Concurrent P‑Selectin Targeting Nanoparticle Orchestrates Tumor-Immune Dynamics for Advanced Immunochemotherapy

Wei Lee; Syuan-Ling Lin; Jui-Yu Chen; Bo-Jie Huang; Wee-Wei Chieng; I-Jung Tsai; Ting-Yu Chang; Yen-Ho Lai; Wan-Zhen Hong; Kevin Chih-Yang Huang; Mien-Chie Hung; San-Yuan Chen; Long-Bin Jeng; Woei-Cherng Shyu; Chih-Sheng Chiang

doi:10.1021/acsnano.5c15120

. 2026 Apr 28;20(18):13496–13516. doi: 10.1021/acsnano.5c15120

Concurrent P‑Selectin Targeting Nanoparticle Orchestrates Tumor-Immune Dynamics for Advanced Immunochemotherapy

Wei Lee ^†, Syuan-Ling Lin ^‡,^§, Jui-Yu Chen ^‡, Bo-Jie Huang ^‡, Wee-Wei Chieng ^‡, I-Jung Tsai ^†, Ting-Yu Chang ^†, Yen-Ho Lai ^∥, Wan-Zhen Hong ^§, Kevin Chih-Yang Huang ^⊥,^#,^∇,^○, Mien-Chie Hung ^§,^∇,^◆, San-Yuan Chen ^§,^¶, Long-Bin Jeng ^†,^⟁, Woei-Cherng Shyu ^‡,^§,^○,^△,^▲,^▽, Chih-Sheng Chiang ^†,^§,^∇,^○,^△,^*

PMCID: PMC13173641 PMID: 42047284

Abstract

Cancer therapy is often constrained by targeting single pathogenic mechanisms without addressing the complex tumor microenvironment (TME). Here, we introduce FINAL (Fucoidan–docetaxel Immunomodulatory Nanoparticles as an Antitumoral Lancer), a surface-engineered nanoplatform that simultaneously targets P-selectin-expressing cancer cells and tumor-associated macrophages (TAMs). Beyond targeting specificity, fucoidan surface modification provides intrinsic bioactivities that individually modulate both cell types while coordinately reshaping the TME. FINAL achieves dual-cell orchestration through P-selectin-mediated targeting, activating both receptor-dependent signaling pathways and receptor-independent bioactivities of fucoidan and DTX. P-selectin-mediated targeting enhances cellular uptake and disrupts tumor-TAM adhesion, reducing the level of circulating hybrid cell (CHC) formation. Independent of targeting, fucoidan’s bioactivity reduces cellular reactive oxygen species in cancer cells, promotes M1 macrophage polarization, and suppresses VEGF-A-mediated angiogenesis. RNA-seq transcriptomic profiling demonstrated that FINAL drives synergistic immune activation pathways while simultaneously repressing tumor progression signatures, providing mechanistic evidence for concurrent tumor-immune dynamics at the molecular level. In triple-negative breast cancer (TNBC) models, this system-level approach achieved breakthrough therapeutic outcomes, including doubling survival duration, suppressing primary tumor growth, inhibiting lung metastasis, and preserving bone marrow hematopoietic function, demonstrating translational potential compared to conventional docetaxel formulations. Importantly, FINAL maintained therapeutic benefits while reducing systemic toxicity, establishing an optimal balance between antitumor efficacy and safety. The rationally designed fucoidan nanobio interface establishes FINAL as a versatile platform for P-selectin-expressing diseases for next-generation immunochemotherapy agents with broad translational potential across multiple cancer types.

Keywords: P-selectin, fucoidan, tumor microenvironment, immunochemotherapy, tumor-associated macrophages, circulating hybrid cells

graphic file with name nn5c15120_0012.jpg

graphic file with name nn5c15120_0010.jpg

Introduction

The trajectory of cancer drug development from nonspecific cytotoxic agents to molecularly targeted therapies has revolutionized treatment paradigms, demonstrating the power of precision medicine in selectively disrupting cancer-specific pathways. Nevertheless, this single-target approach encounters substantial limitations in aggressive malignancies, where durable tumor control remains elusive despite therapeutic advances. The challenge becomes even more pronounced in cancers lacking well-defined targetable markers, where conventional precision strategies may be inadequate to address the multifaceted nature of tumor progression and resistance. Triple-negative breast cancer (TNBC) exemplifies these challenges, lacking specific therapeutic targets while exhibiting extensive crosstalk between cancer cells and tumor-associated macrophages (TAMs) that fosters immunosuppression, angiogenesis, and metastasis. −

Recent discoveries of circulating hybrid cells (CHCs)fusion products between tumor cells and macrophages − have revealed their crucial role as metastatic drivers and adverse prognostic indicators across multiple cancer types. ,− CHCs exhibit enriched M2-like macrophage phenotypes, linking their formation directly to the immunosuppressive TME driven by TAMs. , Moreover, CHCs inherit tumor cell proliferative capacity and macrophage immune privilege simultaneously, enabling them to evade cytotoxic therapies through macrophage-derived survival mechanisms while resisting immune interventions via their tumor cell characteristics, rendering conventional single-target therapies ineffective. Importantly, CHC formation primarily involves direct tumor-macrophage interactions mediated by cell adhesion mechanisms, with molecules such as P-selectin playing a particularly important role in facilitating cell adhesion during the fusion process, creating a therapeutic vulnerability that requires simultaneous disruption of both cellular crosstalk and elimination of the participating cell populations. Therefore, concurrent targeting of both cellular components can disrupt the adhesion-dependent CHC formation process, ultimately achieving systemic therapeutic control.

P-selectin is a constitutive adhesion molecule overexpressed across multiple aggressive cancer types, including TNBC, pancreatic, ovarian, and colorectal carcinomas, as well as on TAMs, , but absent on quiescent endothelial cells and platelets. ,, Targeting this shared marker enables a direct dual-cell approach with wide clinical applicability, simultaneously disrupting tumor–macrophage interactions while minimizing off-target toxicity. Fucoidan, a sulfated polysaccharide with high affinity for P-selectin, ,, presents an opportunity for developing a targeted drug delivery system. , Beyond its targeting capabilities, fucoidan presents intrinsic bioactivities including inducing antioxidant activity, antiangiogenesis, M1 macrophage (M1) polarization, and repolarizing M2 macrophage (M2) toward M1 phenotypes. −

Based on these properties, we developed FINAL (Fucoidan–docetaxel Immunomodulatory Nanoparticles as an Antitumoral Lancer), a docetaxel-loaded poly(lactic-co-glycolic acid) (PLGA) nanoplatform where rational surface engineering with fucoidan creates a bioactive nanobiointerface for concurrent targeting of TNBC cells and TAMs through shared P-selectin. FINAL operates through a sophisticated dual-mechanism approach that simultaneously disrupts tumor-macrophage crosstalk and eliminates both cellular populations, orchestrating a balance between targeted cytotoxicity and immune activation, while preventing CHC formation and reversing TME immunosuppression.

Using the 4T1 TNBC mouse model as a representative aggressive malignancy, FINAL achieved robust therapeutic efficacy by increasing the level of DTX accumulation in the tumor, effectively suppressing tumor growth, dramatically reducing lung metastasis, and doubling the survival period. Importantly, transcriptomic profiling revealed upregulation of immune-activating pathways and suppression of tumor-promoting programs, confirming system-wide TME reprogramming. By intercepting CHC formation, repolarizing TAMs, and eliminating cancer cells simultaneously, FINAL delivers an integrative strategy that achieves durable and spectrum-wide tumor–immune control. Importantly, FINAL preserved critical physiological functions without causing bone marrow suppression or neurotoxicity, even at double the conventional DTX dose, highlighting its potential for clinical translation. Together, the evidence positions FINAL as a translatable immunochemotherapy framework with broad applicability to P-selectin-expressing malignancies, introducing dual-cell P-selectin targeting as a powerful paradigm for next-generation cancer nanomedicine.

Results and Discussion

Characterization of DTX-Loaded NPs Coated by PVA, Dextran Sulfate, and Fucoidan

To implement the dual-cell P-selectin targeting strategy outlined above, we developed FINAL using biodegradable PLGA as the matrix material for docetaxel encapsulation. To achieve colloidal stability in aqueous solutions, a hydrophilic/amphiphilic coating material on the surface of the hydrophobic PLGA core is essential. Through ultrasonic emulsification, PLGA and DTX in the organic phase were condensed into a hydrophobic core and further stabilized by fucoidan in the continuous phase. Aside from FINAL, Poly(vinyl alcohol) (PVA, a common coating material in PLGA-based nanoparticle) and dextran sulfate (Dex) that present low and high structural similarity to fucoidan were used to synthesize control NPs including DTX-free NP vectors (i.e., PVA-NP and Dex-NP) and DTX-encapsulated NPs (i.e., DTX@PNP and DTX@Dex-NP) (Figure A).

Characterization of DTX-loaded NPs coated by PVA (DTX@PNP), dextran sulfate (DTX@Dex-NP), and fucoidan (FINAL). (A) Schematic illustration of DTX-encapsulated NPs stabilized with PVA, dextran, and fucoidan, respectively. DTX is encapsulated in the core of the NPs. (B) The size of the nanoparticles (NPs) with (B1) and without (B2) the addition of l-lysine was measured using dynamic light scattering (DLS). The introduction of l-lysine to the synthesis effectively reduced the size of all of the NPs. (C) The nanostructures of DTX@PNP, DTX@Dex-NP, and FINAL were observed using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). (D) The zeta potential of the NPs was measured using DLS. (E) The binding specificity for the three different NPs toward P-selectin, L-selectin, E-selectin, and BSA was assessed, and the intensity of fluorescence was measured using an ELISA reader. n = 3 independent NP samples.

The original DTX@PNP, DTX@Dex-NP, and FINAL exhibited an average hydrodynamic diameter of more than 200 nm (Figure B1), which exceeds the optimal size range for achieving enhanced permeation and retention (EPR) effects in nanomedicine. To reduce particle size for improved blood circulation and tumor accumulation, lysine was introduced to reduce particle size and improve emulsion stability through reduced interfacial tension and controlled droplet formation during emulsification. − Upon incorporating lysine into the aqueous phase, all three NP formulations exhibited dramatically reduced sizes (Figure B2). FINAL presented the smallest size at 157.7 nm (polydispersity index, PDI = 0.143), compared with DTX@PNP (203.5 nm, PDI = 0.12) and DTX@Dex-NP (183.8 nm, PDI = 0.11). These size variations arise from the inherent physicochemical properties of the surface materials during emulsification. Fucoidan and dextran sulfate, with their highly sulfated structures, create stronger electrostatic interactions, potentially leading to enhanced electrostatic repulsion and smaller initial droplets during emulsification. In contrast, PVA’s neutral hydroxyl groups result in weaker interparticle repulsion and larger particle formation compared to fucoidan.

Benefiting from the repulsive negative charges between molecules, FINAL and DTX@Dex-NP showcased homogeneous nanostructures with low polydispersity under scanning electron microscopy (SEM) at low magnification (Figure C, upper panel). The size, PDI, and zeta potential of FINAL remained consistent during 72 h of monitoring, showcasing high colloidal stability (Figure S1A,B), where fucoidan was found to form a stable coating over the surface of FINAL (Figure S1C). In contrast, minimal aggregation was found in DTX@PNP as characterized by transmission electron microscopy (TEM) (Figure C, lower panel). Consistently, FINAL and DTX@Dex-NPs demonstrated highly negative zeta potentials at −55.1 and −63 mV, respectively. In contrast, DTX@PNP, with hydroxyl groups on its surface, presented a relatively neutral zeta potential (Figure D).

As shown in Table S1, all three DTX nanoformulations presented similar encapsulation efficiencies (EE) and drug loading content (DLC). In addition, release studies in PBS (pH 7.4) with 0.5% Tween-80 at 37 °C revealed comparable release kinetics among all formulations (Figure S2). These similar properties ensure fair comparisons for subsequent bioactivity assessments across the three formulations.

Importantly, in the P-selectin binding specificity assay, FINAL exhibited a fluorescent intensity significantly higher than that of DTX@PNP and DTX@Dex-NP, indicating FINAL possessing a strong affinity toward P-selectin (Figure E). Of note, FINAL exhibited no specific binding toward E-selectin and BSA, mitigating nonspecific interactions with other proteins during circulation. These results indicate that the surface coating of fucoidan effectively enables nanotherapeutic targeting to cancer cells that express P-selectin, facilitating the targeted delivery of DTX to various cancer types.

Fu-NP Enables Dual-Targeting by Recognizing P-Selectin Shared by TNBC and TAM

To verify the expression of P-selectin in TNBC tissues, we conducted an immunohistochemistry (IHC) analysis on 44 clinical samples from TNBC patients. The result revealed abundant P-selectin expression in tumor tissues compared to adjacent normal tissues (Figure A).

To characterize P-selectin distribution within the TME, we analyzed three key cellular populations, including TAMs (CD45⁺/F4/80⁺), non-TAM leukocytes (CD45⁺/F4/80^–), and cancer cells (CD45^–/CD31^–; 95.2 ± 3.2% of this subset expressed luciferase, Figure S3A) in a luciferase (Luc)-expressing 4T1 (4T1-Luc) syngeneic TNBC mouse model. Flow cytometric analysis of whole tumors at 20 days postinoculation revealed heterogeneous P-selectin expression, with TAMs showing the highest levels, followed by cancer cells, while non-TAM leukocytes exhibited notably lower levels (Figure B; Figure S3B–C).

To evaluate P-selectin targeting efficiency, we compared the cellular uptake of three DTX-free quantum dot-encapsulated nanoformulations: PVA-NP, Dex-NP, and Fu-NP. Using radiation-induced P-selectin-expressing MDA-MB-231 cells (Figure S4) and THP-1-derived M2, we observed superior uptake of Fu-NP over the control formulations. At 100 μg mL^–1 over 30 min, Fu-NP showed 2.73-fold and 1.97-fold higher uptake in MDA-MB-231 cells compared to PVA-NP and Dex-NP, respectively (Figure C, upper panel, and D). While all NPs demonstrated substantial uptake by M2 macrophages (Figure C, lower panel; Figure S3G), Fu-NP achieved the highest median fluorescent intensity (MFI) (Figure E), indicating enhanced cell association with P-selectin-expressing cells.

To validate these findings in vivo, we administered DTX-free Fu-NP to 4T1-bearing mice at 20 days post-tumor inoculation. Immunohistochemical analysis revealed preferential Fu-NP accumulation in regions with higher P-selectin expression, confirming the high-affinity P-selectin-fucoidan interaction (Figure F). At the cellular level, flow cytometric analysis demonstrated that TAMs and cancer cells with higher P-selectin expression showed 1.3-fold and 2-fold higher Fu-NP uptake, respectively, compared to their P-selectin^low counterparts (Figure G,H; Figure S3D,E). Intriguingly, in non-TAM leukocytes, P-selectin expression levels did not correlate with Fu-NP uptake (Figure I; Figure S3F), suggesting alternative uptake mechanisms in these cells. Collectively, these findings establish that Fu-NP achieves effective dual-cell targeting through the fucoidan/P-selectin axis, as demonstrated by preferential uptake in both P-selectin-expressing cancer cells and TAMs.

Dual-Cell Targeting by FINAL Promotes M1 Polarization and Suppresses Tumor Invasion In Vitro

Having established dual-targeting selectivity, we investigated the cellular and molecular mechanisms by which FINAL influences both cancer cells and macrophages. We examined whether P-selectin-mediated dual targeting and the bioactivities of FINAL could modulate macrophage polarization and tumor cell signaling, which critically determine the pro-tumorigenic cellular environment. We focused on two key mechanistic pathways: direct modulation of macrophage polarization states, and indirect effects via suppression of tumor-derived pro-M2 signals, including cROS and soluble factors. −

M1 suppresses tumor progression through pro-inflammatory factors, while M2 promotes immunosuppression and metastasis. Regulating this balance is critical for inhibiting TME-driven metastasis. , Mechanistically, fucoidan facilitates M1 polarization and the repolarization of M2 by suppressing intracellular ROS within macrophages, inhibiting NF-κB signaling, and downregulating chemokines including CCL22 and CSF-1. ,,

To exclude DTX-specific effects and isolate the impact of surface coatings, we first evaluated DTX-free formulations (PVA-NP, Dex-NP, and Fu-NP). All formulations promoted M1 differentiation from M0 macrophages while inhibiting M2 polarization, with Fu-NP showing the strongest M2 inhibition (Figure S5A–C). When applied to differentiated M2, only PVA-NP and Fu-NP reversed M2 polarization, among which Fu-NP was the most effective formulation (Figure S5D). Collectively, these results support the potent immunomodulatory profile of Fu-NP in comparison to other controls.

Since M2-like TAMs facilitate tumor progression by enhancing invasion and immunosuppression, we assessed whether DTX-free NPs interfere with these processes using migration and invasion assays with M2 macrophages (upper chamber) exposed to MDA-MB-231-conditioned medium (lower chamber). Both PVA-NP (40% reduction) and Fu-NP (53% reduction) markedly suppressed M2 migration toward MDA-MB-231-conditioned medium, with Fu-NP showing the strongest effects, while Dex-NP (18% reduction) had minimal impact (Figure S6A). In Matrigel invasion assays, all NPs attenuated M2 invasion with Fu-NP again demonstrating superior efficacy (Figure S6B).

