior tumor targeting and enhanced cellular internalization, completing the rational design of our multi-functional nanoplatform.

The peroxisome proliferator-activated receptors (PPARs) are a class of nuclear receptors that function as transcription factors regulating gene expression. They play pivotal roles in lipid metabolism, inflammatory responses, and cell differentiation [42]. Among the three primary subtypes (PPARα, PPARβ/δ, and PPARγ), PPARγ is crucial in regulating cell proliferation, differentiation, and immune responses [43]. Consequently, PPARγ has emerged as a key drug target, leading to the development of numerous agonists, such as thiazolidinediones (TZDs), for treating metabolic diseases like obesity and diabetes [44]. Beyond these applications, PPARγ also profoundly impacts non-metabolic diseases, including non-alcoholic fatty liver disease (NAFLD), cancer, and inflammatory diseases [22, 45]. Studies have shown that PPARγ agonists can inhibit the proliferation and invasion of endometrial cancer cells [46]. However, the role of PPARγ in tumor VM remains unclear. In our study, we revealed that GDVs@CuPBA-iRGD promotes the nuclear translocation of PPARγ, which subsequently triggers its transcriptional activity. This activation leads to the downregulation of key pro-VM genes such as MMP9, ICAM1, and PTGS2, thereby inhibiting tumor VM formation. This provides a deeper understanding of the function of PPARγ in tumor cell plasticity and VM formation. At single-cell resolution, spatial variations in GDVs@CuPBA-iRGD action become visualized; we found that GDVs@CuPBA-iRGD suppress VM while simultaneously remodeling T cell states through increased recruitment of antitumor effector molecules and reduced proportion of exhausted T cell subsets, thereby reprogramming the tumor immune microenvironment. These findings establish GDVs@CuPBA-iRGD as a promising dual-functional nanomedicine that concurrently inhibits VM and activates antitumor immunity.

Conclusions

In this study, we developed a novel bio-mineralized nanomedicine, GDVs@CuPBA-iRGD, for effective cancer therapy. The nanoplatform was constructed based on GDVs, which were mineralized with a Prussian blue analogue and then functionalized with the iRGD tumor-penetrating peptide. This design endowed GDVs@CuPBA-iRGD with excellent pH-responsive degradation and superior cellular uptake efficiency. Consequently, it significantly inhibited VM formation in vitro and in vivo as well as induced multiple cell death pathways, thereby effectively suppressing tumor progression. Furthermore, GDVs@CuPBA-iRGD demonstrated a superior biocompatibility and biosafety. Mechanistic investigations revealed that the anti-VM effects are mediated through the promotion of linoleic acid metabolism, which activates PPARγ nuclear translocation. This pivotal event subsequently triggers a regulatory cascade that leads to the downregulation of key genes critical for VM, ultimately inhibiting VM formation. Moreover, scRNA-seq analysis demonstrated that GDVs@CuPBA-iRGD remodeled the tumor immune microenvironment to potentiate antitumor immunity. Our findings highlight GDVs@CuPBA-iRGD as a potent and safe nanomedicine that targets VM, offering a promising strategy for treating aggressive tumors.

Author contributions

T.S. and H.L. designed this study. T.S., H.L., and C.G. wrote, reviewed, and revised the manuscript. C.G., X.Z., Q.L., X.S., X.H., Q.Q., X.C., and Y.Z. performed the experiments, analyzed and interpreted data. Y.L. and J.H. provided administrative, technical, or material support. All authors read and approved the final manuscript.

Funding

This study was supported by the Tianjin Science and Technology Program (25ZXZSSS00260, 24ZXZSSS00020).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

All animal experiments were conducted in accordance with the WMA Declaration on Animal Use in Biomedical Research and were approved by the Animal Ethics Committee of Nankai University Laboratory Animal Center (No. 2024-SYDWLL-000801).

Competing interests

The authors declare no competing interests.