Elevated cROS in tumor cells promotes M2 polarization and TAM recruitment. , We found that PVA-NP decreased cROS levels by 56%, Dex-NP by 43%, and Fu-NP by 82% in MDA-MB-231 cells, with Fu-NP showing the greatest reduction (Figure S6C). This pronounced effect is consistent with the intrinsic properties of fucoidan, which can attenuate intracellular ROS in tumor cells and thereby influence macrophage polarization. In transwell systems mimicking TME conditions, where M2 (lower chamber) were exposed to soluble mediators and ROS-associated signals generated by TNBC cells (upper chamber), only Fu-NP significantly reduced M2 polarization (Figure S6D). Across six key parametersTAM uptake, cancer cell uptake, P-selectin binding, M1 polarization, cROS reduction, and M2 migration inhibitionFu-NP consistently outperformed other formulations (Figure S6E). These results demonstrate that Fu-NP’s P-selectin targeting capability confers superior performance across multiple cellular parameters relevant to tumor-immune interactions. Given Fu-NP’s superior performance attributed to P-selectin-mediated dual targeting and its bioactivities, we selected nontargeting and bioinert DTX@PNP as the control for subsequent experiments.

To dissect individual component effects, we compared DTX-free carriers (PVA-NP, Fu-NP) to DTX-loaded carriers (DTX@PNP, FINAL). Analysis of IL-1β, TNF-α, and CD206 mRNA showed that both fucoidan and DTX independently promoted M1 polarization, with FINAL producing additive effects reflecting the combined impact of both components (Figure A; Figure S7A–B). Notably, FINAL significantly reversed M2 polarization in prepolarized cells, as validated by immunocytochemistry (ICC) (Figure B).

Dual-cell targeting by FINAL promotes M1 polarization and suppresses tumor invasion *in vitro*. (A) Macrophage polarization in response to DTX-free or DTX-loaded NPs using RT-qPCR. n = 3 independent cell samples. (B) The influence of DTX-free or DTX-loaded NPs on the polarization of differentiated M2 macrophages through IHC staining. n = 3 independent cell samples, and the images were representative of 6 images. (C) The impact of DTX-free or DTX-loaded NPs on the invasion of M2 macrophages using a transwell coculture model. n = 3 independent cell samples, and the images were representative of 6 images. (D) The cROS level in MDA-MB-231 cells treated with DTX-free or DTX-loaded NPs for 24 h was assessed by utilizing 2′,7′-dichlorodihydrofluorescein diacetate (DCF-DA, 10 μM). Quantitative data are presented as fold change (FC), normalized to the control group. n = 3 independent cell samples. (E) DTX-free or DTX-loaded NPs to examine their effects on macrophage polarization in a transwell coculture model involving MDA-MB-231 cells and THP-1-M0, using RT-qPCR analysis. n = 3 independent cell samples. All DTX-free or DTX-loaded NP treatments were performed using an NP dosage standardized by DTX content, corresponding to 10 nM DTX. M0, nonactivated macrophage; M1, M1-macrophage; M2, M2-macrophage; MM231, MDA-MB-231; CM, conditioned medium; cROS, cellular ROS; CTL, control. Bar = 20 μm.

In migration assays, all formulationsboth DTX-free and DTX-loadedreduced macrophage migration, with FINAL demonstrating the strongest inhibitory effect (Figure S8). In invasion assays, only Fu-NP significantly reduced invasion among DTX-free formulations, while FINAL demonstrated the strongest inhibition among drug-loaded NPs, reducing invasion by 82% compared to 65% for DTX@PNP (Figure C).

Regarding the impact on cROS, conventional anticancer agents including DTX elevate intracellular ROS to induce apoptosis. Our data show that while MDA-MB-231 cells exposed to >50 nM DTX generated substantial cROS, lower doses (<10 nM) induce minimal changes (Figure S7C). In contrast, treatment with 10 nM FINALa concentration below DTX IC50markedly reduced intracellular ROS compared with DTX alone (Figure D). The reduction can be attributed to fucoidan’s bioactivity to mitigate pro-tumoral and immunosuppressive signals, facilitating a TME shift conducive to antitumor immunity. In another transwell system simulating TME conditions, Fu-NP reduced M2 polarization by 46%, DTX by 44%, DTX@PNP by 48%, and FINAL by 67%, with FINAL showing the strongest effect due to additive actions (Figure E).

In summary, FINAL exerts robust dual-targeting effects by simultaneously engaging cancer cells and TAMs via shared P-selectin recognition. By integrating the ROS-scavenging and immunomodulatory properties of fucoidan with the cytotoxic effects of DTX, FINAL attenuates tumor-derived prometastatic signaling while promoting M1 macrophage polarization. This synergistic approach emphasizes modulating tumor–immune cell communication rather than cytotoxicity alone, leveraging complementary mechanisms to remodel the cellular environment in ways that disrupt key processes driving metastasis and immune suppression.

RNA-Seq Reveals Component-Specific TME Reprogramming and Validates Fucoidan-Mediated Nanobio Interactions

Given the complexity of in vivo tumor-immune interactions, we employed RNA-seq analysis to systematically dissect the individual and combined contributions of each formulation component to TME modulation. This approach enabled a comprehensive evaluation of how different surface chemistries influence therapeutic outcomes at the transcriptomic level. Mice bearing 4T1 tumors were treated according to a Q4d×4 regimen with DTX (10 mg kg^–1), empty NP vector (PVA-NP, Fu-NP), or DTX-loaded formulations (DTX@PNP, FINAL), with NP numbers standardized across groups to isolate surface coating effects (Figure A). Cells from D28 tumors were analyzed using differentially expressed gene (DEG) profiling to investigate transcriptomic changes across treatment groups. Pathways closely associated with the TME were prioritized by systematic screening within the Gene Set Enrichment Analysis (GSEA) database. First, statistical significance was assessed to compare each group’s effect on TME pathways. Second, for pathways exhibiting significant enrichment (defined as |NES| > 1, and P.adjust <0.25), we further evaluated the directionality of regulation to identify whether specific interventions promoted or suppressed critical TME functions, such as immune cell activation, tumor cell suppression, and cell–cell interaction disruption.

To establish baseline component effects, we first analyzed individual contributions. Free DTX induced the expected anticancer transcriptomic changes, affecting chemokine signaling, dendritic cell activation, and tumor proliferation pathways. Fu-NP demonstrated significant pathway modulation despite lacking a cytotoxic payload, particularly influencing TME remodeling pathways associated with epithelial-mesenchymal transitions and stromal dynamics. In contrast, PVA-NP showed minimal transcriptomic impact, serving as an appropriate inert control (Figure B).

Critically, when comparing DTX-loaded formulations, DTX@PNP with a bioinert PVA coating significantly attenuated DTX’s beneficial effects, producing weaker pathway enrichment across multiple therapeutic categories. This unexpected finding suggests that conventional “inert” coatings may inadvertently compromise drug efficacy through altered nanobio interactions. Conversely, FINAL not only preserved but also amplified DTX’s anticancer effects while activating additional therapeutic pathways, demonstrating the most comprehensive pathway modulation across all seven major functional clusters identified (Figure B).

Detailed pathway analysis revealed distinct effects on both immune and tumor cell compartments, supporting FINAL’s dual-cell targeting mechanism (Figure C). FINAL enhanced multiple immune-related pathways, including myeloid and lymphocytic leukocyte chemotaxis and migration (NES = 1.3–1.9) and myeloid dendritic cell activation (NES = 1.6). Additionally, FINAL upregulated cellular responses to type II interferon (IFN-γ, NES = 1.8) and interleukin-1 (IL-1, NES = 1.6), creating a highly immune-activated and pro-inflammatory microenvironment consistent with M1 macrophage polarization.

Concurrently, FINAL suppressed multiple pro-tumorigenic pathways including tumor cell proliferation (NES = −1.4), angiogenesis (NES = −1.6), epithelial-mesenchymal transition (EMT, NES = −1.8), and cancer stem cell dynamics (NES = −1.5 to −1.6). FINAL also downregulated oxidative stress responses (NES = −1.8), reducing pathways that typically support tumor survival and metastasis. Notably, FINAL significantly downregulated integrin binding (NES = −1.4) and cell adhesion signaling pathways (NES = −1.2), providing transcriptomic evidence for its ability to disrupt tumor-macrophage interactions that drive CHC formation and metastatic progression.

This comprehensive transcriptomic profile demonstrates FINAL’s dual-cell targeting capability through coordinated immune activation and tumor suppression. These findings validate that fucoidan surface engineering creates bioactive nanobio interfaces superior to conventional inert coatings, establishing the mechanistic foundation for subsequent protein-level and functional validation studies.

FINAL-Mediated Reduction in VEGF-A-Induced Angiogenesis In Vitro and In Vivo

Since RNA-seq analysis demonstrated that FINAL broadly suppressed tumor-promoting pathways, particularly those linked to angiogenesis (Figure ), we next assessed its functional impact in vitro and in tumor models. Vascular endothelial growth factor A (VEGF-A) secreted by M2 TAMs in the TME is a key driver of tumorigenesis. To evaluate the impact of different DTX formulations on M2 TAM-mediated angiogenesis, we studied endothelial tube formation using human umbilical vein endothelial cells (HUVECs). HUVECs were treated with conditioned media from M2 TAMs previously exposed to Taxotere, DTX@PNP, or FINAL. Quantification of tube formation revealed that Taxotere, DTX@PNP, and FINAL inhibited M2-induced angiogenesis by 29%, 51%, and 83%, respectively, compared to the control (Figure A), with FINAL demonstrating superior antiangiogenic efficacy.

Prior to in vivo angiogenesis studies, we determined the optimal therapeutic doses for different DTX formulations in the 4T1 breast cancer animal model. Following a Q4d×4 regimen, mice treated with Taxotere or DTX@PNP at 10 mg kg^–1 DTX exhibited >10% weight loss (Figure S9A). At 20 mg kg^–1 DTX, Taxotere treatment resulted in >20% weight loss and mortality within a week post-treatment. In contrast, FINAL treatment at both 10 and 20 mg kg^–1 DTX maintained a weight loss below 10%, with histological analysis confirming the safety of the 20 mg kg^–1 dose (Figure S9B). Thus, the maximum tolerated dose (MTD) for Taxotere and DTX@PNP was established at 10 mg kg^–1, while FINAL was determined to be 20 mg kg^–1.

To evaluate the impact of FINAL on tumor angiogenesis, we assessed the mature blood vessel density in tumor sections through immunohistochemical staining of α-smooth muscle actin (α-SMA). Our analysis revealed that Taxotere at a dose of 10 mg kg^–1 DTX (denoted as Taxotere(10)) promoted angiogenesis, while FINAL demonstrated dose-dependent antiangiogenic effects, with both FINAL(10) and FINAL(20) significantly reducing the α-SMA-positive area compared to other treatment groups (Figure B).

As previous studies have shown that fucoidan can inhibit angiogenesis by reducing the expression of VEGF-A in tumor, − we examined whether FINAL retained such capacity in vivo. As demonstrated by the reverse transcription quantitative real-time PCR (qRT-PCR) analysis, the mRNA expression levels of VEGF-A in tumor tissue were elevated in the mice treated with Taxotere(10) compared to the control group (Figure C). Conversely, treatment with DTX@PNP(10), FINAL(10), and FINAL(20) reduced the expression by 44%, 56%, and 85%, respectively, compared to Taxotere(10). FINAL demonstrated dose-dependent superiority over DTX@PNP(10) in suppressing VEGF-A expression.

To elucidate the cellular basis for reduced VEGF-A expression, we characterized VEGF-A⁺ cell populations within the TME. Flow cytometric analysis showed that neither Taxotere(10) nor DTX@PNP(10) affected VEGF-A levels in cancer cells or TAMs (Figure D,E; Figure S10A, gating strategies; Figure S10B–C, representative flow cytometric density plots). In contrast, FINAL demonstrated dose-dependent inhibition of VEGF-A secretion from both cell populations, with FINAL(10) and FINAL(20) significantly reducing VEGF-A levels compared to Taxotere(10). Notably, FINAL(20) further reduced levels below control in TAMs. These results highlight that FINAL suppresses angiogenesis through dual-cell targeting, reinforcing its role as a systems-level reprogrammer of the TME.

FINAL Reshapes the TME and Enhances Therapeutic Efficacy

Having established that FINAL suppresses pro-angiogenic signaling within the TME (Figure ), we next evaluated how these immunomodulatory effects translated into tumor control and therapeutic efficacy in preclinical models. Initial in vitro cytotoxicity studies revealed that FINAL exhibited comparable efficacy to Taxotere against MDA-MB-231 cells, showing similar IC50 values at 24 h and equivalent apoptotic effects at 8 h (Figure S11A,B). In contrast to TNBC cells, THP-1-derived macrophages demonstrated differential DTX tolerance with M2 showing the highest resistance. At concentrations effective against tumor cells, FINAL did not induce significant cytotoxicity in macrophages (Figure S11C). Nevertheless, FINAL demonstrated superior cytotoxicity toward M2 compared with DTX@PNP and DTX@Dex-NP.

To evaluate TME modulation and antitumor efficacy, various DTX formulations were administered intravenously to 4T1-Luc tumor-bearing mice following a Q4d×4 regimen. Notably, Taxotere(10) reduced the percentage of tumor-infiltrating lymphocytes (TILs, CD45⁺ cells), whereas FINAL(10) and FINAL(20) significantly increased the TIL levels (Figure S12A). While Taxotere(10) increased tumor cROS expression, FINAL demonstrated dose-dependent cROS reduction, with FINAL(10) and FINAL(20) decreasing levels by 33% and 50% versus Taxotere(10), and by 15% and 37% versus DTX@PNP(10), respectively (Figure A; Figure S12B, gating strategies).

FINAL reshapes the TME and enhances therapeutic efficacy *in vivo*. (A) cROS levels of cancer cells (CD45^–/CD31^–) within the tumor were detected using DCF-DA. n = 5 independent tumor samples. Quantitative data are presented as fold change (FC), normalized to the control group. (B) tSNE plots of TAMs (CD45⁺/F4/80⁺, gray) with an overlay of manually gated TNF-α⁺ cells (red) are identified using flow cytometric biaxial gating strategies and pooled data. All samples = 60,000 events; individual samples = 12,000 events (from n = 6 independent tumor samples). (C) tSNE plots of tumor-infiltrating leukocytes (TILs, CD45⁺, gray) with an overlay of manually gated M1 (CD86⁺, red) and M2 (CD206⁺, blue) are identified using flow cytometric biaxial gating strategies; and pooled data of M1/M2 in a stacked bar chart. All samples = 60,000 events; individual samples = 12,000 events (from n = 4 independent tumor samples). (D) Representative bioluminescence images of 4T1-Luc-bearing mice treated with Taxotere (10 mg kg^–1), DTX@PNP (10 mg kg^–1), and FINAL (10 and 20 mg kg^–1) (n = 6). (E) Representative images of the dissected tumors of the mice at 28-day post-tumor inoculation, and (F) the tumor volume change over the 28-day monitoring period (n = 9 biologically independent mice). Arrows indicate the treatment days under the Q4d×4 regimen. (G) The survival of tumor-bearing mice was recorded. n = 5 independent tumor samples. (10), dosage at 10 mg kg^–1; (20), dosage at 20 mg kg^–1; MΦ, macrophage; M1, M1-macrophage; M2, M2-macrophage; CTL, control. *P < 0.05; **P < 0.01; ***P < 0.001 were considered statistically significant versus the control. ^& P < 0.05; ^&& P < 0.01; ^&&& P < 0.001 were considered statistically significant versus Taxotere(10). ^# P < 0.05; ^## P < 0.01; ^### P < 0.001 were considered statistically significant versus DTX@PNP(10). ^$ P < 0.05; ^$$ P < 0.01; ^$$$ P < 0.001 were considered statistically significant versus FINAL(10).

The impact on TAM polarization was assessed through both functional activity and surface marker expression. Analysis of TNF-α production (Figure S12C, gating strategies; Figure S12D, representative density plots) revealed that FINAL(20) significantly enhanced TNF-α release by TAMs compared to all other groups, suggesting it induced TAMs to polarize toward the antitumor phenotype (Figure B). Further phenotypic analysis using surface markers (Figure S12E, gating strategies; Figure S12F, representative density plots) showed that DTX@PNP(10), FINAL(10), and FINAL(20) enhanced M1 polarization by 39%, 52%, and 68% respectively, compared to the control, with FINAL(20) achieving 34% higher M1 polarization than Taxotere(10). While all DTX formulations reduced M2 polarization compared with the control group, FINAL(20) demonstrated superior efficacy, reducing M2 polarization by 36% more than Taxotere(10) (Figure C).

The improved anticancer immunity in the TME for mice treated with FINAL led to superior dose-dependent therapeutic efficacy compared with other DTX formulations, showing enhanced local tumor control (Figure D–F) and extended survival (Figure G).

FINAL(10) and FINAL(20) significantly reduced tumor size compared with the control group and all other groups. To exclude the possibility that size differences between FINAL and DTX@PNP might confound the therapeutic efficacy comparison, we optimized the DTX@PNP preparation by reducing the PVA concentration from 0.5% to 0.25%, successfully producing size-matched particles (154.7 nm, PDI = 0.14) comparable to FINAL (157.7 nm) (Figure S13A). Importantly, therapeutic efficacy studies revealed no significant difference between the original DTX@PNP (196.5 nm) and size-optimized DTX@PNP (154.7 nm) formulations (Figure S13B,C). Both treatments showed similar tumor growth inhibition profiles, demonstrating that size variations within the ∼154–196 nm range do not significantly influence therapeutic outcomes in our PVA system. The result confirms that FINAL’s superior efficacy is attributed to its surface coating and enhanced nanobio interactions.

Collectively, these results highlight FINAL’s dual-cell targeting capacity to simultaneously modulate TNBC cells and TAMs, leading to TME reprogramming and improved antitumor immunity, thereby achieving integrated tumor–immune control and enhanced immunochemotherapeutic efficacy.

FINAL Reduces CHC Formation via TME Modulation and Disruption of Cell Adhesion

With the evidence that FINAL drove TAM toward M1 as well as inhibited tumor progression (Figure ), we investigated whether these effects translated to the reduced formation of CHCs. We examined CHC percentages in the TME, peripheral blood, and lungs at 28 days post-4T1-Luc tumor inoculation.

FINAL treatment effectively reduced the CHC percentage across all examined compartments. In the TME, both FINAL(10) and FINAL(20) decreased CHC percentages compared to the control, with FINAL(20) showing a significant reduction compared to Taxotere(10) (Figure A). Comparable reductions were observed in peripheral blood and lungs (Figure B,C; Figure S14A,C for gating strategies).

FINAL reduces CHC formation via TME modulation and disruption of cell adhesion. (A) In a 4T1-Luc mouse syngeneic tumor model after 28 days of inoculation, we employed flow cytometry to assess the percentage of CHC within the (A) TME, (B) peripheral blood, and (C) lungs. (D) The percentage of M2-CHCs in single viable cells within the TME, peripheral blood, and lungs. The representative flow cytometry plot was gated on 50,000 single viable cells in each tissue. n = 6 tumor samples for (A)–(C). n = 3 tumor samples for (D). (E) Quantification of GFP⁺/M1-CD45⁺ hybrid cell percentage, normalized to the control, following 24-h coculture of P-selectin^high MDA-MB-231-GFP cells and THP-1-M1 macrophages. Cells were treated with DTX, DTX@PNP, or FINAL nanoparticles at 10 nM concentrations. (F) Assessment of GFP⁺/M1-CD45⁺ hybrid cell formation, normalized to the control, following 24-h coculture of MDA-MB-231-GFP cells (control or P-selectin high) and THP-1-M1 macrophages. Cells were treated with DTX-free NP (PVA-NP and Fu-NP), administered at particle numbers as FINAL. (G) P-selectin^high MDA-MB-231-GFP cells were incubated with a fluoro-labeled anti-P-selectin antibody together with PVA-NP or Fu-NP for 30 min, and fluorescence intensity was measured. For (A)–(C) and (E)–(F), quantitative data are presented as fold change (FC), normalized to the control group. CTL, control; 231, MDA-MB-231; 231 P-sel^high, upregulated P-selectin on MDA-MB-231-GFP.

We further characterized M2-type CHCs (M2-CHCs) based on CD206 surface expression. Both FINAL formulations significantly reduced M2-CHC percentages in the TME compared to the control, with FINAL(20) showing superior efficacy over Taxotere(10) (Figure D). This reduction was not attributed to direct macrophage killing, as macrophages exhibited high tolerance to Taxotere (IC50 3 orders of magnitude higher than MDA-MB-231 cells; Figure S11C).

Our RNA-seq analysis revealed that FINAL downregulates integrin binding and cell adhesion pathways (Figure C), suggesting effects on cell–cell interactions beyond cytotoxicity. Fusion between macrophages and tumor cells requires an initial adhesion step. Importantly, both cell types express P-selectin and its ligand PSGL-1; , therefore, P-selectin-mediated adhesion represents a potential molecular mechanism that facilitates the physical proximity and subsequent fusion. We used conditions preserving at least 70% cell viability to evaluate whether fucoidan interferes with P-selectin-mediated adhesion, thereby reducing the level of hybrid cell formation through mechanisms beyond tumor cell depletion.

We found that both serum starvation and hypoxia (3% O₂ for 72 h) upregulated P-selectin expression on the surface of MDA-MB-231 cells stably expressing green fluorescent protein (P-selectin^high MDA-MB-231-GFP; Figure S15A). Using an in vitro CHC model (coculture of P-selectin^high MDA-MB-231-GFP and THP-1-M1 cells for 24 h), we quantified GFP⁺/M1-CD45⁺ hybrid cells following treatment with DTX, DTX@PNP, and FINAL (10 nM DTX each). Consistent with in vivo findings, only FINAL significantly reduced CHC proportions compared to the control, whereas DTX and DTX@PNP showed no difference, implicating fucoidan as the key component suppressing CHC formation through mechanisms independent of tumor cell killing (Figure E; Figure S15B, gating strategies; Figure S15C, representative flow cytometric plots).

To further dissect this mechanism, we examined DTX-free NPs (PVA-NP and Fu-NP) by administering the vectors at particle numbers equivalent to those of the FINAL group. Only Fu-NP treatment reduced the proportion of GFP⁺/M1-CD45⁺ cells in the in vitro CHC model (Figure F; Figure S15D, representative flow cytometric plots). Moreover, when P-selectin^high MDA-MB-231-GFP cells were incubated with fluoro-labeled anti-P-selectin antibody in the presence of Fu-NP, inhibition of antibody binding was observed, as indicated by a decreased mean fluorescence intensity (Figure G; Figure S15E, gating strategies; Figure S15F, representative flow cytometric plots). In contrast, PVA-NP treatment showed no effect compared to the control, suggesting that Fu-NP competitively binds P-selectin, thereby disrupting adhesion between tumor cells and macrophages.

Collectively, these findings demonstrate that FINAL attenuates CHC formation across primary tumors, circulation, and metastatic niches through dual mechanisms: (1) effective depletion of tumor cells and reversion of the M1/M2 ratio under immunosuppressive conditions, and (2) fucoidan-mediated disruption of P-selectin–dependent adhesion between macrophages and tumor cells, reducing CHC generation. This dual mechanism, which arises specifically from the fucoidan-based design and cannot be attributed to docetaxel or the nanoparticle carrier alone, underscores FINAL’s unique capacity to dismantle the cellular foundations of CHC formation. Together, these actions establish a system-wide barrier against metastatic dissemination by reprogramming the tumor–immune microenvironment through dual-cell targeting.

FINAL Suppresses Lung Metastasis by Promoting M1 Polarization of Bone Marrow-Recruited Macrophage in Lung

Building on the preceding evidence that FINAL suppresses CHC formation and remodels the TME to curb metastatic dissemination (Figure ), we next examined its impact on lung immunity, a major metastatic site in breast cancer, particularly through modulation of macrophage populations that are recognized as crucial regulators of metastasis in the lung. , We first analyzed bronchoalveolar lavage fluid (BALF) as an indicator of immune activation. Analysis of BALF revealed that both FINAL(10) and FINAL(20) significantly enhanced TNF-α production compared to control, Taxotere(10), and DTX@PNP(10) (Figure A). Flow cytometric analysis of lung macrophages corroborated these findings, with FINAL(20) significantly increasing TNF-α production (Figure B; Figure S16A, gating strategies; Figure S16B, representative flow cytometric density plots).

FINAL suppresses lung metastasis by promoting anticancer macrophage polarization in lung *in vivo.* (A) TNF-α content in bronchoalveolar lavage fluid (BALF) was measured using ELISA. n = 6 independent tumor samples. (B) tSNE plots of lung leukocytes (CD45⁺, gray) with an overlay of manually gated F4/80⁺/TNF-α⁺ cells (red); and pooled data of relative TNF-α production by lung MΦ. n = 6 independent tumor samples. (C) Heat maps of CD11b for all samples overlaid on the tSNE map. (D) tSNE plots of lung MΦ (gray) with an overlay of manually gated CD11b^–/CD206^– cells (AM1, red) and CD11b^–/CD206⁺ cells (AM2, blue); and (E) pooled data of AM1; (F) pooled data of AM2. n = 6 independent tumor samples. (G) tSNE plots of lung MΦ (gray) with an overlay of manually gated CD11b⁺/CD206^– cells (BMM1, orange) and CD11b⁺/CD206⁺ cells (BMM2, green); (H) pooled data of BMM1; (I) pooled data of BMM2. n = 6 independent tumor samples. (J) The polarization of AMΦ was assessed by the ratio of (E) AM1 to (F) AM2. (K) The polarization of BMMΦ was assessed by the ratio of (H) BMM1 to (I) BMM2. (L) Representative images of lung nodules and pooled data of lung metastatic nodule counting. n = 6 independent tumor samples. (A)–(L) All from the 4T1-Luc mouse syngeneic tumor model after 28 days of inoculation. (M) Comparison of the attributes of Taxotere and docetaxel-loaded NPs across six characteristics using a radar plot. MΦ, macrophage; AM1, AMΦ-M1; AM2, AMΦ-M2; BMM1, BMMΦ-M1; BMM2, BMMΦ-M2; CTL, control. For (B), (E)–(F), (H)–(I), quantitative data are presented as fold change (FC), normalized to the control group.

Lung macrophages comprise two distinct populations: tissue-resident alveolar macrophages (AMΦ) and bone marrow-recruited macrophages (BMMΦ). AMΦ (Luc^–/F4/80⁺/CD11b^–) typically maintain tissue homeostasis but become immunosuppressive during cancer progression. , On the contrary, BMMΦ (Luc^–/F4/80⁺/CD11b⁺) serve as crucial effector cells that exhibit phenotypic plasticity, initially displaying antitumor M1 characteristics but shifting toward a tumor-promoting M2 phenotype during disease progression. , These populations can be distinguished by their CD11b expression (Figure C). The results demonstrated that there was a substantial reduction in both AM1 (AMΦ-M1 type) and AM2 (AMΦ-M2 type) after administering Taxotere(10), DTX@PNP(10), FINAL(10), and FINAL(20) (Figure D–F; Figure S17A, CD206^– MΦ for M1 and CD206⁺ MΦ for M2; Figure S17B, representative flow cytometric density plots). Examining the polarization trend of AMΦ using the M1/M2 ratio revealed no significant differences among the groups (Figure J). Similarly, administration of Taxotere or DTX-encapsulated NPs suppressed the percentage of BMMΦ among leukocytes in the lungs, reflecting the toxicity of DTX. However, FINAL rescued the percentage of BMMΦ in the lungs when compared with Taxotere, showcasing the protective effect (Figure S17C). Further examination of polarization revealed that only the treatment of FINAL(20) did not suppress BMM1 (BMMΦ-M1 type) in the TME. Additionally, administering FINAL(20) increased the BMM1 subset compared to Taxotere(10) (Figure G–H; Figure S17D, representative flow cytometric density plots). On the other hand, all the treatments were effective in reducing the BMM2 (BMMΦ-M2 type) subset (Figure G,I; Figure S17D, representative flow cytometric density plots).

Importantly, the reversal of the M1/M2 ratio in BMMΦ after the treatment of FINAL(20) demonstrated the immune-regulating feature of FINAL (Figure K), and it in turn demonstrated the highest efficiency to reduce lung metastasis compared to other groups (Figure L). When comparing Taxotere, DTX@PNP and FINAL across six characteristics contributing to therapeutic effectiveness, our data suggested that FINAL demonstrated a larger area in the radar plot for the inhibition of tumor growth, tumor M1 polarization, tumor angiogenesis inhibition, CHC reduction, lung metastasis inhibition, and lung M1 polarization (Figure M). These data indicate that FINAL regulates macrophage polarization and alters the microenvironment of the metastatic site to reduce the tumor metastasis.

Overall, the effectiveness of FINAL in treating TNBC lies in its dual-targeting approach toward cancer cells and TAMs, a strategy that redefines tumor–immune dynamics. It specifically targeted tumor cells, reducing bone marrow toxicity while altering macrophages to a pro-tumor polarization. This action reduced the proportion of CHCs at the primary tumor site and distant metastatic sites, thereby diminishing the aggressive nature of the TNBC.

Translational Potential and Toxicology Studies of FINAL

Translating nanomedicine into clinical application requires a comprehensive assessment of effectiveness and safety. To evaluate the translational potential of FINAL, we performed a series of studies including the safety profile of fucoidan by i.v. administration, biodistribution, single-dose and repeated-dose toxicology as well as blood compatibility of FINAL. Although fucoidan is listed as a Generally Recognized as Safe (GRAS) material, previous studies were mostly focused on the oral administration route. Thus, we intravenously injected fucoidan at a high dose of 75 mg kg^–1 in mice (i.e., ∼13.5-fold the dose compared with the currently administered dose in FINAL). The administration of fucoidan did not alter serum chemistry parameters including aspartate transaminase (AST), alanine transaminase (ALT), creatinine, blood urea nitrogen (BUN), glucose, and albumin or cause histological changes in vital organs (heart, lung, liver, kidney, mandibular gland) (Figure S18). Meanwhile, the fucoidan treatment resulted in a mild to moderate increase of the corticomedullary ratio in the thymus. The results indicate that fucoidan possesses not only high biocompatibility but has the potential to stimulate immune cell proliferation and maturation under i.v. injection.

The biodistribution of DIR-loaded FINAL, DTX@Dex-NP, and DTX@PNP was monitored using IVIS. We found that among the three formulations, FINAL showed the highest fluorescent signal in tumors, indicating that FINAL possesses a superior ability to accumulate in tumors compared with other formulations (Figure S19). The selective accumulation of FINAL in tumors can be attributed to its P-selectin targeting capability. Furthermore, to directly compare the biodistribution of FINAL with Taxotere, a liquid–liquid extraction method was used to quantify drug concentrations in organs and tumors. FINAL demonstrated no significant differences compared with Taxotere at 24 h postadministration in the heart, lung, liver, kidney, and spleen. Encouragingly, the concentration of DTX in tumors for FINAL was 4.4-fold higher than that of Taxotere (Figure S20A). More importantly, when analyzing intracellular DTX concentrations in tumors by lysing tumor tissue with radioimmunoprecipitation assay buffer (RIPA), FINAL demonstrated a 13.6-fold higher concentration compared with Taxotere (Figure S20B).

FINAL presented a significantly enhanced safety profile compared to Taxotere, as demonstrated in single- and repeated-dose toxicity studies (Figures S21–S23). Given that the major adverse effects of DTX are neutropenia resulting from bone marrow suppression and neuropathy, our single-dose toxicity study specifically evaluated these end points. Remarkably, administration of FINAL did not trigger histological findings of bone marrow suppression or neuronal degeneration at doses of up to 50 and 200 mg kg^–1 DTX, respectively (Figure S21).

Most importantly, in the repeated-dose toxicity study, Taxotere at 10 mg kg^–1 induced grade 3–4 severe bone marrow toxicity, characterized by increased cellularity with myeloid lineage expansion, indicating the bone marrow’s regenerative attempt following DTX-induced myelosuppression (Figure S22). This was accompanied by substantially reduced peripheral blood parameters, including reticulocyte (RETIC), leukocyte (LEU), neutrophil (NEU), and platelet (PLT) levels (Figure S23D), confirming severe neutropenia. The experimental findings demonstrate a classic compensatory hematopoietic response following DTX treatment. Strikingly, in contrast, the bone marrow of mice treated with FINAL remained under normal conditions, exhibiting minimal to no toxicity even at double the dose (20 mg kg^–1) (Figure S22; Table S2).

Consistently, repeated-dose toxicity studies in rats showed that following FINAL treatment, serum chemistry and white blood cell counts, especially neutrophil percentage, were not impaired at 4-, 14-, and 28-days postadministration. Furthermore, levels of RETIC, LEU, NEU, and PLT remained stable throughout the entire treatment period (Figure S23A–C). Similarly, while Taxotere caused mild to moderate peripheral neuropathy with grade 3 axonal degeneration, FINAL completely preserved nerve architecture even at the higher dose of 20 mg kg^–1 DTX (Figure S22; Table S2).

FINAL also demonstrated superior blood compatibility compared with Taxotere. When whole blood was treated with FINAL and Taxotere at the same DTX concentrations, significant hemolysis was observed in the Taxotere group, while FINAL showed no hemolytic activity (Figure S24). This hemolysis in the Taxotere group likely resulted from the Triton X-100 component, which further highlights the advantage of the FINAL formulation, which eliminates the need for harsh surfactants. Collectively, this comprehensive evidence supports that FINAL offers significant protective effects in comparison to Taxotere, demonstrating a clear clinical relevance and translational potential.

Bio-Nano Interface Engineering: From TME Remodeling to Systemic Immunochemotherapy

Most cancer therapeutics target a single pathogenic mechanism of cancer cells to prevent tumor progression. However, tumor heterogeneity and the complex TME have limited the efficacy for local tumor control and metastasis inhibition. Moreover, the systemic toxicity could compress the therapeutic window and even compromise the immune system, reducing the overall immunity. For instance, despite DTX serving as the first-line therapy for a number of cancers, its poor aqueous solubility and systemic toxicity including neutropenia and neuropathy have largely compromised its effectiveness. , More critically, bone marrow suppression caused by DTX has harmful effects of impairing immunity in both the primary and metastatic TME.

Facilitating the precision delivery, FINAL retains the strengths of DTX including its high potency against TNBC cells , and its ability to enhance antitumor immunity, − but rescues the weakness of its poor aqueous solubility and systemic toxicity. Importantly, FINAL orchestrates the pharmacodynamic effects of DTX and the immunomodulatory potentialof fucoidan throughout the primary tumor, systemic circulation, pre-metastatic niches, and metastatic environment, providing a cytotoxic effect against tumor tissues while inducing anti-cancer immunity via macrophages.

In the primary tumor, by actively interacting with TNBC cells and TAMs, FINAL demonstrates the ability to reduce cROS production in TNBC cells (Figure D), induce TAM polarization toward the M1 phenotype (Figure ), decrease VEGF-A production by both cells, and subsequently inhibit angiogenesis in vivo (Figure ). Notably, this antiangiogenic effect was found to originate majorly from fucoidan’s inherent antiangiogenic activity (Figure ), accompanied by DTX’s additive effect. Of note, as DTX@PNP also exhibited an observable antiangiogenic effect, it can be inferred that PLGA might also play a role in suppressing angiogenesis, possibly by inhibiting pro-angiogenic signals typically associated with M2 macrophages, which could be studied in the future.

Building on these complementary contributions to vascular inhibition, the two distinct mechanisms involving DTX to induce cytotoxicity toward TNBC cells and fucoidan to trigger M1 polarization and the subsequent M1/M2 reversion in the TME further contribute to the inhibition of tumor progression (Figure ). Combining fucoidan and DTX in a single nanoparticle provides a synergistic effect to reshape the TME and extends the survival period of 4T1-tumor-bearing mice in a dose-dependent manner. In addition, our results demonstrate FINAL’s multimodal inhibition of CHC formation through: (1) direct targeting and killing of P-selectin-expressing TNBC cells (Figure ), (2) promotion of M1 polarization (Figure ), and (3) reduction of VEGF-A in the TME (Figure ). Together with the alleviation of angiogenesis, the comprehensive mechanism explains the observed reduction in the level of CHCs across multiple compartments (Figure ).

In addressing disease progression, the protective effects of FINAL extend beyond local tumor control to a key immune organ, the bone marrow. As the primary site of hematopoiesis, bone marrow plays a crucial role in maintaining systemic immune responses through the continuous production and mobilization of immune cells. However, DTX induces myelosuppression, compromises bone marrow hematopoietic function, leading to decreased white blood cell counts, severe neutropenia, and potential neutropenic sepsis. Importantly, FINAL effectively alleviates the myeloid toxicity likely due to the alteration of the DTX exposure profile in bone marrow (Figure S22). Moreover, FINAL maintained an appropriate proportion of peripheral monocytes to support normal macrophage differentiation, as evidenced by preserved white blood cell counts (Figure S23). The preserved hematopoietic function while promoting M1 differentiation orchestrates systemic antitumor immunity (Figure ).

In the metastatic environment, FINAL establishes protection against metastatic colonization through dual mechanisms including reducing CHC migration from the primary tumor to the lungs (Figure ) and enhancing antitumor BMM1 infiltration (Figure ). The marked decrease in tumor nodules and prolonged survival in FINAL(20)-treated mice (Figure ) underscore the importance of modulating these interconnected systemic processes. Through the P-selectin-fucoidan molecular axis, FINAL disrupts multiple pathogenic mechanisms, demonstrating the potential to simultaneously target interconnected pathological processes in cancer progression (Figure ).

Schematic illustration of FINAL as a dual-targeting NP system for cancer therapy. FINAL dual-targeting nanomedicine selectively engages P-selectin–expressing TNBC cells and TAMs within the tumor microenvironment, disrupts P-selectin-mediated cell adhesion to suppress CHC formation and metastatic fusion, and delivers chemotherapy to induce tumor cell apoptosis. Simultaneously, FINAL reprograms immunosuppressive M2-type TAMs toward a pro-inflammatory M1 phenotype, boosting antitumor immunity and attenuating angiogenesis. This orchestrated modulation of tumor–immune dynamics suppresses tumor growth, inhibits lung metastasis, preserves bone marrow function, and prolongs survival in preclinical models, with improved selectivity and safety compared to conventional docetaxel formulations.

FINAL presents the ability to yield a balance between toxicity and immunochemotherapeutic efficacy. The evaluation on the translational potential of FINAL through the single-dose toxicity, repeated-dose toxicity studies (Figures S21–S23) and blood compatibility test (Figure S24) suggests that the safety profile of FINAL is superior to Taxotere. While confirming the biocompatibility of fucoidan at FINAL’s therapeutic dose (Figure S18), we demonstrated that its surface coating plays a crucial role in mediating FINAL’s nanobio interactions, specifically in cROS regulation and P-selectin targeting.

Conclusions

Our data revealed that CHC was not only a TNBC metastatic biomarker but also a potential therapeutic target for cancer therapy. Our study illuminates the complex interplay between TNBC cells and TAMs in the TME and presents a nanotechnology-derived strategy to disrupt their interaction, thereby impeding tumor progression and metastasis. Given that high P-selectin expression is reported in lymphoma, ovarian, and lung cancer, FINAL might have the potential to extend beyond TNBC to other P-selectin-overexpressing malignancies.

While our findings establish a proof-of-concept for dual-cell targeting, several areas require further investigation. Fucoidan exhibits complex concentration-dependent effects on cellular ROS across different cancer cell types, with antioxidant effects at lower concentrations but potential cytotoxicity at higher concentrations. ,− This concentration-dependent variability underscores the need for precise dose optimization studies to ensure consistent therapeutic effects across patient populations. Additionally, accurate quantification of tissue fucoidan concentrations is essential for clinical translation and optimal therapeutic window determination.

In summary, FINAL orchestrates the pharmacodynamic effect of DTX across the primary tumor, systemic circulation, and metastatic site, addressing key limitations of nontargeted therapies for TNBC and conventional cytotoxic agents. By integrating tumor cytotoxicity with immune activation through engineered nanobio interfaces, FINAL represents a promising immunochemotherapy approach for comprehensive cancer control. This dual-cell P-selectin-targeting strategy provides a framework for developing next-generation TME-targeted therapies for TNBC and other P-selectin-associated diseases.

Methods

Ethical Statements

This study was conducted in accordance with the ethical guidelines of the China Medical University. The human tissue protocol was reviewed and approved by the Institutional Review Board (IRB) of China Medical University Hospital (approval number: CMUH110-REC1–087). Informed consent was obtained in writing from all participants prior to their inclusion in the study, following a protocol that detailed the study’s objectives, potential risks, and the confidentiality of personal data, in strict accordance with the Declaration of Helsinki. All animal experiments were performed following the protocols under the approval of the Institutional Animal Care and Use Committee of the China Medical University (approval No: CMUIACUC-2020-379 and CMUIACUC-2022-093) in accordance with the relevant guidelines and regulations.

Materials and Reagents

Dextran sulfate, poly(vinyl alcohol) (PVA, Mw = 13,000–23,000 Da), poly(lactide-co-glycolide)-Rhodamine B, l-lysine, acetonitrile, dichloromethane, and acetone were purchased from Merck. Fucoidan was purchased from Marinova Pty Ltd. Poly(d,l-lactide-co-glycolide) (Resomer RG 502 H) was purchased from Evonik Industries AG. Docetaxel was purchased from Scinopharm Taiwan, Ltd. Taxotere was a gift from the China Medical University Hospital. Qdot605 was purchased from Thermo Fisher Scientific, USA.

Synthesis and Characterization of Nanoparticles (NPs)

Nanoparticle (NP) synthesis was performed by using a single-step emulsion technique. For the preparation of NP vectors, a hydrophobic phase consisting of PLGA dissolved in dichloromethane (50 mL, 20 mg mL^–1) was combined with a hydrophilic aqueous phase containing lysine (0.625 mg mL^–1) and one of three surface coating stabilizers: PVA, dextran sulfate, or fucoidan (2 mL, 5 mg mL^–1). The resulting two-phase solution was emulsified using ultrasonication at 60 W (UP-200H, Hielscher, Germany) for 1 min while maintained on ice. After emulsification, chloroform was removed via rotary evaporation under vacuum. The resulting suspension was then subjected to centrifugation at 12,000 × g to isolate the NPs. Subsequently, the pellet was redispersed in DDW to obtain PVA-NP, Dex-NP, or Fu-NP, respectively.

For the synthesis of DTX-encapsulated NPs, DTX (1 mg) was incorporated into the hydrophobic phase (50 μL) prior to emulsification. The subsequent synthetic processes remained identical to those described for the NP vectors. Following purification by centrifugation, DTX@PNP, DTX@Dex-NP, or FINAL were obtained, corresponding to the respective stabilizers used.

To facilitate fluorescent observation under microscopy or using an In Vitro Imaging System (IVIS), Qdot605 (0.1 mg) and DiR (0.1 mg) were dissolved in dichloromethane together with PLGA and DTX, while the aqueous phase and subsequent synthesis procedures remained identical.

The morphology of DTX@PNP, DTX@Dex-NP, and FINAL was observed using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The particle size and zeta potential were measured by using dynamic light scattering (DLS, Litesizer 500, Anton Paar).

Quantification of Fucoidan Using Heparin Red

Fucoidan quantification was performed using the Heparin Red Kit (Redprobes UG, Münster, Germany) with modifications for fucoidan detection based on established protocols. The assay exploits the fluorescence quenching of the cationic perylene diimide probe upon binding to sulfated polysaccharides like fucoidan. All of the reagents were warmed to room temperature before use. For enhanced sensitivity suitable for fucoidan detection (0.5–20 μg/mL range), the Enhancer Solution and Heparin Red were mixed in a 360:1 (v:v) ratio (9 mL of Enhancer Solution with 25 μL of Heparin Red solution). Fucoidan standards (0–8 μg/mL) and samples (20 μL) were pipetted into 96-well black microplates in triplicate, followed by the rapid addition of 80 μL of assay mixture. The microplate was immediately shaken at high speed for 3 min in the fluorescence reader (excitation: 570 nm, emission: 605 nm), and fluorescence was measured within 1 min. Fucoidan concentrations were determined by comparison to calibration curves with polynomial regression applied when nonlinear relationships were observed. The assay mixture was prepared fresh daily and used within the same day of preparation.

Cell Culture

Human MDA-MB-231 and mouse 4T1-Luc breast cancer cells (ATCC CRL-2539-LUC2) were maintained in DMEM (HyClone, USA) supplemented with 10% FBS (HyClone), l-glutamine (2 mM), penicillin (100 U mL^–1), streptomycin (100 μg mL^–1), and 1 mM sodium pyruvate (above all from Thermo Fisher Scientific, USA). Human THP-1 cells were maintained in RPMI-1640 (HyClone) supplemented with FBS (10%), l-glutamine (2 mM), penicillin (100 U mL^–1), streptomycin (100 μg mL^–1), 2-Mercaptoethanol (2-ME, 50 μM), and 1 mM sodium pyruvate. All cells were detected to be Mycoplasma-free as routinely checked using a PCR Mycoplasma Detection Kit (Merck Sigma-Aldrich, USA).

Animal Care and Tumor Inoculation of 4T1 Cells

Six- to eight-week-old female BALB/c mice (National Animal Centre of Taiwan) were used to establish the syngeneic 4T1 breast cancer model. In brief, manual restraint by hand was applied for intraperitoneal (IP) injection of Zoletil (25 mg kg^–1) and Xylazine (7.5 mg kg^–1) for anesthesia. 4T1-Luc cells (1 × 10⁶ in 100 μL of PBS) were implanted into the left flank region or the fourth mammary fat pad on the right side of the abdomen of female BALB/c mice using 27-gauge needles.

Evaluating Therapeutic Efficacy by Monitoring Tumor Size and Survival Rate

Mice bearing 4T1-Luc tumors were treated with the docetaxel-loaded NPs via intravenous injection (administered through the right femoral vein) every 4 days for a total of four doses (Q4dx4), starting 7 days after tumor inoculation. Mice were treated with Taxotere and DTX@PNP at 10 mg kg^–1 DTX equivalent, while FINAL was administered at 10 and 20 mg kg^–1 DTX equivalent. The tumor volumes were monitored using a digital caliper (Mitutoyo) every 7 days using the following equation: $Tumor Volume (m m^{3}) = \frac{W^{2} \times L}{2}$ , where W is the width of the tumor, and L is the length of the tumor (W < L). Animals were euthanized when the volume was over 3,000 mm³ or the length reached 2 cm for ethical reasons. For the bioluminescence test, mice were injected with D-Luciferin (Thermo Fisher Scientific, USA) intraperitoneally and imaged using the noninvasive in vivo imaging system (IVIS 200 System, Xenogen, USA) under isoflurane anesthesia delivered via a nose cone. The survival rate was generated using the Kaplan–Meier method, and comparisons between groups were performed using the log-rank test.

Evaluation of Antimetastasis Ability

4T1-Luc tumor-inoculated mice were examined for lung metastasis by direct visual counting of the metastatic nodules. Lungs were then excised and washed once in water, immersed in 4% PFA, and further dehydrated in 30% sucrose at room temperature. Surface metastases appeared as white nodules and were counted under a microscope.

Detection of P-Selectin Expression on Live Tumor Surface

On Day 20, mice were sacrificed and tumors were excised. The tumors were digested in RPMI-1640 containing collagenase I (1 mg mL^–1, Thermo Fisher Scientific, USA) and DNase I (0.2 mg mL^–1, Merck, Germany) for 60 min at 37 °C. The mixture was shaken vigorously every 15 min. Tumor cells were homogenized using a syringe handle and a 70 μm cell strainer until all tumor tissue was resolved into a single-cell suspension. After washing, the harvested cells were stained with antihuman CD45, F4/80, CD31, and P-selectin antibodies to distinguish TAMs (CD45⁺/F4/80⁺ cells), cancer cells (CD45^–/CD31^– cells), and non-TAM leukocytes (CD45⁺/F4/80^– cells). All the above antibodies for flow cytometry are from BioLegend, USA.

The Relationship between P-Selectin Expression and NP Uptake in Live Tumors

At 20 days post-tumor inoculation, the 4T1-bearing mice were administered 10 mg kg^–1 of Fu-NP-Qdot605 (Thermo Fisher Scientific, USA). After 24 h, the mice were sacrificed, and the tumors were excised. Half of each tumor was subjected to an immunohistochemical assay (IHC) using a P-selectin antibody (Thermo Fisher Scientific, USA) to examine the relationship between P-selectin-expressing cells and Fu-NP uptake. For details of the IHC methodology, refer to the IHC section. The other half of the tumor was homogenized to obtain a single-cell suspension, which was then analyzed by flow cytometry to evaluate the uptake of Fu-NP-Qdot605 by different cell populations, including TAMs (CD45⁺/F4/80⁺ cells), cancer cells (CD45^–/CD31^– cells), and non-TAM leukocytes (CD45⁺/F4/80^– cells).

Binding Studies of Nanoparticles to Immobilized P-Selectin

Human recombinant P-selectin, E-selectin, or L-selectin (each at 50 ng, Thermo Fisher Scientific, USA) was added to high-hydrophobicity 96-well enzyme-linked immunosorbent assay (ELISA) plates and incubated at 4 °C overnight. The wells were washed with phosphate-buffered saline (PBS) containing 0.05% Tween-20 (PBST) three times and blocked with 3% BSA for 2 h at 37 °C. Then, the indicated dosage of Qdot605-labeled NPs was incubated within PBS for 15 min at room temperature (RT). The wells were gently washed three times with PBST. Fluorescence was measured using the SpectraMax iD3 (excitation: 560 nm; emission: 620 nm).

Immunohistochemistry and Generation of Protein Expression Values

Immunohistochemical staining against P-selectin was performed using a standard procedure. Briefly, sections of a tissue microarray (TMA) were prepared on the slide, deparaffinized in xylene, and rehydrated in graded concentrations of ethanol. Antigens were retrieved in 10 mM citrate buffer (pH 6.0, Dako, Denmark) for 5 min in a MicroMED T/T Mega microwave (Milestone, Italy). Endogenous peroxidase activity was blocked by incubating in 0.3% hydrogen peroxide in methanol. Primary P-selectin antibodies (Thermo Fisher Scientific, USA) were applied (overnight at 4 °C), followed by biotinylated secondary antibodies (1:200, 1 h at RT, Thermo Fisher Scientific) and an ABC kit (1 h at RT, Thermo Fisher Scientific) sequentially. Diaminobenzidine tetrahydrochloride (DAB, Thermo Fisher Scientific) was used as the enzyme substrate. Immunostained TMA slides were scanned by TissueFAXS Spectra (TissueGnostics GmbH, Austria) and converted into image files. Staining intensity of P-selectin and the area of positively stained cells were analyzed in the whole area of each spot by StrataQuest (Definiens AG, Germany). StrataQuest determined positive versus negative staining based on the colorimetric differences between stained and unstained subcellular locations (for example, positive P-selectin staining consisted of pixels with brown greater than blue). These algorithms then used grayscale (0–255) to quantitate the intensity of staining. Intensity grades were classified by StrataQuest as follows: grade 0, negative; 1, weak but detectable above control; 2, moderate; and 3, strong. For each observed TMA spot, a summary value referred to as the H-Score was calculated. The H-Score consists of a sum of the percentages of positively stained cells multiplied by the weighted intensity of staining.

Dual Cell-Targeting Affinity Test

MDA-MB-231 cells were irradiated with 2 Gy X-ray and labeled with DiO (Thermo Fisher Scientific, USA) to mark the membranes, while THP-1-derived M2 macrophages were labeled with DiO only. Both cell types were separately incubated with PVA-NP, Dex-NP, and Fu-NP, labeled with Qdot605, at a concentration of 100 μg mL^–1 for 30 min. Subsequently, the NP that were not taken up were washed away. The cells were then observed using flow cytometry or mounted with a DAPI mounting medium and observed using confocal microscopy.

Intracellular ROS Levels of Cancer Cells

For the in vitro assay, MDA-MB-231 cancer cells were treated with various NPs at a concentration of either 100 μg mL^–1 of DTX-free NPs or a particle quantity of NPs equivalent to the drug dosage used in the FINAL group for 24 h, followed by incubation with 10 μM 2′,7′-dichlorodihydrofluorescein diacetate (DCF-DA, Merck, Germany) for 30 min at 37 °C. For the in vivo assay, single-cell suspensions collected from 4T1 tumor cells were stained with 10 μM DCF-DA for 30 min at 37 °C. Upon oxidation of DCF-DA to fluorescent 2′,7′-dichlorofluorescein (DCF), the emitted fluorescence signal was quantified using an Attune NxT flow cytometer (Thermo Fisher Scientific, USA) with the BL1 emission channel, employing a 488 nm excitation wavelength to assess intracellular ROS levels.

Activation of Macrophage Polarization

THP-1 monocytes were induced with 100 ng mL^–1 phorbol 12-myristate 13-acetate (PMA, Merck Millipore, USA) for 48 h to differentiate into M0 macrophages. After a 24 h rest, they were polarized into M1 macrophages with IFN-γ (50 ng mL^–1, BioLegend, USA) or into M2 macrophages with IL-4 (20 ng mL^–1, BioLegend) for 24 h. The effect on M0 or M2 stage macrophages was evaluated after treatment with either 100 μg mL^–1 of DTX-free NPs or a particle quantity of NPs equivalent to the drug dosage used in the FINAL group for 24 h. Macrophage polarity was confirmed by mRNA expression levels of IL-1β, TNF-α, and CD206 using quantitative RT-PCR or by analyzing CD86 and CD206 protein levels.

Macrophage Polarization Detected by Quantitative Real-Time PCR

The polarity of THP-1-derived M0 macrophages was studied after NP treatment for 24 h. Cellular RNAs of the polarized macrophages were isolated in a TRIzol solution (Thermo Fisher Scientific, USA), treated with DNase I (Invitrogen, USA), and transcribed into cDNA by RevertAid reverse transcriptase (Thermo Fisher Scientific) according to the manufacturer’s instructions. Quantitative RT-PCR was conducted using SYBR Green Master Mix (Thermo Fisher Scientific), a cDNA template (50 ng), and the primers (Table S3). The quantitative RT-PCR reaction was performed at 95 °C for 15 min, followed by 40 cycles at 95 °C for 15 s and 60 °C for 1 min. The GAPDH expression level was used as an internal control. Relative mRNA levels were calculated by the formula: ΔΔCT = ΔCt test sample – ΔCt control sample. Fold changes in gene expression were calculated by using the 2^–ΔΔCT method.

Macrophage Polarization Detected by Immunocytochemistry Staining

The polarity of THP-1-derived M2 macrophages was studied after treatment with either 100 μg mL^–1 of DTX-free NPs or a particle quantity of NPs equivalent to the drug dosage used in the FINAL group for 24 h. The cells were washed with PBS and fixed with 4% paraformaldehyde (PFA) for 15 min at RT. Subsequently, fixed cells were treated with 0.1% Triton X-100 in PBS for 10 min at RT to permeabilize the cell membrane. After permeabilization, cells were incubated in blocking solution (5% bovine serum albumin in PBS) for 60 min at RT to reduce nonspecific binding. Primary antibodies against CD68 and CD206 (both from Thermo Fisher Scientific, USA) were diluted in blocking solution according to the manufacturer’s recommendations. Cells were then incubated with the primary antibodies overnight at 4 °C. Following the primary antibody incubation, secondary antibodies were diluted in blocking solution according to the manufacturer’s recommendations. Cells were incubated with the secondary antibodies for 1 h at RT, protected from light. Subsequently, the cells were mounted on a DAPI mounting medium. Stained cells were visualized by using a Zeiss LSM900 confocal microscope equipped with appropriate filter sets for the fluorophores used. Image analysis was performed using ZEN (Zeiss, Germany) software to quantify the fluorescence colocalization of signals.

Macrophage Polarization in a Transwell Mimicking TME

MDA-MB-231 cells were seeded with a 0.4 μm pore size membrane in the upper chamber of a transwell insert (Merck Millipore, USA), while THP-1-derived M0 macrophages were seeded in the lower chamber. Each group was treated with their respective NPs. After 24 h of coculture, macrophages from the lower chamber were harvested for qRT-PCR analysis to quantify the expression of CD206, indicative of macrophage polarization.

Macrophage Migration and Invasion Assay

For the migration assay, THP-1-derived M2 macrophages were loaded into a Transwell insert (Merck Millipore, USA) with an 8 μm pore size membrane in serum-free medium. The lower chamber was filled with MDA-MB-231-conditioned medium to stimulate macrophage migration. The Transwell plates were incubated at 37 °C in a humidified atmosphere with 5% CO2 for 24 h to allow for macrophage migration through the membrane. For the invasion assay, the upper side of the Transwell membrane was precoated with a layer of Matrigel (Thermo Fisher Scientific, USA) prior to seeding the macrophages. The setup was otherwise similar to the migration assay, and incubation was performed for 24 h to allow for invasion through the Matrigel layer.

After the incubation period, nonmigrated/invaded cells on the upper side of the membrane were gently removed using a cotton swab. Cells that had migrated/invaded to the lower side of the membrane were fixed with 4% paraformaldehyde for 10 min at RT. Fixed cells were stained with crystal violet (Thermo Fisher Scientific) to visualize and count the migrated/invaded cells. The stained membranes were imaged by using a light microscope. The number of migrated or invaded cells was quantified in multiple random fields per membrane by using image analysis software for automated counting.

RNA Sequencing

Tumor tissues were harvested from mice bearing 4T1 breast tumors that received DTX, PVA-NP, Fu-NP, DTX@PNP, and FINAL treatment in accordance with a Q4d×4 regimen and were sacrificed 28 days after tumor inoculation. Total RNA was extracted from tumor tissue using the PureLink RNA Mini Kit (Thermo Fisher Scientific, USA), following the manufacturer’s instructions. RNA quantity and integrity were assessed using a Bioanalyzer (Agilent Technologies, USA).

Sequencing libraries were prepared using the TruSeq Stranded Total RNA Sample Preparation Kit (Illumina, USA), and quality control was performed prior to sequencing. Libraries were sequenced on an Illumina HiSeq 2,000 platform to generate paired-end reads. Raw sequencing results were delivered as BAM files and converted to FASTQ format using Picard tools. FASTQ files were aligned to the mouse reference genome (mm10/GRCm38) using the STAR aligner (v2.5.2a) or TopHat2 (v2.0.14) as appropriate. Gene expression quantification was performed using featureCounts (v1.4.6), and differential gene expression analysis was performed using DESeq2.

Flow Cytometry Analyses

For surface marker staining, single-cell suspensions were stained with a mixture of 5 to 6 fluorophores including 7-Aminoactinomycin D (7-AAD, BioLegend, USA) for viability and were acquired on the Attune NxT flow cytometer with data analyzed using FlowJo software (BD Life Sciences, USA). Fc receptors were blocked with Fc-receptor-specific mAb (BD PharMingen, USA) before cell surface staining. Single-cell suspensions collected from tumor tissues, lungs, and peripheral blood were identified by using the following antibodies: CD45-BV510, F4/80-BV421, CD86-APC, CD206-BV711, and CD11b-PE (all from BioLegend). Isotype-matched mAbs served as negative controls to demonstrate specificity and to establish background staining levels.

For intracellular TNF-α detection, single-cell suspensions collected from tumor tissues and lungs were resuspended (1 × 10⁶ cells mL^–1) in complete medium (RPMI-1640 containing 10% FBS, sodium pyruvate (1 mM), penicillin (100 U mL^–1), streptomycin (100 μg mL^–1), and l-glutamine (2 mM), all purchased from Thermo Fisher Scientific, USA). 16 h before collecting the cells for staining, the protein transport inhibitor brefeldin A (10 μg mL^–1, BioLegend), along with phorbol 12-myristate 13-acetate (PMA, 20 ng mL^–1) and ionomycin (1 μg mL^–1), was added to the wells (all reagents from Merck Sigma-Aldrich, USA). After surface staining, cells were fixed and permeabilized with the Fixation/Permeabilization buffer (eBioscience, Thermo Fisher Scientific), according to the manufacturer’s instructions. Fixed/permeabilized cells were washed with 1× Permeabilization Buffer (eBioscience, Thermo Fisher Scientific) and stained with anti-TNF-α-BV711 mAb (BioLegend).

For intracellular VEGF-A and Luc detection, single-cell suspensions collected from tumor tissues and peripheral blood were resuspended for surface staining; then the cells were fixed and permeabilized using the same fixation/permeabilization procedure. The cells were stained with anti-VEGF-A-PE (BioLegend) and anti-Luc-FITC (Thermo Fisher Scientific). Fluorescence minus one controls were used to set accurate gates for the intracellular staining. Flow cytometric analysis was performed using an Attune NxT flow cytometer and Attune NxT software (both Thermo Fisher Scientific).

T-Distributed Stochastic Neighbor Embedding (tSNE)-Based Analysis

T-distributed stochastic neighbor embedding (tSNE) was analyzed by FlowJo and performed using default parameters (iterations = 500, perplexity = 50, and θ = 0.5). Samples were randomly downsampled to 2,000–5,000 events per sample. The range in events was determined by the sample with the fewest events acquired, and analysis was run on equal numbers of events per sample. Individual flow cytometry sample files were combined into a single flow cytometry standard file to assist in defining spatially distinct populations by using the concatenation tool.

Immunohistochemical (IHC) Assessment

Animals were euthanized with carbon dioxide, and their 4T1 tumors were extracted and then immersed in 4% paraformaldehyde. Tissue samples were dehydrated in a graded series of 20% and 30% sucrose solutions, frozen on dry ice, and then cut into a series of adjacent 10 μm-thick coronal sections using a cryostat. The frozen sections were fixed in cold 95% alcohol for 10 min and then air-dried. The sections were rehydrated in PBS and blocked with 5% BSA for 60 min at room temperature. Each section was immunostained with antibodies against P-selectin and α-SMA (both from Thermo Fisher Scientific, USA) overnight at 4 °C, followed by incubation with a 488-conjugated goat antimouse secondary antibody (1:500; Thermo Fisher Scientific) for 1 h at room temperature. The sections were sealed with a DAPI mounting medium (Dako, Denmark) and then analyzed by using a Zeiss LSM900 laser-scanning confocal microscope.

Cytokine Detection by Enzyme-Linked Immunosorbent Assay (ELISA)

Human TNF-α in the bronchoalveolar lavage fluid (BALF) was measured by ELISA in accordance with the manufacturer’s instructions (BioLegend, USA).

Apoptosis Analyses

Cells treated with 10 nM docetaxel-loaded NPs were analyzed for apoptosis using the Annexin V/7-AAD Apoptosis Detection Kit (BioLegend, USA) after 8 h of incubation, following the manufacturer’s protocol. In brief, cells were recovered from the cultures, washed twice with cold PBS and resuspended in binding buffer. Cells were labeled with Annexin V and 7-AAD for 15 min, then analyzed by the Attune NxT flow cytometer and Attune NxT software (both from Thermo Fisher Scientific).

Angiogenesis Analyses

To investigate the effects of NPs on the inhibition of angiogenic factors from M2 macrophages, the macrophages were initially treated with docetaxel-loaded NPs (equivalent DTX concentration at 10 nM) for 24 h, and the conditioned medium was collected and centrifuged. This conditioned medium was then used to treat HUVECs for an additional 24 h. Following trypsinization of HUVECs, the cells were seeded onto Matrigel, and tube formation capability was evaluated after 4 h.

In Vitro CHC Model

MDA-MB-231-GFP cells were subjected to serum starvation and incubated under hypoxic conditions (3% O₂) for 72 h to induce upregulation of P-selectin expression. For CHC formation assays, P-selectin^high MDA-MB-231-GFP cells were cocultured with THP-1-M1 cells in a 1:3 ratio for 24 h, maintaining at least 70% total cell viability. Various treatments were applied: DTX, DTX@PNP, and FINAL (each at 10 nM DTX), as well as DTX-free carriers (PVA-NP and Fu-NP) at particle numbers corresponding to the FINAL group. After treatment, hybrid cells were quantified by flow cytometry as GFP⁺/CD45⁺ events using specific gating strategies to distinguish fusion hybrids from parental cell populations.

To assess P-selectin–mediated adhesion interference, P-selectin^high MDA-MB-231-GFP cells were incubated with a fluoro-labeled anti–P-selectin antibody for 30 min in the presence or absence of PVA-NP or Fu-NP. The effect of fucoidan on antibody binding was evaluated by measuring mean fluorescence intensity, with decreased values indicating competitive inhibition of P-selectin binding.

Biodistribution

The biodistribution of different DTX formulations was monitored by using IVIS and liquid–liquid extraction methods. First, DTX@Dex-NP, DTX@PNP, and FINAL were labeled with DiR, and their biodistribution was monitored using IVIS. Mice were intravenously injected with DTX@Dex-NP, DTX@PNP, or FINAL at a dose of 10 mg kg^–1 DTX, imaged under IVIS at 24 h postadministration, and subsequently sacrificed. Organs were then collected, and fluorescence was semiquantified.

Second, the comparison of biodistribution between Taxotere and FINAL was performed by using liquid–liquid extraction followed by HPLC-TOF-MS quantification. Taxotere and FINAL were administered intravenously to 4T1 tumor-bearing mice at 10 mg kg^–1. At 24 h post administration, mice were sacrificed, and organs (heart, liver, lung, spleen, kidney) and tumors were collected and weighed. Tissue samples were homogenized using a Bullet Blender (Next Advance, Inc., USA) according to manufacturer’s protocol. Homogenates were centrifuged at 8,000 × g for 15 min at 4 °C. The supernatant (50 μL) was mixed with 200 μL of methyl tert-butyl ether (MTBE) under sonication for 15 min for DTX extraction. After centrifugation at 5,000 × g for 15 min at 4 °C, 30 μL of the solution was collected and vacuum-dried. Dried samples were reconstituted in 60% acetonitrile for HPLC-TOF-MS analysis (Waters). HPLC-TOF-MS analysis was performed using a C18 column (packing L1) with mobile phases consisting of water (A) and acetonitrile (B), both containing 1% formic acid. The column temperature was maintained at 40 °C with a flow rate of 0.3 mL min^–1. The mobile phase gradient (A:B) was programmed as follows: 0–0.3 min, A:B = 90%:10%; 1.6–2.7 min, A:B = 20%:80%; 3.0–3.5 min, A:B = 90%:10%. The gradient was programmed as follows: 0 min, 10% B; 0.3 min, 10% B; 1.6 min, 80% B; 2.7 min, 80% B; 3.0 min, 10% B; 3.5 min, 10% B.

In Vivo Safety Profile of FINAL

To evaluate the safety of FINAL, single-dose and repeated-dose toxicity studies were performed. For single-dose toxicity, FINAL was intravenously administered into ICR mice at a DTX dosage of 50, 100, or 200 mg per kg (body weight). At 14 days after the treatment, the tissues including bone marrow and sciatic nerve, which are vulnerable to DTX, were collected and observed through histological analysis.

The repeated dose toxicity was performed by intravenously administering FINAL into SD rats at a DTX dosage of 5 mg per kg (body weight) for Q4d×3. At 4, 14, and 28 days after the final injection, whole blood was collected for the analysis of serum chemistry and hematology. For serum chemistry, aspartate transaminase (AST), alanine transaminase (ALT), creatinine (CREA), blood urea nitrogen (BUN), albumin (ALB), and glucose (GLU) were detected using clinical chemical analytic equipment (Fujifilm Dri-Chem 3500s, Fujifilm, Japan). For hematology, whole blood was collected in Microvette 100 potassium-EDTA blood collection tubes (Sarstedt) and the white blood cell counts were measured using a hematology analyzer (ProCyte Dx, IDEXX, Norway).

Statistics and Reproducibility

All measurements in this study were performed in a blinded design. Statistical analysis was performed using GraphPad Prism software (La Jolla, USA), and data are represented as mean ± standard deviation (SD). Error bars represent the SD of three or more independent experiments. Two-tailed Student’s t-tests were used to evaluate the significance of mean differences between the control and the treated groups. Differences between groups were evaluated by one-way ANOVA with the Tukey’s multiple comparisons test unless otherwise noted. A P value < 0.05 was considered significant. All experiments in the Figures were repeated for at least three times, and the performed numbers were provided in the regarding Figure legends.

Supplementary Material

nn5c15120_si_001.pdf^{(4.9MB, pdf)}

Acknowledgments

We would like to thank the Medical Research Core Facilities Centre, Office of Research & Development at China Medical University (Taichung, Taiwan), and Ever Supreme Bio Technology for their technical support.

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsnano.5c15120.

Colloidal stability and surface fucoidan stability (Figure S1); encapsulation efficiency and drug loading content (Table S1); drug release profiles (Figure S2); flow cytometry gating strategies for TAM, non-TAM, and cancer cells (Figures S3, S10); P-selectin expression under radiation, hypoxia, and serum starvation (Figures S4 and S15); impact of nanoparticles on macrophage polarization and intracellular ROS (Figures S5–S8); in vivo dose screening and major organ histology (Figure S9); in vitro cytotoxicity and apoptosis induction (Figure S11); flow cytometry gating strategies for TAM (Figure S12); impact of nanoparticle size on tumor suppression (Figure S13); flow cytometry gating strategies for TAM (Figure S14); flow cytometry gating strategies for lung macrophages (Figures S16–S17); acute toxicity studies, serum biochemistry, and safety profiles (Figures S18 and S23); biodistribution and tumor targeting quantification (Figures S19–S20); histopathological evaluation of bone marrow and sciatic nerve (Figures S21–S22); histopathologic grading data (Table S2); hemolysis assay for blood compatibility (Figure S24); and RT-qPCR primer sequences (Table S3) (PDF)

◮.

S.-Y.C., L.-B.J., W.-C.S., and C.-S.C. contributed equally to this work.

This work was supported by the National Science and Technology Council (NSTC) of Taiwan (MOST 111-2823-8-039-002, NSTC 112-2823-8-039-003, NSTC 112-2321-B-039-008, NSTC 111-2314-B-039-009-MY3, NSTC 113-2124-M-039-005, NSTC 114-2124-M-039-002, and NSTC 114-2314-B-039-049-MY2), China Medical University (CMU111-N-03, CMU111-MF-56, CMU112-MF-105, CMU-113-MF-04, and CMU114-MF-05), the Cancer Biology and Precision Therapeutics Center, China Medical University from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan, and the Emerging Technology Application Program of the Central Taiwan Science Park (113RB06).

The authors declare no competing financial interest.

References

Qian B. Z., Pollard J. W.. Macrophage Diversity Enhances Tumor Progression and Metastasis. Cell. 2010;141:39–51. doi: 10.1016/j.cell.2010.03.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
Henze A. T., Mazzone M.. The Impact of Hypoxia on Tumor-Associated Macrophages. J. Clin. Invest. 2016;126:3672–3679. doi: 10.1172/JCI84427. [DOI] [PMC free article] [PubMed] [Google Scholar]
Roshanzamir F., Robinson J. L., Cook D., Karimi-Jafari M. H., Nielsen J.. Metastatic Triple Negative Breast Cancer Adapts Its Metabolism to Destination Tissues While Retaining Key Metabolic Signatures. Proc. Natl. Acad. Sci. U. S. A. 2022;119:e2205456119. doi: 10.1073/pnas.2205456119. [DOI] [PMC free article] [PubMed] [Google Scholar]
Adams D. L., Martin S. S., Alpaugh R. K., Charpentier M., Tsai S., Bergan R. C., Ogden I. M., Catalona W., Chumsri S., Tang C. M., Cristofanilli M.. Circulating Giant Macrophages as a Potential Biomarker of Solid Tumors. Proc. Natl. Acad. Sci. U. S. A. 2014;111:3514–3519. doi: 10.1073/pnas.1320198111. [DOI] [PMC free article] [PubMed] [Google Scholar]
Harouaka R. A., Zhou M. D., Yeh Y. T., Khan W. J., Das A., Liu X., Christ C. C., Dicker D. T., Baney T. S., Kaifi J. T., Belani C. P., Truica C. I., El-Deiry W. S., Allerton J. P., Zheng S. Y.. Flexible Micro Spring Array Device for High-Throughput Enrichment of Viable Circulating Tumor Cells. Clin. Chem. 2014;60:323–333. doi: 10.1373/clinchem.2013.206805. [DOI] [PubMed] [Google Scholar]
Shabo I., Midtbö K., Andersson H., Åkerlund E., Olsson H., Wegman P., Gunnarsson C., Lindström A.. Macrophage Traits in Cancer Cells Are Induced by Macrophage-Cancer Cell Fusion and Cannot Be Explained by Cellular Interaction. BMC Cancer. 2015;15:922. doi: 10.1186/s12885-015-1935-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
Duelli D. M., Padilla-Nash H. M., Berman D., Murphy K. M., Ried T., Lazebnik Y.. A Virus Causes Cancer by Inducing Massive Chromosomal Instability through Cell Fusion. Curr. Biol. 2007;17:431–437. doi: 10.1016/j.cub.2007.01.049. [DOI] [PubMed] [Google Scholar]
Pawelek J. M.. Cancer-Cell Fusion with Migratory Bone-Marrow-Derived Cells as an Explanation for Metastasis: New Therapeutic Paradigms. Future Oncol. 2008;4:449–452. doi: 10.2217/14796694.4.4.449. [DOI] [PubMed] [Google Scholar]
Adams D. L., Adams D. K., Alpaugh R. K., Cristofanilli M., Martin S. S., Chumsri S., Tang C. M., Marks J. R.. Circulating Cancer-Associated Macrophage-Like Cells Differentiate Malignant Breast Cancer and Benign Breast Conditions. Cancer Epidemiol., Biomarkers Prev. 2016;25:1037–1042. doi: 10.1158/1055-9965.EPI-15-1221. [DOI] [PMC free article] [PubMed] [Google Scholar]
Gironda D. J., Adams D. L., He J., Xu T., Gao H., Qiao Y., Komaki R., Reuben J. M., Liao Z., Blum-Murphy M.. et al. Cancer Associated Macrophage-Like Cells and Prognosis of Esophageal Cancer after Chemoradiation Therapy. J. Transl. Med. 2020;18:413. doi: 10.1186/s12967-020-02563-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
Walker B. S., Sutton T. L., Zarour L., Hunter J. G., Wood S. G., Tsikitis V. L., Herzig D. O., Lopez C. D., Chen E. Y., Mayo S. C., Wong M. H.. Circulating Hybrid Cells: A Novel Liquid Biomarker of Treatment Response in Gastrointestinal Cancers. Ann. Surg. Oncol. 2021;28:8567–8578. doi: 10.1245/s10434-021-10379-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
Henn T. E., Anderson A. N., Hollett Y. R., Sutton T. L., Walker B. S., Swain J. R., Sauer D. A., Clayburgh D. R., Wong M. H.. Circulating Hybrid Cells Predict Presence of Occult Nodal Metastases in Oral Cavity Carcinoma. Head Neck. 2021;43:2193–2201. doi: 10.1002/hed.26692. [DOI] [PMC free article] [PubMed] [Google Scholar]
Manjunath Y., Mitchem J. B., Suvilesh K. N., Avella D. M., Kimchi E. T., Staveley-O’Carroll K. F., Deroche C. B., Pantel K., Li G., Kaifi J. T.. Circulating Giant Tumor-Macrophage Fusion Cells Are Independent Prognosticators in Patients with NSCLC. J. Thorac. Oncol. 2020;15:1460–1471. doi: 10.1016/j.jtho.2020.04.034. [DOI] [PubMed] [Google Scholar]
Lustberg M. B., Balasubramanian P., Miller B., Garcia-Villa A., Deighan C., Wu Y., Carothers S., Berger M., Ramaswamy B., Macrae E. R.. et al. Heterogeneous Atypical Cell Populations Are Present in Blood of Metastatic Breast Cancer Patients. Breast Cancer Res. 2014;16:R23. doi: 10.1186/bcr3622. [DOI] [PMC free article] [PubMed] [Google Scholar]
Aguirre L. A., Montalbán-Hernández K., Avendaño-Ortiz J., Marín E., Lozano R., Toledano V., Sánchez-Maroto L., Terrón V., Valentín J., Pulido E.. et al. Tumor Stem Cells Fuse with Monocytes to Form Highly Invasive Tumor-Hybrid Cells. Oncoimmunology. 2020;9:1773204. doi: 10.1080/2162402X.2020.1773204. [DOI] [PMC free article] [PubMed] [Google Scholar]
Clawson G. A., Matters G. L., Xin P., McGovern C., Wafula E., DePamphilis C., Meckley M., Wong J., Stewart L., D’Jamoos C., Altman N., Imamura Kawasawa Y., Du Z., Honaas L., Abraham T.. “Stealth Dissemination” of Macrophage-Tumor Cell Fusions Cultured from Blood of Patients with Pancreatic Ductal Adenocarcinoma. PLoS One. 2017;12:e0184451. doi: 10.1371/journal.pone.0184451. [DOI] [PMC free article] [PubMed] [Google Scholar]
Clawson G. A., Matters G. L., Xin P., Imamura-Kawasawa Y., Du Z., Thiboutot D. M., Helm K. F., Neves R. I., Abraham T.. Macrophage-Tumor Cell Fusions from Peripheral Blood of Melanoma Patients. PLoS One. 2015;10:e0134320. doi: 10.1371/journal.pone.0134320. [DOI] [PMC free article] [PubMed] [Google Scholar]
Gast C. E., Silk A. D., Zarour L., Riegler L., Burkhart J. G., Gustafson K. T., Parappilly M. S., Roh-Johnson M., Goodman J. R., Olson B.. et al. Cell Fusion Potentiates Tumor Heterogeneity and Reveals Circulating Hybrid Cells That Correlate with Stage and Survival. Sci. Adv. 2018;4:eaat7828. doi: 10.1126/sciadv.aat7828. [DOI] [PMC free article] [PubMed] [Google Scholar]
Shamay Y., Elkabets M., Li H., Shah J., Brook S., Wang F., Adler K., Baut E., Scaltriti M., Jena P. V.. et al. P-Selectin Is a Nanotherapeutic Delivery Target in the Tumor Microenvironment. Sci. Transl. Med. 2016;8:345ra387. doi: 10.1126/scitranslmed.aaf7374. [DOI] [PMC free article] [PubMed] [Google Scholar]
Yeini E., Ofek P., Pozzi S., Albeck N., Ben-Shushan D., Tiram G., Golan S., Kleiner R., Sheinin R., Dangoor S. I.. et al. P-Selectin Axis Plays a Key Role in Microglia Immunophenotype and Glioblastoma Progression. Nat. Commun. 2021;12:1912. doi: 10.1038/s41467-021-22186-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
Tchernychev B., Furie B., Furie B. C.. Peritoneal Macrophages Express Both P-Selectin and Psgl-1. J. Cell Biol. 2003;163:1145–1155. doi: 10.1083/jcb.200310079. [DOI] [PMC free article] [PubMed] [Google Scholar]
Koshrovski-Michael S., Ajamil D. R., Dey P., Kleiner R., Tevet S., Epshtein Y., Green Buzhor M., Khoury R., Pozzi S., Shenbach-Koltin G.. et al. Two-in-One Nanoparticle Platform Induces a Strong Therapeutic Effect of Targeted Therapies in P-Selectin-Expressing Cancers. Sci. Adv. 2024;10:eadr4762. doi: 10.1126/sciadv.adr4762. [DOI] [PMC free article] [PubMed] [Google Scholar]
Hariri G., Zhang Y., Fu A., Han Z., Brechbiel M., Tantawy M. N., Peterson T. E., Mernaugh R., Hallahan D.. Radiation-Guided P-Selectin Antibody Targeted to Lung Cancer. Ann. Biomed. Eng. 2008;36:821–830. doi: 10.1007/s10439-008-9444-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wang H., Liang Y., Yin Y., Zhang J., Su W., White A. M., Jiang B., Xu J., Zhang Y., Stewart S.. et al. Carbon Nano-Onion-Mediated Dual Targeting of P-Selectin and P-Glycoprotein to Overcome Cancer Drug Resistance. Nat. Commun. 2021;12:312. doi: 10.1038/s41467-020-20588-0. [DOI] [PMC free article] [PubMed] [Google Scholar] [Retracted]
Bachelet L., Bertholon I., Lavigne D., Vassy R., Jandrot-Perrus M., Chaubet F., Letourneur D.. Affinity of Low Molecular Weight Fucoidan for P-Selectin Triggers Its Binding to Activated Human Platelets. Biochim. Biophys. Acta. 2009;1790:141–146. doi: 10.1016/j.bbagen.2008.10.008. [DOI] [PubMed] [Google Scholar]
Chen S., Zhao Y., Zhang Y., Zhang D.. Fucoidan Induces Cancer Cell Apoptosis by Modulating the Endoplasmic Reticulum Stress Cascades. PLoS One. 2014;9:e108157. doi: 10.1371/journal.pone.0108157. [DOI] [PMC free article] [PubMed] [Google Scholar]
Deng Z., Wu N., Suo Q., Wang J., Yue Y., Geng L., Zhang Q.. Fucoidan, as an Immunostimulator Promotes M1 Macrophage Differentiation and Enhances the Chemotherapeutic Sensitivity of Capecitabine in Colon Cancer. Int. J. Biol. Macromol. 2022;222:562–572. doi: 10.1016/j.ijbiomac.2022.09.201. [DOI] [PubMed] [Google Scholar]
Sun J., Sun J., Song B., Zhang L., Shao Q., Liu Y., Yuan D., Zhang Y., Qu X.. Fucoidan Inhibits CCL22 Production through NF-κB Pathway in M2 Macrophages: A Potential Therapeutic Strategy for Cancer. Sci. Rep. 2016;6:35855. doi: 10.1038/srep35855. [DOI] [PMC free article] [PubMed] [Google Scholar]
Gao X., Li A., Zhou C.. L-Arginine and L-Lysine Improve the Emulsifying and Dissolution Properties of Pale, Soft, Exudative-Like Chicken Myofibrillar Proteins by Modifying Their Conformations. Food Chem. 2025;463:141136. doi: 10.1016/j.foodchem.2024.141136. [DOI] [PubMed] [Google Scholar]
Wang L. M., Zhang Y. X., Yang Q., Li K., Ma W. C., Bai Y. H.. A Comparative Study on the Pse-Like Chicken Breast Meat Protein Isolate-Sunflower Oil Emulsion Stability, Rheological Properties and Gel Properties by Different Additions of L-Lysine. Food Chem. X. 2025;29:102684. doi: 10.1016/j.fochx.2025.102684. [DOI] [PMC free article] [PubMed] [Google Scholar]
Guo X., Gao F., Zhang Y., Peng Z., Jamali M. A.. Effect of L-Histidine and L-Lysine on the Properties of Oil-in-Water Emulsions Stabilized by Porcine Myofibrillar Proteins at Low/High Ionic Strength. LWT. 2021;141:110883. doi: 10.1016/j.lwt.2021.110883. [DOI] [Google Scholar]
Tcholakova S., Denkov N. D., Danner T.. Role of Surfactant Type and Concentration for the Mean Drop Size During Emulsification in Turbulent Flow. Langmuir. 2004;20:7444–7458. doi: 10.1021/la049335a. [DOI] [PubMed] [Google Scholar]
Pulaski B. A., Ostrand-Rosenberg S.. Mouse 4T1 Breast Tumor Model. Curr. Protoc. Immunol. 2001;20:20.2. doi: 10.1002/0471142735.im2002s39. [DOI] [PubMed] [Google Scholar]
Boutilier A. J., Elsawa S. F.. Macrophage Polarization States in the Tumor Microenvironment. Int. J. Mol. Sci. 2021;22:6995. doi: 10.3390/ijms22136995. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zhang Y., Choksi S., Chen K., Pobezinskaya Y., Linnoila I., Liu Z. G.. ROS Play a Critical Role in the Differentiation of Alternatively Activated Macrophages and the Occurrence of Tumor-Associated Macrophages. Cell Res. 2013;23:898–914. doi: 10.1038/cr.2013.75. [DOI] [PMC free article] [PubMed] [Google Scholar]
Chen L. M., Tseng H. Y., Chen Y. A., Al Haq A. T., Hwang P. A., Hsu H. L.. Oligo-Fucoidan Prevents M2 Macrophage Differentiation and HCT116 Tumor Progression. Cancers. 2020;12:421. doi: 10.3390/cancers12020421. [DOI] [PMC free article] [PubMed] [Google Scholar]
Li P., Wang H., Shao Q., Kong B., Qu X.. Fucoidan Modulates Cytokine Production and Migration of THP-1-Derived Macrophages Via Colony-Stimulating Factor-1. Mol. Med. Rep. 2017;15:2325–2332. doi: 10.3892/mmr.2017.6228. [DOI] [PubMed] [Google Scholar]
Jeong J.-W., Hwang S. J., Han M. H., Lee D.-S., Yoo J. S., Choi I.-W., Cha H.-J., Kim S., Kim H.-S., Kim G.-Y., Jeon Y.-J., Lee H.-J., Park H. T., Yoo Y. H., Choi Y. H.. Fucoidan Inhibits Lipopolysaccharide-Induced Inflammatory Responses in RAW 264.7 Macrophages and Zebrafish Larvae. Mol. Cell. Toxicol. 2017;13:405–417. doi: 10.1007/s13273-017-0045-2. [DOI] [Google Scholar]
Wang C., Guo J., Wu Z.. Combinative Treatment of Curdione and Docetaxel Triggers Reactive Oxygen Species (Ros)-Mediated Intrinsic Apoptosis of Triple-Negative Breast Cancer Cells. Bioengineered. 2021;12:10037–10048. doi: 10.1080/21655979.2021.1994737. [DOI] [PMC free article] [PubMed] [Google Scholar]
Qiu S. Q., Waaijer S. J. H., Zwager M. C., de Vries E. G. E., van der Vegt B., Schröder C. P.. Tumor-Associated Macrophages in Breast Cancer: Innocent Bystander or Important Player? Cancer Treat Rev. 2018;70:178–189. doi: 10.1016/j.ctrv.2018.08.010. [DOI] [PubMed] [Google Scholar]
Hsu W. J., Lin M. H., Kuo T. C., Chou C. M., Mi F. L., Cheng C. H., Lin C. W.. Fucoidan from Laminaria Japonica Exerts Antitumor Effects on Angiogenesis and Micrometastasis in Triple-Negative Breast Cancer Cells. Int. J. Biol. Macromol. 2020;149:600–608. doi: 10.1016/j.ijbiomac.2020.01.256. [DOI] [PubMed] [Google Scholar]
Bae H., Lee J. Y., Yang C., Song G., Lim W.. Fucoidan Derived from Fucus Vesiculosus Inhibits the Development of Human Ovarian Cancer Via the Disturbance of Calcium Homeostasis, Endoplasmic Reticulum Stress, and Angiogenesis. Mar. Drugs. 2020;18:45. doi: 10.3390/md18010045. [DOI] [PMC free article] [PubMed] [Google Scholar]
Chen X., Sun L., Wei X., Lu H., Tan Y., Sun Z., Jiang J.. Antitumor Effect and Molecular Mechanism of Fucoidan in NSCLC. BMC Complement. Med. Ther. 2021;21:25. doi: 10.1186/s12906-020-03191-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sabe H., Yahara Y., Ishii M.. Cell Fusion Dynamics: Mechanisms of Multinucleation in Osteoclasts and Macrophages. Inflamm. Regen. 2024;44:49. doi: 10.1186/s41232-024-00360-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
Olbromski M., Mrozowska M., Piotrowska A., Smolarz B., Romanowicz H.. The VISTA/VSIG3/PSGL-1Axis: Crosstalk between Immune Effector Cells and Cancer Cells in Invasive Ductal Breast Carcinoma. Cancer Immunol., Immunother. 2024;73:136. doi: 10.1007/s00262-024-03701-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lin Y., Huang S., Qi Y., Xie L., Jiang J., Li H., Chen Z.. PSGL-1 Is a Novel Tumor Microenvironment Prognostic Biomarker with Cervical High-Grade Squamous Lesions and More. Front. Oncol. 2023;13:1052201. doi: 10.3389/fonc.2023.1052201. [DOI] [PMC free article] [PubMed] [Google Scholar]
Carroll M. J., Fogg K. C., Patel H. A., Krause H. B., Mancha A. S., Patankar M. S., Weisman P. S., Barroilhet L., Kreeger P. K.. Alternatively-Activated Macrophages Upregulate Mesothelial Expression of P-Selectin to Enhance Adhesion of Ovarian Cancer Cells. Cancer Res. 2018;78:3560–3573. doi: 10.1158/0008-5472.CAN-17-3341. [DOI] [PMC free article] [PubMed] [Google Scholar]
Sharma S. K., Chintala N. K., Vadrevu S. K., Patel J., Karbowniczek M., Markiewski M. M.. Pulmonary Alveolar Macrophages Contribute to the Premetastatic Niche by Suppressing Antitumor T Cell Responses in the Lungs. J. Immunol. 2015;194:5529–5538. doi: 10.4049/jimmunol.1403215. [DOI] [PubMed] [Google Scholar]
Qian B., Deng Y., Im J. H., Muschel R. J., Zou Y., Li J., Lang R. A., Pollard J. W.. A Distinct Macrophage Population Mediates Metastatic Breast Cancer Cell Extravasation, Establishment and Growth. PLoS One. 2009;4:e6562. doi: 10.1371/journal.pone.0006562. [DOI] [PMC free article] [PubMed] [Google Scholar]
Divangahi M., King I. L., Pernet E.. Alveolar Macrophages and Type I IFN in Airway Homeostasis and Immunity. Trends Immunol. 2015;36:307–314. doi: 10.1016/j.it.2015.03.005. [DOI] [PubMed] [Google Scholar]
Chang C.-Y., Armstrong D., Corry D. B., Kheradmand F.. Alveolar Macrophages in Lung Cancer: Opportunities Challenges. Front. Immunol. 2023;14:1268939. doi: 10.3389/fimmu.2023.1268939. [DOI] [PMC free article] [PubMed] [Google Scholar]
Tapmeier T. T., Howell J. H., Zhao L., Papiez B. W., Schnabel J. A., Muschel R. J., Gal A.. Evolving Polarisation of Infiltrating and Alveolar Macrophages in the Lung During Metastatic Progression of Melanoma Suggests CCR1 as a Therapeutic Target. Oncogene. 2022;41:5032–5045. doi: 10.1038/s41388-022-02488-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
Cho H. J., Jung J. I., Lim D. Y., Kwon G. T., Her S., Park J. H., Park J. H. Y.. Bone Marrow-Derived, Alternatively Activated Macrophages Enhance Solid Tumor Growth and Lung Metastasis of Mammary Carcinoma Cells in a BALB/c Mouse Orthotopic Model. Breast Cancer Res. 2012;14:R81. doi: 10.1186/bcr3195. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lai Y. H., Chiang C. S., Hsu C. H., Cheng H. W., Chen S. Y.. Development and Characterization of a Fucoidan-Based Drug Delivery System by Using Hydrophilic Anticancer Polysaccharides to Simultaneously Deliver Hydrophobic Anticancer Drugs. Biomolecules. 2020;10:970. doi: 10.3390/biom10070970. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kulhari H., Pooja D., Shrivastava S., Kuncha M., Naidu V. G. M., Bansal V., Sistla R., Adams D. J.. Trastuzumab-Grafted Pamam Dendrimers for the Selective Delivery of Anticancer Drugs to Her2-Positive Breast Cancer. Sci. Rep. 2016;6:23179. doi: 10.1038/srep23179. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kruh G. D.. Ins and Outs of Taxanes. Cancer Biol. Ther. 2005;4:1030–1032. doi: 10.4161/cbt.4.9.2052. [DOI] [PubMed] [Google Scholar]
Hernández-Vargas H., Palacios J., Moreno-Bueno G.. Molecular Profiling of Docetaxel Cytotoxicity in Breast Cancer Cells: Uncoupling of Aberrant Mitosis and Apoptosis. Oncogene. 2007;26:2902–2913. doi: 10.1038/sj.onc.1210102. [DOI] [PubMed] [Google Scholar]
Haggerty T. J., Dunn I. S., Rose L. B., Newton E. E., Martin S., Riley J. L., Kurnick J. T.. Topoisomerase Inhibitors Modulate Expression of Melanocytic Antigens and Enhance T Cell Recognition of Tumor Cells. Cancer Immunol., Immunother. 2011;60:133–144. doi: 10.1007/s00262-010-0926-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
Chan O. T., Yang L. X.. The Immunological Effects of Taxanes. Cancer Immunol., Immunother. 2000;49:181–185. doi: 10.1007/s002620000122. [DOI] [PMC free article] [PubMed] [Google Scholar]
Garnett C. T., Schlom J., Hodge J. W.. Combination of Docetaxel and Recombinant Vaccine Enhances T-Cell Responses and Antitumor Activity: Effects of Docetaxel on Immune Enhancement. Clin. Cancer Res. 2008;14:3536–3544. doi: 10.1158/1078-0432.CCR-07-4025. [DOI] [PMC free article] [PubMed] [Google Scholar]
Millrud C. R., Mehmeti M., Leandersson K.. Docetaxel Promotes the Generation of Anti-Tumorigenic Human Macrophages. Exp. Cell Res. 2018;362:525–531. doi: 10.1016/j.yexcr.2017.12.018. [DOI] [PubMed] [Google Scholar]
Ma S., Feng X., Liu F., Wang B., Zhang H., Niu X.. The Pro-Inflammatory Response of Macrophages Regulated by Acid Degradation Products of Poly(lactide-co-glycolide) Nanoparticles. Eng. Life Sci. 2021;21:709–720. doi: 10.1002/elsc.202100040. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bissery M.-C., Guénard D., Guéritte-Voegelein F., Lavelle F.. Experimental Antitumor Activity of Taxotere (Rp 56976, Nsc 628503), a Taxol Analogue. Cancer Res. 1991;51:4845–4852. [PubMed] [Google Scholar]
Ryu M. J., Chung H. S.. Fucoidan Reduces Oxidative Stress by Regulating the Gene Expression of HO-1 and SOD-1 through the Nrf2/ERK Signaling Pathway in HaCat Cells. Mol. Med. Rep. 2016;14:3255–3260. doi: 10.3892/mmr.2016.5623. [DOI] [PubMed] [Google Scholar]
Hsu H.-Y., Lin T.-Y., Lu M.-K., Leng P.-J., Tsao S.-M., Wu Y.-C.. Fucoidan Induces Toll-Like Receptor 4-Regulated Reactive Oxygen Species and Promotes Endoplasmic Reticulum Stress-Mediated Apoptosis in Lung Cancer. Sci. Rep. 2017;7:44990. doi: 10.1038/srep44990. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zhang Z., Teruya K., Eto H., Shirahata S.. Fucoidan Extract Induces Apoptosis in MCF-7 Cells Via a Mechanism Involving the ROS-Dependent JNK Activation and Mitochondria-Mediated Pathways. PLoS One. 2011;6:e27441. doi: 10.1371/journal.pone.0027441. [DOI] [PMC free article] [PubMed] [Google Scholar]
Yang L., Wang P., Wang H., Li Q., Teng H., Liu Z., Yang W., Hou L., Zou X.. Fucoidan Derived from Undaria Pinnatifida Induces Apoptosis in Human Hepatocellular Carcinoma SMMC-7721 Cells Via the ROS-Mediated Mitochondrial Pathway. Mar. Drugs. 2013;11:1961–1976. doi: 10.3390/md11061961. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kong D. S., Song S. Y., Kim D. H., Joo K. M., Yoo J. S., Koh J. S., Dong S. M., Suh Y. L., Lee J. I., Park K., Kim J. H., Nam D. H.. Prognostic Significance of c-Met Expression in Glioblastomas. Cancer. 2009;115:140–148. doi: 10.1002/cncr.23972. [DOI] [PubMed] [Google Scholar]
Jung Y., Joo K. M., Seong D. H., Choi Y. L., Kong D. S., Kim Y., Kim M. H., Jin J., Suh Y. L., Seol H. J., Shin C. S., Lee J. I., Kim J. H., Song S. Y., Nam D. H.. Identification of Prognostic Biomarkers for Glioblastomas Using Protein Expression Profiling. Int. J. Oncol. 2012;40:1122–1132. doi: 10.3892/ijo.2011.1302. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

nn5c15120_si_001.pdf^{(4.9MB, pdf)}

[ref1] Qian B. Z., Pollard J. W.. Macrophage Diversity Enhances Tumor Progression and Metastasis. Cell. 2010;141:39–51. doi: 10.1016/j.cell.2010.03.014. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref2] Henze A. T., Mazzone M.. The Impact of Hypoxia on Tumor-Associated Macrophages. J. Clin. Invest. 2016;126:3672–3679. doi: 10.1172/JCI84427. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref3] Roshanzamir F., Robinson J. L., Cook D., Karimi-Jafari M. H., Nielsen J.. Metastatic Triple Negative Breast Cancer Adapts Its Metabolism to Destination Tissues While Retaining Key Metabolic Signatures. Proc. Natl. Acad. Sci. U. S. A. 2022;119:e2205456119. doi: 10.1073/pnas.2205456119. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref4] Adams D. L., Martin S. S., Alpaugh R. K., Charpentier M., Tsai S., Bergan R. C., Ogden I. M., Catalona W., Chumsri S., Tang C. M., Cristofanilli M.. Circulating Giant Macrophages as a Potential Biomarker of Solid Tumors. Proc. Natl. Acad. Sci. U. S. A. 2014;111:3514–3519. doi: 10.1073/pnas.1320198111. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref5] Harouaka R. A., Zhou M. D., Yeh Y. T., Khan W. J., Das A., Liu X., Christ C. C., Dicker D. T., Baney T. S., Kaifi J. T., Belani C. P., Truica C. I., El-Deiry W. S., Allerton J. P., Zheng S. Y.. Flexible Micro Spring Array Device for High-Throughput Enrichment of Viable Circulating Tumor Cells. Clin. Chem. 2014;60:323–333. doi: 10.1373/clinchem.2013.206805. [DOI] [PubMed] [Google Scholar]

[ref6] Shabo I., Midtbö K., Andersson H., Åkerlund E., Olsson H., Wegman P., Gunnarsson C., Lindström A.. Macrophage Traits in Cancer Cells Are Induced by Macrophage-Cancer Cell Fusion and Cannot Be Explained by Cellular Interaction. BMC Cancer. 2015;15:922. doi: 10.1186/s12885-015-1935-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref7] Duelli D. M., Padilla-Nash H. M., Berman D., Murphy K. M., Ried T., Lazebnik Y.. A Virus Causes Cancer by Inducing Massive Chromosomal Instability through Cell Fusion. Curr. Biol. 2007;17:431–437. doi: 10.1016/j.cub.2007.01.049. [DOI] [PubMed] [Google Scholar]

[ref8] Pawelek J. M.. Cancer-Cell Fusion with Migratory Bone-Marrow-Derived Cells as an Explanation for Metastasis: New Therapeutic Paradigms. Future Oncol. 2008;4:449–452. doi: 10.2217/14796694.4.4.449. [DOI] [PubMed] [Google Scholar]

[ref9] Adams D. L., Adams D. K., Alpaugh R. K., Cristofanilli M., Martin S. S., Chumsri S., Tang C. M., Marks J. R.. Circulating Cancer-Associated Macrophage-Like Cells Differentiate Malignant Breast Cancer and Benign Breast Conditions. Cancer Epidemiol., Biomarkers Prev. 2016;25:1037–1042. doi: 10.1158/1055-9965.EPI-15-1221. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref10] Gironda D. J., Adams D. L., He J., Xu T., Gao H., Qiao Y., Komaki R., Reuben J. M., Liao Z., Blum-Murphy M.. et al. Cancer Associated Macrophage-Like Cells and Prognosis of Esophageal Cancer after Chemoradiation Therapy. J. Transl. Med. 2020;18:413. doi: 10.1186/s12967-020-02563-x. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref11] Walker B. S., Sutton T. L., Zarour L., Hunter J. G., Wood S. G., Tsikitis V. L., Herzig D. O., Lopez C. D., Chen E. Y., Mayo S. C., Wong M. H.. Circulating Hybrid Cells: A Novel Liquid Biomarker of Treatment Response in Gastrointestinal Cancers. Ann. Surg. Oncol. 2021;28:8567–8578. doi: 10.1245/s10434-021-10379-2. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref12] Henn T. E., Anderson A. N., Hollett Y. R., Sutton T. L., Walker B. S., Swain J. R., Sauer D. A., Clayburgh D. R., Wong M. H.. Circulating Hybrid Cells Predict Presence of Occult Nodal Metastases in Oral Cavity Carcinoma. Head Neck. 2021;43:2193–2201. doi: 10.1002/hed.26692. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref13] Manjunath Y., Mitchem J. B., Suvilesh K. N., Avella D. M., Kimchi E. T., Staveley-O’Carroll K. F., Deroche C. B., Pantel K., Li G., Kaifi J. T.. Circulating Giant Tumor-Macrophage Fusion Cells Are Independent Prognosticators in Patients with NSCLC. J. Thorac. Oncol. 2020;15:1460–1471. doi: 10.1016/j.jtho.2020.04.034. [DOI] [PubMed] [Google Scholar]

[ref14] Lustberg M. B., Balasubramanian P., Miller B., Garcia-Villa A., Deighan C., Wu Y., Carothers S., Berger M., Ramaswamy B., Macrae E. R.. et al. Heterogeneous Atypical Cell Populations Are Present in Blood of Metastatic Breast Cancer Patients. Breast Cancer Res. 2014;16:R23. doi: 10.1186/bcr3622. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref15] Aguirre L. A., Montalbán-Hernández K., Avendaño-Ortiz J., Marín E., Lozano R., Toledano V., Sánchez-Maroto L., Terrón V., Valentín J., Pulido E.. et al. Tumor Stem Cells Fuse with Monocytes to Form Highly Invasive Tumor-Hybrid Cells. Oncoimmunology. 2020;9:1773204. doi: 10.1080/2162402X.2020.1773204. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref16] Clawson G. A., Matters G. L., Xin P., McGovern C., Wafula E., DePamphilis C., Meckley M., Wong J., Stewart L., D’Jamoos C., Altman N., Imamura Kawasawa Y., Du Z., Honaas L., Abraham T.. “Stealth Dissemination” of Macrophage-Tumor Cell Fusions Cultured from Blood of Patients with Pancreatic Ductal Adenocarcinoma. PLoS One. 2017;12:e0184451. doi: 10.1371/journal.pone.0184451. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref17] Clawson G. A., Matters G. L., Xin P., Imamura-Kawasawa Y., Du Z., Thiboutot D. M., Helm K. F., Neves R. I., Abraham T.. Macrophage-Tumor Cell Fusions from Peripheral Blood of Melanoma Patients. PLoS One. 2015;10:e0134320. doi: 10.1371/journal.pone.0134320. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref18] Gast C. E., Silk A. D., Zarour L., Riegler L., Burkhart J. G., Gustafson K. T., Parappilly M. S., Roh-Johnson M., Goodman J. R., Olson B.. et al. Cell Fusion Potentiates Tumor Heterogeneity and Reveals Circulating Hybrid Cells That Correlate with Stage and Survival. Sci. Adv. 2018;4:eaat7828. doi: 10.1126/sciadv.aat7828. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref19] Shamay Y., Elkabets M., Li H., Shah J., Brook S., Wang F., Adler K., Baut E., Scaltriti M., Jena P. V.. et al. P-Selectin Is a Nanotherapeutic Delivery Target in the Tumor Microenvironment. Sci. Transl. Med. 2016;8:345ra387. doi: 10.1126/scitranslmed.aaf7374. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref20] Yeini E., Ofek P., Pozzi S., Albeck N., Ben-Shushan D., Tiram G., Golan S., Kleiner R., Sheinin R., Dangoor S. I.. et al. P-Selectin Axis Plays a Key Role in Microglia Immunophenotype and Glioblastoma Progression. Nat. Commun. 2021;12:1912. doi: 10.1038/s41467-021-22186-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref21] Tchernychev B., Furie B., Furie B. C.. Peritoneal Macrophages Express Both P-Selectin and Psgl-1. J. Cell Biol. 2003;163:1145–1155. doi: 10.1083/jcb.200310079. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref22] Koshrovski-Michael S., Ajamil D. R., Dey P., Kleiner R., Tevet S., Epshtein Y., Green Buzhor M., Khoury R., Pozzi S., Shenbach-Koltin G.. et al. Two-in-One Nanoparticle Platform Induces a Strong Therapeutic Effect of Targeted Therapies in P-Selectin-Expressing Cancers. Sci. Adv. 2024;10:eadr4762. doi: 10.1126/sciadv.adr4762. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref23] Hariri G., Zhang Y., Fu A., Han Z., Brechbiel M., Tantawy M. N., Peterson T. E., Mernaugh R., Hallahan D.. Radiation-Guided P-Selectin Antibody Targeted to Lung Cancer. Ann. Biomed. Eng. 2008;36:821–830. doi: 10.1007/s10439-008-9444-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref24] Wang H., Liang Y., Yin Y., Zhang J., Su W., White A. M., Jiang B., Xu J., Zhang Y., Stewart S.. et al. Carbon Nano-Onion-Mediated Dual Targeting of P-Selectin and P-Glycoprotein to Overcome Cancer Drug Resistance. Nat. Commun. 2021;12:312. doi: 10.1038/s41467-020-20588-0. [DOI] [PMC free article] [PubMed] [Google Scholar] [Retracted]

[ref25] Bachelet L., Bertholon I., Lavigne D., Vassy R., Jandrot-Perrus M., Chaubet F., Letourneur D.. Affinity of Low Molecular Weight Fucoidan for P-Selectin Triggers Its Binding to Activated Human Platelets. Biochim. Biophys. Acta. 2009;1790:141–146. doi: 10.1016/j.bbagen.2008.10.008. [DOI] [PubMed] [Google Scholar]

[ref26] Chen S., Zhao Y., Zhang Y., Zhang D.. Fucoidan Induces Cancer Cell Apoptosis by Modulating the Endoplasmic Reticulum Stress Cascades. PLoS One. 2014;9:e108157. doi: 10.1371/journal.pone.0108157. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref27] Deng Z., Wu N., Suo Q., Wang J., Yue Y., Geng L., Zhang Q.. Fucoidan, as an Immunostimulator Promotes M1 Macrophage Differentiation and Enhances the Chemotherapeutic Sensitivity of Capecitabine in Colon Cancer. Int. J. Biol. Macromol. 2022;222:562–572. doi: 10.1016/j.ijbiomac.2022.09.201. [DOI] [PubMed] [Google Scholar]

[ref28] Sun J., Sun J., Song B., Zhang L., Shao Q., Liu Y., Yuan D., Zhang Y., Qu X.. Fucoidan Inhibits CCL22 Production through NF-κB Pathway in M2 Macrophages: A Potential Therapeutic Strategy for Cancer. Sci. Rep. 2016;6:35855. doi: 10.1038/srep35855. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref29] Gao X., Li A., Zhou C.. L-Arginine and L-Lysine Improve the Emulsifying and Dissolution Properties of Pale, Soft, Exudative-Like Chicken Myofibrillar Proteins by Modifying Their Conformations. Food Chem. 2025;463:141136. doi: 10.1016/j.foodchem.2024.141136. [DOI] [PubMed] [Google Scholar]

[ref30] Wang L. M., Zhang Y. X., Yang Q., Li K., Ma W. C., Bai Y. H.. A Comparative Study on the Pse-Like Chicken Breast Meat Protein Isolate-Sunflower Oil Emulsion Stability, Rheological Properties and Gel Properties by Different Additions of L-Lysine. Food Chem. X. 2025;29:102684. doi: 10.1016/j.fochx.2025.102684. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref31] Guo X., Gao F., Zhang Y., Peng Z., Jamali M. A.. Effect of L-Histidine and L-Lysine on the Properties of Oil-in-Water Emulsions Stabilized by Porcine Myofibrillar Proteins at Low/High Ionic Strength. LWT. 2021;141:110883. doi: 10.1016/j.lwt.2021.110883. [DOI] [Google Scholar]

[ref32] Tcholakova S., Denkov N. D., Danner T.. Role of Surfactant Type and Concentration for the Mean Drop Size During Emulsification in Turbulent Flow. Langmuir. 2004;20:7444–7458. doi: 10.1021/la049335a. [DOI] [PubMed] [Google Scholar]

[ref33] Pulaski B. A., Ostrand-Rosenberg S.. Mouse 4T1 Breast Tumor Model. Curr. Protoc. Immunol. 2001;20:20.2. doi: 10.1002/0471142735.im2002s39. [DOI] [PubMed] [Google Scholar]

[ref34] Boutilier A. J., Elsawa S. F.. Macrophage Polarization States in the Tumor Microenvironment. Int. J. Mol. Sci. 2021;22:6995. doi: 10.3390/ijms22136995. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref35] Zhang Y., Choksi S., Chen K., Pobezinskaya Y., Linnoila I., Liu Z. G.. ROS Play a Critical Role in the Differentiation of Alternatively Activated Macrophages and the Occurrence of Tumor-Associated Macrophages. Cell Res. 2013;23:898–914. doi: 10.1038/cr.2013.75. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref36] Chen L. M., Tseng H. Y., Chen Y. A., Al Haq A. T., Hwang P. A., Hsu H. L.. Oligo-Fucoidan Prevents M2 Macrophage Differentiation and HCT116 Tumor Progression. Cancers. 2020;12:421. doi: 10.3390/cancers12020421. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref37] Li P., Wang H., Shao Q., Kong B., Qu X.. Fucoidan Modulates Cytokine Production and Migration of THP-1-Derived Macrophages Via Colony-Stimulating Factor-1. Mol. Med. Rep. 2017;15:2325–2332. doi: 10.3892/mmr.2017.6228. [DOI] [PubMed] [Google Scholar]

[ref38] Jeong J.-W., Hwang S. J., Han M. H., Lee D.-S., Yoo J. S., Choi I.-W., Cha H.-J., Kim S., Kim H.-S., Kim G.-Y., Jeon Y.-J., Lee H.-J., Park H. T., Yoo Y. H., Choi Y. H.. Fucoidan Inhibits Lipopolysaccharide-Induced Inflammatory Responses in RAW 264.7 Macrophages and Zebrafish Larvae. Mol. Cell. Toxicol. 2017;13:405–417. doi: 10.1007/s13273-017-0045-2. [DOI] [Google Scholar]

[ref39] Wang C., Guo J., Wu Z.. Combinative Treatment of Curdione and Docetaxel Triggers Reactive Oxygen Species (Ros)-Mediated Intrinsic Apoptosis of Triple-Negative Breast Cancer Cells. Bioengineered. 2021;12:10037–10048. doi: 10.1080/21655979.2021.1994737. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref40] Qiu S. Q., Waaijer S. J. H., Zwager M. C., de Vries E. G. E., van der Vegt B., Schröder C. P.. Tumor-Associated Macrophages in Breast Cancer: Innocent Bystander or Important Player? Cancer Treat Rev. 2018;70:178–189. doi: 10.1016/j.ctrv.2018.08.010. [DOI] [PubMed] [Google Scholar]

[ref41] Hsu W. J., Lin M. H., Kuo T. C., Chou C. M., Mi F. L., Cheng C. H., Lin C. W.. Fucoidan from Laminaria Japonica Exerts Antitumor Effects on Angiogenesis and Micrometastasis in Triple-Negative Breast Cancer Cells. Int. J. Biol. Macromol. 2020;149:600–608. doi: 10.1016/j.ijbiomac.2020.01.256. [DOI] [PubMed] [Google Scholar]

[ref42] Bae H., Lee J. Y., Yang C., Song G., Lim W.. Fucoidan Derived from Fucus Vesiculosus Inhibits the Development of Human Ovarian Cancer Via the Disturbance of Calcium Homeostasis, Endoplasmic Reticulum Stress, and Angiogenesis. Mar. Drugs. 2020;18:45. doi: 10.3390/md18010045. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref43] Chen X., Sun L., Wei X., Lu H., Tan Y., Sun Z., Jiang J.. Antitumor Effect and Molecular Mechanism of Fucoidan in NSCLC. BMC Complement. Med. Ther. 2021;21:25. doi: 10.1186/s12906-020-03191-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref44] Sabe H., Yahara Y., Ishii M.. Cell Fusion Dynamics: Mechanisms of Multinucleation in Osteoclasts and Macrophages. Inflamm. Regen. 2024;44:49. doi: 10.1186/s41232-024-00360-3. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref45] Olbromski M., Mrozowska M., Piotrowska A., Smolarz B., Romanowicz H.. The VISTA/VSIG3/PSGL-1Axis: Crosstalk between Immune Effector Cells and Cancer Cells in Invasive Ductal Breast Carcinoma. Cancer Immunol., Immunother. 2024;73:136. doi: 10.1007/s00262-024-03701-w. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref46] Lin Y., Huang S., Qi Y., Xie L., Jiang J., Li H., Chen Z.. PSGL-1 Is a Novel Tumor Microenvironment Prognostic Biomarker with Cervical High-Grade Squamous Lesions and More. Front. Oncol. 2023;13:1052201. doi: 10.3389/fonc.2023.1052201. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref47] Carroll M. J., Fogg K. C., Patel H. A., Krause H. B., Mancha A. S., Patankar M. S., Weisman P. S., Barroilhet L., Kreeger P. K.. Alternatively-Activated Macrophages Upregulate Mesothelial Expression of P-Selectin to Enhance Adhesion of Ovarian Cancer Cells. Cancer Res. 2018;78:3560–3573. doi: 10.1158/0008-5472.CAN-17-3341. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref48] Sharma S. K., Chintala N. K., Vadrevu S. K., Patel J., Karbowniczek M., Markiewski M. M.. Pulmonary Alveolar Macrophages Contribute to the Premetastatic Niche by Suppressing Antitumor T Cell Responses in the Lungs. J. Immunol. 2015;194:5529–5538. doi: 10.4049/jimmunol.1403215. [DOI] [PubMed] [Google Scholar]

[ref49] Qian B., Deng Y., Im J. H., Muschel R. J., Zou Y., Li J., Lang R. A., Pollard J. W.. A Distinct Macrophage Population Mediates Metastatic Breast Cancer Cell Extravasation, Establishment and Growth. PLoS One. 2009;4:e6562. doi: 10.1371/journal.pone.0006562. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref50] Divangahi M., King I. L., Pernet E.. Alveolar Macrophages and Type I IFN in Airway Homeostasis and Immunity. Trends Immunol. 2015;36:307–314. doi: 10.1016/j.it.2015.03.005. [DOI] [PubMed] [Google Scholar]

[ref51] Chang C.-Y., Armstrong D., Corry D. B., Kheradmand F.. Alveolar Macrophages in Lung Cancer: Opportunities Challenges. Front. Immunol. 2023;14:1268939. doi: 10.3389/fimmu.2023.1268939. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref52] Tapmeier T. T., Howell J. H., Zhao L., Papiez B. W., Schnabel J. A., Muschel R. J., Gal A.. Evolving Polarisation of Infiltrating and Alveolar Macrophages in the Lung During Metastatic Progression of Melanoma Suggests CCR1 as a Therapeutic Target. Oncogene. 2022;41:5032–5045. doi: 10.1038/s41388-022-02488-3. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref53] Cho H. J., Jung J. I., Lim D. Y., Kwon G. T., Her S., Park J. H., Park J. H. Y.. Bone Marrow-Derived, Alternatively Activated Macrophages Enhance Solid Tumor Growth and Lung Metastasis of Mammary Carcinoma Cells in a BALB/c Mouse Orthotopic Model. Breast Cancer Res. 2012;14:R81. doi: 10.1186/bcr3195. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref54] Lai Y. H., Chiang C. S., Hsu C. H., Cheng H. W., Chen S. Y.. Development and Characterization of a Fucoidan-Based Drug Delivery System by Using Hydrophilic Anticancer Polysaccharides to Simultaneously Deliver Hydrophobic Anticancer Drugs. Biomolecules. 2020;10:970. doi: 10.3390/biom10070970. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref55] Kulhari H., Pooja D., Shrivastava S., Kuncha M., Naidu V. G. M., Bansal V., Sistla R., Adams D. J.. Trastuzumab-Grafted Pamam Dendrimers for the Selective Delivery of Anticancer Drugs to Her2-Positive Breast Cancer. Sci. Rep. 2016;6:23179. doi: 10.1038/srep23179. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref56] Kruh G. D.. Ins and Outs of Taxanes. Cancer Biol. Ther. 2005;4:1030–1032. doi: 10.4161/cbt.4.9.2052. [DOI] [PubMed] [Google Scholar]

[ref57] Hernández-Vargas H., Palacios J., Moreno-Bueno G.. Molecular Profiling of Docetaxel Cytotoxicity in Breast Cancer Cells: Uncoupling of Aberrant Mitosis and Apoptosis. Oncogene. 2007;26:2902–2913. doi: 10.1038/sj.onc.1210102. [DOI] [PubMed] [Google Scholar]

[ref58] Haggerty T. J., Dunn I. S., Rose L. B., Newton E. E., Martin S., Riley J. L., Kurnick J. T.. Topoisomerase Inhibitors Modulate Expression of Melanocytic Antigens and Enhance T Cell Recognition of Tumor Cells. Cancer Immunol., Immunother. 2011;60:133–144. doi: 10.1007/s00262-010-0926-x. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref59] Chan O. T., Yang L. X.. The Immunological Effects of Taxanes. Cancer Immunol., Immunother. 2000;49:181–185. doi: 10.1007/s002620000122. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref60] Garnett C. T., Schlom J., Hodge J. W.. Combination of Docetaxel and Recombinant Vaccine Enhances T-Cell Responses and Antitumor Activity: Effects of Docetaxel on Immune Enhancement. Clin. Cancer Res. 2008;14:3536–3544. doi: 10.1158/1078-0432.CCR-07-4025. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref61] Millrud C. R., Mehmeti M., Leandersson K.. Docetaxel Promotes the Generation of Anti-Tumorigenic Human Macrophages. Exp. Cell Res. 2018;362:525–531. doi: 10.1016/j.yexcr.2017.12.018. [DOI] [PubMed] [Google Scholar]

[ref62] Ma S., Feng X., Liu F., Wang B., Zhang H., Niu X.. The Pro-Inflammatory Response of Macrophages Regulated by Acid Degradation Products of Poly(lactide-co-glycolide) Nanoparticles. Eng. Life Sci. 2021;21:709–720. doi: 10.1002/elsc.202100040. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref63] Bissery M.-C., Guénard D., Guéritte-Voegelein F., Lavelle F.. Experimental Antitumor Activity of Taxotere (Rp 56976, Nsc 628503), a Taxol Analogue. Cancer Res. 1991;51:4845–4852. [PubMed] [Google Scholar]

[ref64] Ryu M. J., Chung H. S.. Fucoidan Reduces Oxidative Stress by Regulating the Gene Expression of HO-1 and SOD-1 through the Nrf2/ERK Signaling Pathway in HaCat Cells. Mol. Med. Rep. 2016;14:3255–3260. doi: 10.3892/mmr.2016.5623. [DOI] [PubMed] [Google Scholar]

[ref65] Hsu H.-Y., Lin T.-Y., Lu M.-K., Leng P.-J., Tsao S.-M., Wu Y.-C.. Fucoidan Induces Toll-Like Receptor 4-Regulated Reactive Oxygen Species and Promotes Endoplasmic Reticulum Stress-Mediated Apoptosis in Lung Cancer. Sci. Rep. 2017;7:44990. doi: 10.1038/srep44990. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref66] Zhang Z., Teruya K., Eto H., Shirahata S.. Fucoidan Extract Induces Apoptosis in MCF-7 Cells Via a Mechanism Involving the ROS-Dependent JNK Activation and Mitochondria-Mediated Pathways. PLoS One. 2011;6:e27441. doi: 10.1371/journal.pone.0027441. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref67] Yang L., Wang P., Wang H., Li Q., Teng H., Liu Z., Yang W., Hou L., Zou X.. Fucoidan Derived from Undaria Pinnatifida Induces Apoptosis in Human Hepatocellular Carcinoma SMMC-7721 Cells Via the ROS-Mediated Mitochondrial Pathway. Mar. Drugs. 2013;11:1961–1976. doi: 10.3390/md11061961. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref68] Kong D. S., Song S. Y., Kim D. H., Joo K. M., Yoo J. S., Koh J. S., Dong S. M., Suh Y. L., Lee J. I., Park K., Kim J. H., Nam D. H.. Prognostic Significance of c-Met Expression in Glioblastomas. Cancer. 2009;115:140–148. doi: 10.1002/cncr.23972. [DOI] [PubMed] [Google Scholar]

[ref69] Jung Y., Joo K. M., Seong D. H., Choi Y. L., Kong D. S., Kim Y., Kim M. H., Jin J., Suh Y. L., Seol H. J., Shin C. S., Lee J. I., Kim J. H., Song S. Y., Nam D. H.. Identification of Prognostic Biomarkers for Glioblastomas Using Protein Expression Profiling. Int. J. Oncol. 2012;40:1122–1132. doi: 10.3892/ijo.2011.1302. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Concurrent P‑Selectin Targeting Nanoparticle Orchestrates Tumor-Immune Dynamics for Advanced Immunochemotherapy

Wei Lee

Syuan-Ling Lin

Jui-Yu Chen

Bo-Jie Huang

Wee-Wei Chieng

I-Jung Tsai

Ting-Yu Chang

Yen-Ho Lai

Wan-Zhen Hong

Kevin Chih-Yang Huang

Mien-Chie Hung

San-Yuan Chen

Long-Bin Jeng

Woei-Cherng Shyu

Chih-Sheng Chiang

Abstract

Introduction

Results and Discussion

Characterization of DTX-Loaded NPs Coated by PVA, Dextran Sulfate, and Fucoidan

1.

Fu-NP Enables Dual-Targeting by Recognizing P-Selectin Shared by TNBC and TAM

2.

Dual-Cell Targeting by FINAL Promotes M1 Polarization and Suppresses Tumor Invasion In Vitro

3.

RNA-Seq Reveals Component-Specific TME Reprogramming and Validates Fucoidan-Mediated Nanobio Interactions

4.

FINAL-Mediated Reduction in VEGF-A-Induced Angiogenesis In Vitro and In Vivo

5.

FINAL Reshapes the TME and Enhances Therapeutic Efficacy

6.

FINAL Reduces CHC Formation via TME Modulation and Disruption of Cell Adhesion

7.

FINAL Suppresses Lung Metastasis by Promoting M1 Polarization of Bone Marrow-Recruited Macrophage in Lung

8.

Translational Potential and Toxicology Studies of FINAL

Bio-Nano Interface Engineering: From TME Remodeling to Systemic Immunochemotherapy

9.

Conclusions

Methods

Ethical Statements

Materials and Reagents

Synthesis and Characterization of Nanoparticles (NPs)

Quantification of Fucoidan Using Heparin Red

Cell Culture

Animal Care and Tumor Inoculation of 4T1 Cells

Evaluating Therapeutic Efficacy by Monitoring Tumor Size and Survival Rate

Evaluation of Antimetastasis Ability

Detection of P-Selectin Expression on Live Tumor Surface

The Relationship between P-Selectin Expression and NP Uptake in Live Tumors

Binding Studies of Nanoparticles to Immobilized P-Selectin

Immunohistochemistry and Generation of Protein Expression Values

Dual Cell-Targeting Affinity Test

Intracellular ROS Levels of Cancer Cells

Activation of Macrophage Polarization

Macrophage Polarization Detected by Quantitative Real-Time PCR

Macrophage Polarization Detected by Immunocytochemistry Staining

Macrophage Polarization in a Transwell Mimicking TME

Macrophage Migration and Invasion Assay

RNA Sequencing

Flow Cytometry Analyses

T-Distributed Stochastic Neighbor Embedding (tSNE)-Based Analysis

Immunohistochemical (IHC) Assessment

Cytokine Detection by Enzyme-Linked Immunosorbent Assay (ELISA)

Apoptosis Analyses

Angiogenesis Analyses

In Vitro CHC Model

Biodistribution

In Vivo Safety Profile of FINAL

Statistics and Reproducibility

Supplementary Material

Acknowledgments

◮.

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES