Nanomaterials in modulating tumor-associated macrophages and enhancing immunotherapy

Chen Liang a, Yihan Zhang d, Siyao Wang a, Wangbo Jiao d, Jingyi Guo a, Nan Zhang *b and Xiaoli Liu *abc
aKey Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, The College of Life Sciences & School of Medicine, Northwest University, Xi’an, Shaanxi 710069, China. E-mail: liuxiaoli0108@xjtu.edu.cn
bInstitute of Regenerative and Reconstructive Medicine, Med-X Institute, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi 710049, China
cNational Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, Shaanxi Provincial Center for Regenerative Medicine and Surgical Engineering, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi 710061, China
dKey Laboratory of Synthetic and Natural Functional Molecule of the Ministry of Education, College of Chemistry and Materials Science, Northwest University, Xi’an, Shaanxi 710127, China

Received 3rd February 2024 , Accepted 12th April 2024

First published on 13th April 2024


Abstract

Tumor-associated macrophages (TAMs) are predominantly present in the tumor microenvironment (TME) and play a crucial role in shaping the efficacy of tumor immunotherapy. These TAMs primarily exhibit a tumor-promoting M2-like phenotype, which is associated with the suppression of immune responses and facilitation of tumor progression. Interestingly, recent research has highlighted the potential of repolarizing TAMs from an M2 to a pro-inflammatory M1 status—a shift that has shown promise in impeding tumor growth and enhancing immune responsiveness. This concept is particularly intriguing as it offers a new dimension to cancer therapy by targeting the tumor microenvironment, which is a significant departure from traditional approaches that focus solely on tumor cells. However, the clinical application of TAM-modulating agents is often challenged by issues such as insufficient tumor accumulation and off-target effects, limiting their effectiveness and safety. In this regard, nanomaterials have emerged as a novel solution. They serve a dual role: as delivery vehicles that can enhance the accumulation of therapeutic agents in the tumor site and as TAM-modulators. This dual functionality of nanomaterials is a significant advancement as it addresses the key limitations of current TAM-modulating strategies and opens up new avenues for more efficient and targeted therapies. This review provides a comprehensive overview of the latest mechanisms and strategies involving nanomaterials in modulating macrophage polarization within the TME. It delves into the intricate interactions between nanomaterials and macrophages, elucidating how these interactions can be exploited to drive macrophage polarization towards a phenotype that is more conducive to anti-tumor immunity. Additionally, the review explores the burgeoning field of TAM-associated nanomedicines in combination with tumor immunotherapy. This combination approach is particularly promising as it leverages the strengths of both nanomedicine and immunotherapy, potentially leading to synergistic effects in combating cancer.


1. Introduction

Immunosuppressive cells, notably myeloid-derived suppressive cells (MDSCs), M2-like tumor-associated macrophages (M2-like TAMs), tumor-associated neutrophils, regulatory T cells (Tregs), and tumor-associated dendritic cells collectively contribute to the immune evasion microenvironment in solid tumors.1–8 Among these, M2-like TAMs have emerged as key players owing to their pivotal role in secreting immunosuppressive molecules such as interleukin 10 (IL-10) and transforming growth factor-β (TGF-β).9–11 These molecules significantly contribute to promoting tumorigenesis, cancer progression, angiogenesis, cancer invasion, and metastasis. Additionally, M2-like TAMs, functioning as antigen-presenting cells (APCs), exert a profound impact on adaptive immunity. For instance, they hinder T-cell activation by interfering with T-cell lipid metabolism.12 This interference poses a formidable obstacle to the adaptive immune response against tumors. To address this, innovative strategies have been explored, such as promoting M2-to-M1 repolarization and depleting existing M2-like TAMs. These approaches have demonstrated efficacy in TAM engineering, thus opening new avenues for tumor eradication through the synergistic enhancement of both innate and adaptive immunity.13

The current approach to modulating TAM polarization primarily relies on various cytokines. Typically, the granulocyte-macrophage colony-stimulating factor, interferon gamma (IFN-γ), and lipopolysaccharide (LPS) are employed to activate M1-type macrophages, while macrophage colony-stimulating factor, interleukin 4 (IL-4), IL-10, and interleukin 13 (IL-13) are utilized for M2-type macrophage activation.14 In addition, receptor agonists and RNAs have shown efficacy in modulating TAM polarization. These cytokines, which are small molecule proteins, usually act on classical polarization pathways,13 including TLR/NF-κB and JAK/STAT. Despite the mechanism of polarization is clear, these approaches face common challenges, such as non-targeted delivery and release, systemic side effects, and limitations in tissue penetration and bioavailability. One promising avenue to overcome these challenges lies in leveraging nanomaterials. Due to their high programmability, excellent biocompatibility, and minimal biotoxicity, nanomaterials could be meticulously designed as delivery vehicles to address these issues.15,16 This strategic use of nanomaterials offers a potential solution to enhance the precision and effectiveness of TAM modulation, paving the way for more targeted and efficient immunotherapies in the context of solid tumors.

As research progresses, not all reported nanodelivery systems for TAM polarizations have a clearly defined action pathway. The introduction of alternative treatment modalities, such as sound, light, electricity, and magnetism, may augment intracellular reactive oxygen species (ROS), thereby influencing both innate and adaptive immunity.17,18 Moreover, specific nanomaterials possessing intrinsic enzyme-like catalytic features can also induce ROS generation.19 ROS, well-documented for their role in prompting pro-inflammatory macrophage polarization,20 operate through the transcription of pro-inflammatory factors and monocyte chemotactic proteins.21 This process is facilitated and promoted by mitogen-activated protein kinase (MAPK) and NF-κB signaling pathways, among others. Notably, the diverse influences on TAM polarization highlight the complexity of the immune response modulation. Expanding beyond nanomaterials, immune cell-derived exosomes or nanoparticles coated with immune cell membranes, including those from macrophage and natural killer cells, inherit the tumor-homing ability of immune cells.22 This capability allows them to effectively modulate TAM polarization, presenting a promising avenue for precise immunomodulation within the tumor microenvironment. Furthermore, exosomes derived from bacterial cells exhibit shared similarities in their ability to polarize TAMs, adding an intriguing dimension to the spectrum of modulatory agents. Beyond nanomaterials and exosomes, gases,23 vitamin C (Vc), simvastatin, and other agents have also been identified for their ability to polarize TAMs.

This review provides a thorough overview of the origins, functions, and significance of macrophages in tumor biology. It delves into the intricate signaling pathways associated with macrophage polarization and explores the diverse strategies and mechanisms employed by nanotechnology to modulate these crucial immune cells. Beyond elucidating the current state of knowledge, the review offers insights into the potential development of nanomaterials for macrophage engineering, suggesting promising avenues for future research and applications. Figure (Fig. 1) provides a schematic representation of how nanomaterials play a regulatory role in macrophage polarization.


image file: d4tb00230j-f1.tif
Fig. 1 Schematic of nanomaterials regulating tumor-associated macrophage (TAM) polarization.

2. Origins and roles of macrophages

Recent studies have revealed the predominant origins of tissue-resident macrophages, with a substantial lineage tracing back to the yolk sac and fetal liver during early development. As an individual matures, progenitor cells originating in the bone marrow enter the peripheral blood, undergo maturation processes, and eventually give rise to circulating macrophages in vivo.24–26 Macrophages exhibit a dynamic classification into two main categories: tissue-resident macrophages and monocyte macrophages.27 This categorization underscores the heterogeneous nature of macrophages, which possess high plasticity and the ability to adopt various polarization states to maintain the organism's homeostasis.13,28 Functionally, macrophages are broadly classified into two major subtypes based on their roles within the immune system: the pro-inflammatory M1-like macrophages and anti-inflammatory M2-like macrophages. This functional diversity highlights the pivotal role of macrophages in orchestrating immune responses and maintaining a delicate balance within the host organism.

Pathogen-associated and danger-associated molecular patterns, such as IFN-γ, tumor necrosis factor-α (TNF-α), and LPS, serve as specific activators of M1-type macrophages.29–34 Upon activation, M1 macrophages express antigenic determinants, including CD80, CD86, NOS2, and secrete a range of cytokines and pro-inflammatory metabolites such as IL-1β, IL-12, CCR7, Inhibin Subunit Beta A (Inhba), TNF-α, ROS and nitric oxide (NO).35 Tumoricidal M1-type macrophages not only enhance phagocytosis and antigen presentation ability, but also play a crucial role in promoting cytotoxic T-cell activation. However, M1-type macrophages constitute a minority cell population within the tumor microenvironment (TME), where proinflammatory factors are relatively scarce. In contrast, M2 macrophages respond to anti-inflammatory factors such as TGF-β and IL-10. The activation of M2-type macrophages results in the expression of antigenic determinants, including Chi3l3/Ym1, Retnla/Fizz1, Egr2, Fn1, and Mrc1/CD206. They secrete cytokines such as vascular endothelial growth factor, epidermal growth factor, Arg1, among others.36 M2-type macrophages play a role in promoting injury repair and cell growth, contributing to the production of Treg and MDSCs. They constitute the majority cell population within the TME, characterized by a high content of inflammation-suppressing factors.37 This dual classification of macrophages into M1 and M2 subtypes, each responding to distinct activation signals and exerting different functions within the TME, underscores the intricate balance between pro-inflammatory and anti-inflammatory responses in the context of tumor biology.

The M1/M2 polarization process is a reversible and dynamic phenomenon that is characterized by functional adaptation. During this process, macrophages undergo a transformation, acquiring new functions while retaining the ability to sense external environment stimuli. This intrinsic adaptability enables macrophages to continuously adjust to changing conditions. Recognizing that this adaptability positions macrophages as potential targets and intervening in their polarization process has emerged as a promising tool for tumor treatment. The schematic representation of the macrophage polarization mechanism is depicted in Fig. 2, providing a concise illustration of the dynamic and reversible nature of macrophage polarization.


image file: d4tb00230j-f2.tif
Fig. 2 Schematic of the polarization mechanism of TAMs.

3. Cellular immunotherapy for cancer treatment

Cellular immunity involves the recognition of antigens by pattern recognition receptors of APCs, the presentation of antigen information, and the subsequent activation of CD4+ T cells or CD8+ T cells through MHC class II molecules or MHC class I molecules, along with other co-stimulatory molecules.38–40 CD4+ T cells play a supportive role in the activation of CD8+ T cells, which are subsequently fully activated and proliferate to recognize and eliminate tumor cells.41 Concurrently, the fragments of cleared tumor cell contribute to the enhancement of immunity. However, tumors employ diverse strategies to evade immune surveillance. Tumors with low immunogenic antigens face challenges in eliciting effective anti-tumor immune responses, a phenomenon known as antigenic modulation. The low expression of MHC Class I molecules in tumor cells further impedes their ability to present tumor antigens. Abnormal tumor cell co-stimulatory signaling, such as PD-L1, CD47, and other molecules, interferes with APC recognition, macrophage phagocytosis, and the specific activation of T cells.38 This intricate interplay within the immune system highlights the challenges faced in harnessing cellular immunity for effective cancer therapy. Tumors employ sophisticated mechanisms to subvert immune responses, necessitating innovative therapeutic approaches to overcome these evasion strategies.

Decades of exploration have shaped the landscape of tumor immunotherapies. Cancer vaccines, leveraging highly immunogenic antigens or mRNA molecules, selectively activate immunity for tumor prevention or treatment (Fig. 3a).42,44 Another avenue involves dendritic cell (DC) vaccines, where tumor antigens are loaded onto DCs to enhance their antigen presentation process (Fig. 3b). Overcoming challenges associated with culturing and purifying DCs, recent research has introduced mononuclear vaccines employing DC precursor cells as a vehicle. This approach induces the differentiation of monocytes into DCs, thereby facilitating the development of DC vaccines.43,45,46 Adoptive cell therapy, a recent focus in tumor immunotherapy,47 encompasses diverse modalities such as tumor-infiltrating T-cell therapy,48,49 chimeric antigen receptor T-cell therapy, and T-cell receptor therapy.50 Despite their promise, these treatments face challenges, including the poor homing ability of engineered cells to the tumor site, limited treatment duration, inability to reverse the immunosuppressive microenvironment, and unsatisfactory therapeutic outcomes.


image file: d4tb00230j-f3.tif
Fig. 3 (a) A simplified depiction of cancer vaccine delivery platforms. Reproduced with permission.42 Copyright 2021, Springer Nature. (b) Schematic of dendritic cells inducing adaptive and innate anti-leukemia immunity. Reproduced with permission.43 Copyright 2019, MDPI.

Recognizing the high plasticity of macrophages, scientists have explored innovative approaches such as CAR-macrophages,51 macrophage polarization inducers,52etc. The CAR-macrophage has the advantages of easy access to the TME despite the dense stroma around tumor cells, short in vivo circulation time, and low off-target toxicity. For example, Zhang et al. developed a CAR-147 macrophage approach that did not cause cytokine release syndrome, the most common toxicity event in the preclinical use of CAR-T cells to treat tumors, and exerted positive anti-tumor effects by increasing the level of pro-inflammatory factors in the TME.53 Zanganeh et al. found that iron oxide nanomaterials could induce M1-type macrophages in the TME to inhibit tumor growth.54 The method based on macrophage regulation has obtained preliminary research results in clinical practice. Conde et al. found that M1-like macrophages were rapidly transformed into M2-like regulatory macrophages in allografts of transplant recipients treated with the anti-CD40/CD40L mAb co-stimulation blockade, but untreated recipients maintained M1-like inflammatory macrophages in rejected allografts.55 This suggests that the immune response is achieved by modulating macrophage polarization rather than depleting all macrophages. Abdin et al. found that the use of human iPSC-derived CAR macrophages promoted strong activation of the pro-inflammatory M1 phenotype and upregulation of chemokines and co-stimulatory genes.56 Upon activation, CAR-iMacs exhibited a strong antiviral immune response, which further enhanced their anti-tumor capacity by activating the interferon pathway. These approaches pave the way for precision immunotherapy by targeting macrophages.

4. Current research landscape in macrophage modulation using nanomaterials

In the beginning, agonists, DNA, RNA and other small molecule drugs were utilized to modulate macrophages. They usually work by definite pathways. However, the actual efficacy is usually unsatisfactory for their low bioavailability and potent systemic side effects. Nanomaterials that act as delivery vehicles could offer a precise design option for enhancing drug delivery efficiency and bioavailability in vivo.57 In this case, the well-explored mechanism of M1-type macrophage polarization can be involved, primarily through classical pathways such as the NF-κB, STAT protein family, Notch, etc. Additionally, macrophage polarization can also be regulated by controlling the activation and number of micro-RNAs.58 In addition to serving as delivery vehicles, some nanomaterials themselves have the function of polarizing macrophages. The polarization mechanisms do not align with the classical pathway and remain unclear. For example, cuttlefish nanodroplets polarize macrophages by intervening in the MAPK pathway.59 Metal oxides, on the other hand, primarily induce macrophage polarization through the production of ROS, a multifunctional process that is challenging to classify into a single pathway.60 Above all, we classify nanomaterials that polarize macrophages through classical pathways, non-classical pathways or multi-pathways based on the substances playing the major role, such as drugs, ROS, endogenous substances, natural nanomaterials, and more.

4.1. Modulation of macrophages by affecting classical polarized cellular pathways

As we have mentioned before, small molecules modulate macrophage polarization via classical pathways. Nanomaterials with programmable structure mainly act as delivery vehicles to improve the solubility, targeting and biosafety of these small molecules such as agonists, DNA and RNA.
4.1.1. TLR/NF-κB signaling pathway. Toll-like receptors (TLRs), specific pattern recognition receptors on APCs, are capable of identifying pathogen-associated and danger-associated molecular patterns such as LPS and flagellin. TLRs consist of an extracellular structural domain for ligand binding, a transmembrane structural domain, and an intracellular structural domain for signal transduction. TLR3, TLR7, TLR8, and TLR9 are located on the intracellular endosomes, while other TLRs are located on the cytoplasmic membrane. Upon ligand binding, TLRs recruit signaling proteins such as MyD88, TIRAP, TRAM, or TRIF in the intracellular structural domain. These proteins, in turn, activate different kinases and ubiquitin ligases based on the specific stimuli.61–63 All TLRs, except TLR3, activate the classical MyD88 signal, leading to the production of TNF-α, IL-1, and IL-6, and the activation of the transcription factor NF-κB. Conversely, TLR3 can only be activated through a TRIF-dependent pathway. TLR4 is unique as it can recruit all four downstream molecules, including MyD88, MAL/TIRAP, TRIF, and TRAM.31

R848, an FDA-approved TLR7/8 agonist, facilitates the conversion of TAMs from the M2 to M1 phenotype, significantly enhancing antibody-dependent cell-mediated phagocytosis. However, R848 alone falls short of meeting therapeutic expectations in the complex TME. Wei et al. developed poly (lactic-co-glycolic acid) (PLGA) nanoparticles (Ec-PR848) loaded with DOX as immunogenic cell death (ICD) initiators.64 Ec-PR848 was created by linking non-pathogenic glycol chitosan-coated E. coli MG1655 and PLGA-R848 through electrostatic interactions. Compared to PR848, further incorporation with E. coli MG1655 significantly improved the polarization efficiency. The outer membrane of E. coli MG1655 is predominantly composed of LPS, which can promote the M1-type polarization via the TLR/NF-κB signaling pathway. This strategy demonstrates the considerable potential of combined ICD and M2-to-M1 repolarization therapy (Fig. 4). Similarly, to address pharmacokinetic issues, Kim et al. designed a nanoemulsion (NE) system capable of encapsulating R837 and R848 together, exhibiting higher immune activation capacity and safety as compared to a single agonist-loaded system.65 R837 is an immune modulator that specifically activates the TLR7 receptor, which is similar in function to R848 and is commonly used to activate the TLR signaling pathway. Anti-PD-1, which was almost ineffective alone, exhibited a significant increase in the number of tumor-free mice when involved in the NE system. This underscores the role of the NE system in overcoming the limitations of the PD-1/L1 single agent blockade or low therapeutic efficiency. As a novel immunotherapy platform, the universal NE system holds great potential in converting non-responders into responders to immune checkpoint blockade therapy, thereby paving the way for clinical translation.


image file: d4tb00230j-f4.tif
Fig. 4 (a) The schematic representation of the effects of poly(lactic-co-glycolic acid) (PLGA) nanoparticles (PR848) loaded with R848 and PLGA nanoparticles (PDOX) loaded with DOX. (b) The quantification of CD80+ macrophages (M1-type) measured via flow cytometry after incubation with different materials for 48 h. (c) The quantification of CD206+ macrophages (M2 type). Reproduced with permission.64 Copyright 2021, American Chemical Society.

In addition to R848, there exist numerous TLRs agonists and certain small molecules with the ability to specifically activate TLRs. CpG-ODN, an oligodeoxynucleotide found in bacteria or viruses, lacks methylation and contains CpG sequences. Recognized specifically by TLR9, CpG-ODN exhibits immunostimulatory properties, impacting NK cells and macrophages, and promoting the M1 pro-inflammatory phenotype,66,67 particularly in weakly immunogenic tumors. This effect is mediated by the interaction of specific bases on both sides of the unmethylated CpG dinucleotide with TLR9,68,69 leading to the activation of NF-κB signaling and the release of pro-inflammatory cytokines, such as TNF-α, IL-6, and IL-12. However, like many small molecule drugs, CpG-ODN is susceptible to degradation by nucleases in vivo, necessitating repeated dosing. This may potentially lead to autoimmune diseases and systemic toxicity, especially affecting the liver and kidneys. Consequently, the optimization of CpG-ODN delivery using nanotechnology to enhance its stimulatory activity has emerged as an effective therapeutic approach. To enhance this process, Shan et al. developed a nanocage (rHF) structure using the human ferritin heavy chain to encapsulate CpG-ODN.70 The outer surface of rHF was modified with a peptide targeting M2 macrophages, significantly improving drug accumulation in TAMs.

4.1.2. The JAK/STAT signaling pathway. M1-type macrophages can be classified into M1 (LPS), M1 (IFN-γ), and M1 (LPS + IFN-γ) based on the source of activation signals. Another class of receptors, IFN-γR, specifically triggers the M1 phenotype. IFN-γ, primarily secreted by NK cells and T cells, serves as a specific ligand for IFN-γR, activating the JAK-STAT1 signaling pathway. The transcription factor STAT1 undergoes phosphodimerization and translocation to the nucleus,71,72 where it encodes various cytokines, chemokines, etc. Inhibition of STAT1 phosphorylation reduces M1 activation of macrophages, and azithromycin acts as an anti-inflammatory agent by inhibiting the transcription of STAT1 and NF-κB. STAT1 also functions as a negative regulator of immune cells (Treg), restraining the growth and transformation of Foxp3+ Treg. While Maj et al. observed that the clearance of Treg did not entirely signify the inhibition of all its pro-tumor effects, it is undeniable that reducing Treg to some extent does exhibit an anti-tumor effect.73

Fu et al. synthesized a conjugated polymer nanoparticle (CPN) based on principles of photothermal and IFN-γ plasmids driven by the heat shock promoter HSP70.74 CPN, serving as a near-infrared photothermal nanoconverter, could induce HSP70-driven IFN-γ expression under irradiation. This led to the phenotypic remodeling of M1-type macrophages, inhibiting tumor growth by upregulating MHC II receptors and secreting pro-inflammatory factors such as TNF-α, IL-6, and NO synthase. The construction of a near-infrared laser-triggered optogenetic nanosystem was successful, enabling the remote and controllable activation of immune responses around cancer cells. This provides an outstanding strategy for non-invasive cancer immunotherapy (Fig. 5).


image file: d4tb00230j-f5.tif
Fig. 5 (a) Schematic representation of the action of conjugated polymer nanoparticles (CPNs). (b) The IFN-γ expression level in the supernatant of the transwell system with different treatments. (c) The M1/M2 ratio (CD86+/CD206+) of macrophages following different treatments, as assayed using flow cytometry. M1-related cytokine levels of TNF-α (d) and IL-6 (e) in the supernatant. Reproduced with permission.74 Copyright 2021, John Wiley and Sons.

However, STAT1 is not the sole downstream substrate of JAK. Seven STAT family members have been identified, and among them, STAT1, STAT3, and STAT6 are believed to be associated with the macrophage polarization process. The STAT3 signaling pathway is a stable signal for maintaining the M2 phenotype. Chen et al. developed a FA-OCMCS/N-2-HACC/siSTAT3 nanoparticle, incorporating folic acid as the targeting ligand and chitosan as the nanocarrier.75 This design exploited the high expression of the folate receptor in M2-type macrophages. The nanoparticles significantly reduced the STAT3 protein expression in vivo, successfully repolarizing macrophages in the TAMs populations from M2 to M1. STAT6 is a crucial transcription factor for IL-4-mediated immune response, inhibiting the production of the inflammatory mediator NO by depleting arginine from the iNOS/Nos2 substrates. This ultimately contributes to the loss of the M1 phenotype.76 Building on this principle, Xiao et al. designed a nanodrug integrated with the STAT6 inhibitor AS1517499 and IKKβ siRNA for the M2 to M1 repolarization of TAMs.77 The nanodrugs, sheathed with pH-sheddable PEG and concealed M2-targeting peptide, exclusively targeted M2-type macrophages in the acidic TME without affecting M2 macrophages in healthy tissues. This effectively reduced systemic immune side effects commonly observed in M2-targeted drug delivery nanosystems. In Glioblastoma (GBM), due to the presence of the blood–brain barrier, there is inefficient drug delivery and deficient drug concentrations at the lesion. To address the therapeutic challenges of GBM, Cui et al. designed a bionic nanoplatform based on endogenous exosomes linked with brain-targetable transferrin to overcome the delivery problem.78 Additionally, tanshinone IIA (TanIIA) was utilized to inhibit STAT3 phosphorylation, attenuating the immunosuppressive effects of Tregs and MDSC, which addressed the difficulty in GBM recovery after surgery. TanIIA was loaded onto GBM exosomes, coupled with CpG ODN 1826 to stimulate TLR9 activation for synergistic effects. This nanoplatform polarized TAMs from the M2-type to the M1-type anti-tumor macrophages, significantly reducing the post-operative recurrence of GBM.

4.1.3. Notch signaling pathway. The Notch signaling pathway, a traditional signaling pathway, has been observed to have receptor expression correlated with the emergence of M1 macrophages.79,80 Unlike other cell surface receptors, Notch receptors and ligands are both membrane proteins, deviating from the classical model of secreted and membrane proteins. The δ-like ligands and Jagged ligands on the cell surface can signal neighboring cells, thereby activating their cognate receptors.81

To date, pharmaceutical companies have rapidly developed antibody-protein drugs targeting the Notch pathway. However, there have been no reported standalone macrophage nano-modulators exclusively targeting the Notch pathway. Considering the crucial role of Notch signaling as a regulator of macrophage polarization, it is inevitable that Notch will be a hot topic for future research.

4.1.4. RNA modulation. MiRNAs are a class of short RNA fragments that do not encode proteins but play a crucial role in the complex growth of cells, often becoming deregulated during cancer development.82,83 When miRNAs that promote the release of inflammatory factors are delivered into the TME, they modulate the polarization phenotype of TAMs and exert an anti-tumor effect. However, bare miRNAs possess a high negative charge and are susceptible to rapid clearance. Consequently, the development of miRNA nano-delivery systems for macrophages is necessary, focusing on the targeted silencing of genes associated with the polarization of the M2 phenotype.84

Zhao et al. demonstrated that fibroblasts from tumor tissues of pancreatic cancer patients could be utilized to prepare miRNA-320a-loaded exosomes (CAFs-Exo).85 In comparison with normal fibroblasts, CAFs-Exo with miRNA-320a exhibited a stronger ability to promote macrophage polarization towards the M2-type. Treatment with an inhibitor of miRNA-320a significantly reduced the expression of miRNA-320a in CAFs-Exo and their capacity to polarize macrophages to the M2-type. Additionally, using the immunofluorescence co-localization technique and protein imprinting, it was demonstrated that miRNA-320a polarizes macrophages to the M2 phenotype by activating the PTEN/PI2Kγ pathway, ultimately promoting the development of pancreatic cancer cells.

MiRNA-155 serves as a regulatory molecule not only on the receptor gene of IL-13, reducing signaling and STAT6 activity to promote the repolarization of TAMs and inhibit tumor growth,86,87 but also plays a crucial role in promoting the proliferation and invasion of malignant cells in various tumor types, including those found in lung, colon, and breast cancers. In inhibition experiments, miRNA-155 demonstrated the ability to repolarize macrophages from M2 to M1 through the STAT1, ERK3/1, and NF-κB pathways.88 Zang et al. designed lipid-coated calcium phosphonate nanoparticles (CaP/miR@MNPs) with conjugated mannose for the delivery of miR155 to TAMs.89 The pH-sensitive material allowed PEG to shield the CaP/miR@MNPs at physiological pH and detach in acidic TME. The nanoparticles effectively delivered miRNA-155, acting within M2 macrophages at tumor sites and successfully inhibiting tumor growth, resulting in a longer survival time for the experimental group of mice.

Compared to endogenous single-stranded miRNAs, double-stranded siRNAs are typically synthesized exogenously and introduced through transfection. SiRNAs complement target genes, inducing the degradation of the corresponding messenger RNAs. This process specifically blocks translation without affecting normal gene expression. Consequently, siRNAs have the capability to target and silence any gene expression, presenting a novel approach for tumor therapy. The siRNAs are more precise in silencing protein expression, although they share common challenges with miRNA.90,91

Monoacylglycerol lipase (MGLL) is a lipolytic enzyme highly expressed in tumor cells, playing a crucial role in regulating the metabolism of triacylglycerols. In the nutrient-poor TME, lipids are broken down into fatty acids to meet energy requirements. The accumulated glycerol activates TAMs to overexpress CB-2 activity, promoting the accumulation of M2-type macrophages. In line with this, Cao et al. developed a poly (disulfide amide) nanosystem for the co-delivery of MGLL siRNA (siMGLL) and CB-2 siRNA (siCB-2).92 Silencing the target genes in a pancreatic cancer model was found to inhibit tumor growth and induce apoptosis of tumor cells (Fig. 6).


image file: d4tb00230j-f6.tif
Fig. 6 (a) A schematic representation of the action of siCB-2/siNC nanoparticles. The expression of classic M2-like macrophage markers (CD206 (b), CCL-22 (c), and Arg-1 (d)) and M1-like macrophages markers (CD80 (e), TNF-α (f), and iNOS (g)), as determined via qRT-PCR analysis. Reproduced with permission.92 Copyright 2022, Elsevier.

The complex TME encompasses several factors that are conducive to tumor growth, including the acidic environment. The abnormal concentration of lactic acid in the microenvironment contributes to acidity, with monocarboxylate transporter protein (MCT) considered one of the culprits responsible for this acidity source. MCT-4 facilitates lactate efflux to maintain stable intracellular pH and induce a weak acidic TME.93,94 One major reason for the prevalence of M2 in TAMs is that lactate activates the cAMP pathway, making macrophages highly sensitive to acidic environments. Silencing MCT can reduce lactate efflux from tumor cells, promote apoptosis, and create a microenvironment with a low concentration of lactate, which is favorable for immune cells to exert anti-tumor effects. Li et al. designed a silica nanoparticle loaded with hydroxycamptothecin (HCPT) and siMCT-4.95 HCPT was encapsulated in silica nanoparticles using BSA. A layer of positively charged poly (ether imide) was coupled to the nanoparticles via amide bonds to load siRNA. The combination of lactate efflux inhibition and chemotherapeutic agents improved the inhibitory state of the microenvironment, inhibiting tumor growth and metastasis.

As research on miRNA and siRNA continues to progress, scientists are increasingly directing their attention to other types of RNAs, such as mRNA or lncRNA.96 These RNAs are typically involved in modulating the immune microenvironment in the form of exosomes, serving as the native RNAs of organisms. They play a significant role in regulating the polarization process of macrophages by participating in the key nodes of the polarization pathway.97

Since IRF5 serves as a downstream effector molecule of TLR, it is considered a potent M1 activator. Zhang et al. designed targeted nanoparticles capable of delivering IRF5 and IKKβ mRNA, encoding M1-polarizing transcription factors, to reprogram TAMs.98 Analysis of the differences in macrophage gene expression between the experimental and pro-inflammatory groups, using NanoString gene expression, revealed the upregulation of M1 key differentiation genes such as Ccl5, while strongly downregulating M2 differentiation genes such as Serpinb2 and Ccl11. This led to the conclusion that the particle vector successfully induced changes in the macrophage phenotype from M2-type pro-inflammatory towards M1-type pro-inflammatory. In an ovarian cancer model, IRF5/IKKβ NPs significantly reduced immunosuppressive macrophages and increased M1-type macrophages at the tumor site, while enhancing inflammatory factor infiltration. In a glioma model, nanoparticles significantly reduced tumor growth, increased survival cycles in mice, and demonstrated notable therapeutic effects in ovarian cancer and glioma, all while exhibiting favorable biocompatibility. Based on these promising experimental results, Zhang et al. were prepared to initiate the first human clinical trials to further advance the progress in the field of cancer treatment. Besides these studies, a selection of similar experimental results can be found in Table 1.

Table 1 RNA-loaded nanomaterials developed for TAM repolarization
RNA type Target site Influence Nanomaterials Ref.
miRNA-155 C/EBPβ mRNA upregulate in response to LPS or IFN signals sPEG/GLC nanocomplexes 99
miRNA-125b/miRNA-155 IRF-4/C/EBPβ mRNA Enhance surface activation markers in response to IFN-γ/upregulate in response to LPS or IFN signals HA-PEI/HA-PEG self-assembling nanoparticle-based non-viral vectors 100
miRNA-125b IRF-4 Enhance surface activation markers in response to IFN-γ HA-PEI nanoparticles 101
Exosome 102
CD44/EGFR-targeted hyaluronic acid (HA)-based nanoparticles 103
miRNA-127 Bcl6 Upregulate phosphorylated JNK kinase RNA-binding motif nanoplexes 104
Redd1-siRNA Redd1 Upregulate IL-4 Outer membrane vesicles 105


4.2. Nanomaterials for polarizing macrophages through a non-classical polarization mode

While all biological processes can be traced, some are too complex to be attributed to a specific pathway. For instance, ROS, a classical component of inflammatory sites, can be involved in various physiological and biochemical processes in cells through the activation of the epidermal growth factor receptor, activation of phospholipases, the PI3K signaling pathway, and modulation of calmodulin activity, etc. ROS can be generated through the metal nanoparticles-mediated Fenton reaction. High concentrations of ROS can even lead directly to cell death, and ROS also induce macrophage polarization to the M1 type. Exosomes loaded with complex cell-derived pro-inflammatory components can promote macrophage polarization towards the M1 type. In this selection, we classify nanomaterials that polarize macrophages through non-classical pathways based on the specific substances that play a role in the polarization, such as ROS, endogenous substances, natural nanomaterials, and more.
4.2.1. Nanomaterials polarize macrophages by ROS. Elevated levels of ROS can lead to cell death, which are often generated through the Fenton reaction of metal nanoparticles or natural peroxisome.106,107 Ferumoxytol, an FDA-approved iron oxide nanoparticles used for treating iron deficiency anemia induced by chronic kidney disease, exhibits Fenton-like reaction activity, generating ROS. The growing body of research on ROS has revealed a close connection between ROS and macrophage polarization.108

Zou et al. employed red blood cell membranes (RBCM) encapsulated with perfluorohexane (PFC) and glucose oxidase (GOX) to construct bionic artificial NK cells.109 The main body of the nanosystem was formed by PFC, serving as a biomimetic cytoskeleton, while GOX, as a bioactive substance, consumed glucose and produced H2O2 to emulate the function of NK cells. ROS generated by this system can repolarize M2-type macrophages to M1-type, clear tumor cells, activate immune-enhancing responses, and induce an immune amplification effect (Fig. 7). Liu et al. innovatively developed a ferrimagnetic vortex-domain iron oxide nanoring and graphene oxide (FVIOs-GO) hybrid nanoparticle with a higher specific absorption ratio (SAR) as compared to superparamagnetic materials.110 The GO bridged on the FVIOs exhibited desirable electronic and thermal conductivity, compensating for the poor dielectric loss of FVIOs and resulting in a synergistically enhanced SAR. Additionally, the CREKA peptide was employed for the precise targeting of breast cancer. Under an alternating magnetic field (AMF), this system induced ICD and a change in the TAM phenotype at the tumor site. The temperature control introduced into the nanozyme system, combined with the excellent tissue-penetrating property of AMF, increased the temperature at a fixed point, enhancing the generation of ROS, accurately killing tumor cells, and improving the inhibitory immune microenvironment (Fig. 8). Cheng et al. utilized a glucose-containing hydrophilic micelle stabilizer, chitosan, to encapsulate CUDC101 and a photosensitizer, IR780, creating a novel nanomaterial system.111 CUDC101 inhibited CD47 to re-educate pro-tumor M2 phenotype macrophages, while ROS generated by the photosensitizers and the upregulation of p53 also contributed to macrophage reprogramming.


image file: d4tb00230j-f7.tif
Fig. 7 (a) The schematic of NK cells–biomimetic (aNK) for the re-education of macrophages. The expression of (b) M1 macrophage markers CD86, (c) CD80, (d) MHC-II, and (e) M2 macrophage markers CD206 based on flow cytometry analysis. Reproduced with permission.109 Copyright 2019, John Wiley and Sons.

image file: d4tb00230j-f8.tif
Fig. 8 (a) Display diagram illustrating the delivery of peptide CREKA-conjugated ferrimagnetic vortex-domain iron oxide nanorings and graphene oxide (FVIOs-GO-CREKA) nanorings, along with a schematic diagram of their effects. The quantification of M1 (b) and M2 (c) macrophage phenotypes for different treatments on day 7 in vivo. Reproduced with permission.110 Copyright 2020, American Chemical Society.
4.2.2. Nanomaterials with cell-derived proinflammatory components. Nanomaterials with biomembranes or membrane-like structures are biocompatible and inherit a variety of protein signaling molecules while carrying genetic information from cytomembranes. This category typically includes extracellular vesicles, liposomes, and membrane-encapsulated nano-delivery systems. All the nanomaterials with cell-derived pro-inflammatory components described in this section exert their ability to promote macrophage polarization by carrying pro-inflammatory factors or nucleic acid molecules on their surfaces or internally. Although they have different physicochemical properties, biochemical composition, and pathways of action, the result is an increase in inflammatory factors and polarization of M1-type macrophages.112,113

Extracellular vehicles (EVs) play a crucial role in modulating metabolism and cancer development, serving as a conservative means of intercellular communication. EVs offer several advantages over polymeric synthetic carriers. They are cell-derived, potentially reducing rejection effects if homologous, and maintain some membrane features of the original cells if they are heterologous.114 When EVs are produced by the proinflammatory cells, they inherit some pro-inflammatory components, such as LPS on the surface of the bacterial membrane, TNF-α, IFN-γ, and IL-1 produced by immune cells. EVs contain numerous proteins and RNA from the source cells, providing activation signals or genetic information to the target cells.115 The lipid bilayer of exocysts can protect contents from degradation or metabolism in the blood circulation, serving as an effective cargo carrier.114 Exploiting these advantages and targeting macrophage repolarization by leveraging EV carrier properties or their intrinsic characteristics is a promising avenue of research. Chen et al. developed exosomes loaded with chlorin e6 and iron oxide nanoparticles (IONS).116 IONS promoted M1 cell polarization through the Fenton reaction, and exosomes loaded with IONS demonstrated a concentration-dependent polarization of macrophages into the M1 phenotype. The combined effect of these co-loaded components synergistically promoted the polarization process. While researchers emphasize that ROS play an important role, it is undeniable that due to the cellular origin of the exosomes, their properties increase the biocompatibility of the nanosystems and pro-inflammatory components, providing a macrophage regulation effect in addition to ROS.116

Although exosomes have high biological relevance, their limited production hinders their widespread use. Nanovesicles, produced by continuous cell extrusion, may serve as potential alternatives to exosomes, providing higher yields and greater enrichment of proteins and RNA. This makes nanovesicles promising candidates for inducing macrophage phenotypes with potentially higher efficiency than exosomes. Choo et al. utilized M1 macrophage exosome-mimicking nanovesicles (M1NV) to repolarize TAMs from the M2 to M1 phenotype at the tumor site.117 This approach aimed to address the limitations of immune checkpoint therapy, showing improved results as compared to using the PD-L1 monoclonal antibody or M1NV alone. The study suggested that M1NV derived from M1 macrophages could act as an immunomodulator, enhancing the pro-tumor environment in the TME. Additionally, the study explored the use of outer vesicles obtained from Gram-negative bacteria as a nanosystem to influence macrophage polarization. These vesicles contained LPS, an endogenous stimulatory component secreted by Gram-negative bacteria, which could activate various TLR pathways to induce M1 polarization in macrophages (Fig. 9). Similarly, NK cell membranes were investigated for their ability to induce pro-inflammatory M1 macrophage polarization and target tumor cells via membrane proteins (e.g., RANKL or DNAM-1). Deng et al. designed nanoparticles loaded with a photodynamic therapeutic agent and modified with NK cell membranes, demonstrating the NK cell membranes’ dual potential to target macrophages and induce M1 polarization.118 The combined approach eradicated primary tumors, enhanced microenvironment suppression, and prevented tumor migration and recurrence.


image file: d4tb00230j-f9.tif
Fig. 9 (a) The synthesis process of M1 macrophage exosome-mimicking nanovesicles (M1NVs) and the schematic diagram of its action. The relative mRNA expression of M1 (b) and M2 (c) macrophage markers, as determined through qRT-PCR. Reproduced with permission.117 Copyright 2018, American Chemical Society.
4.2.3. Nanoparticles extracted from natural substance. In addition to the explored technologies, natural substances with inherent activity are gaining attention as their functional roles are being developed with technological advancements. These substances kill tumor cells in their own intrinsic way or induce an inflammatory response to promote the polarization of M1-type macrophages. Ionizing radiation induces to the release of tumor-associated antigens and damaged DNA. Ultrafiltration of concentrated cultures (RT-UF) generated by irradiating tumor cells can stimulate the maturation of DCs and the polarization of M1 macrophages. Wan et al. developed a nano-delivery system, UF@MRP, by loading RT-UF and Melittin, a natural cytolytic peptide derived from bee venom known for rapidly killing tumor cells, into a novel hydrogel MLT-polyethylene glycol.119 The released lysogenic peptides killed cancer cells, RT-UF matured DCs, and the promotion of macrophage M1 polarization reshaped the TME, strongly activating adaptive immunity.

The ink of cuttlefish is composed of melanin, polysaccharides, oligopeptides, and metals. Various reports have indicated that some polysaccharides of natural origin can modulate the phenotype and function of macrophages. Deng et al. investigated the role of nanoparticles from cuttlefish ink as immunomodulators affecting macrophage phenotypes, focusing on the functional aspect of polysaccharides. These nanoparticles exhibited advantages such as a spherical shape, high dispersion, and positive biocompatibility. The activation of the MAPK signaling pathway promoted the transformation of the M2 into the M1 phenotype. Melanin, with its photothermal conversion properties, could effectively promote the ablation of tumor cells through photothermal therapy, presenting promising prospects.49

Ou et al. purified tobacco mosaic virus by extraction, precipitation, centrifugation, and dialysis.120 They discovered that rod-shaped nano-extracts of tobacco mosaic virus polarized macrophages to the M1 phenotype and reversed the pro-tumor microenvironment. The polarization was significantly inhibited when the nanoextract was used in combination with TAK-242 (a TLR4 inhibitor), leading to the downregulation of genes related to CD86, iNOS, TNF-α, IL-6, IL-1β, IL-12b, and CD40. Additionally, when CU115 (a TlR7/8 inhibitor) was used in combination with the tobacco mosaic virus (TMV), the polarization was still inhibited to some extent, indicating the involvement of TLR4 and TLR7/8 in the polarization of macrophages by TMV, with TLR4 playing a more central role. Further studies revealed that the key mechanism involved TLR4-TRAF6-NF-κB/MAPK, highlighting its significant role. TMV was observed to cause no damage to major organs in vivo, significantly inhibiting tumor growth after inducing macrophage polarization. Moreover, it demonstrated high efficiency in inhibiting tumor metastasis, offering a novel approach for tumor immunotherapy and repolarization therapy targeting macrophages.

4.2.4. Others. In addition to the substances mentioned earlier, various substances, including gases, Vc, and TiO2, have been identified for their ability to polarize macrophages towards the M1 type. These diverse substances defy easy categorization as drugs or natural nanomaterials due to their varied nature. Dai et al. addressed the challenge of hypoxia by creating micro-oxygen capsules encapsulating oxygen in polydopamine nanoparticles.121 These capsules successfully delivered oxygen to the hypoxic microenvironment, alleviating hypoxia in TAMs and promoting M1 macrophage polarization, as evidenced by an increased M1/M2 ratio. In a recent study, Ma et al. explored the therapeutic potential of high concentrations of Vc in promoting tumor therapy.122 Vc was found to stimulate the production of hydrogen peroxide, linked to the polarization of M1-type macrophages. To harness these effects, the researchers developed a biodegradable and stimuli-responsive lipid polymer nanoparticle loaded with Vc and the photothermal material indocyanine green. This nanoparticle, based on lecithin-polyethylene glycol modified PLGA, exhibited laser-promoted Vc release at the target site. This strategy stimulated an adaptive immune response against cancer, enhanced immune checkpoint therapy, reduced the proportion of M2-type macrophages, and increased the accumulation of M1-type macrophages. Kartikasari et al. discovered that nanospikes on the surface of titanium dioxide nanospirals, produced by alkaline etching, specifically upregulated the gene markers iNOS and TNF-α.123,124 These nanospikes also significantly increased the expression of TLR2/4 genes representing M1-type macrophages, effectively converting macrophages into the M1-type.

The drugs mentioned in this context are distinct from those traditionally used for polarization in classical pathways. These drugs, such as simvastatin, vorinostat, and regorafenib (Rego), were not macrophage-polarizing agents initially, but have demonstrated significant effects on polarizing macrophage in studies, employing nanomaterials as carriers. Yin et al. illustrated the TME and TAMs phenotype-altering capability of simvastatin, and subsequently designed a liposome system.125 This system incorporated modified PD-L1 antibodies and co-encapsulated simvastatin with gefitinib. The objective was to counteract gefitinib resistance and enhance the antitumor efficacy of the drug by leveraging the repolarizing effect of simvastatin on TAMs.126 Wei et al. developed a bifunctional biorthogonal nanozyme utilizing the Fenton reaction activity of molybdenum sulfide.127 Ultra-small palladium nanoparticles were deposited on molybdenum sulfide, serving as active sites to catalyze the in-situ synthesis of HDACi vorinostat prodrugs. Combined with vorinostat, an FDA-approved drug known for repolarizing TAMs, this nanozyme approach significantly mitigated the toxic effects of vorinostat. The Fenton-ROS generated by molybdenum sulfide enhanced oxidative stress, induced damage to cancer cells, and facilitated changes in macrophage phenotype.

5. Summary and outlook

The immunosuppressive TME poses a significant challenge for drug resistance and desensitization. Targeting TAMs is considered a direct and effective strategy to address these issues, with a focus on two main directions. (1) Modulating the TAM phenotype. This involves altering the proportion of dominant cells in TAMs to reduce the number of M2-type cells and promote the creation of a pro-inflammatory microenvironment. (2) Enhancing macrophage phagocytosis. This approach aims to boost the phagocytic activity of macrophages, leading to the direct killing of tumor cells and facilitating the presentation of tumor-associated antigens. Nanomaterials exhibit high biocompatibility, offering solutions to challenges associated with TAMs modulators, including precise delivery, minimizing systemic side effects, and improving therapeutic efficacy.

The future research and development in the field can be broadly categorized into two main areas. (1) The combination of known anticancer drugs with immunomodulators. This involves using established anticancer drugs with proven efficacy in combination with agents designed to reshape the immunosuppressive microenvironment. The goal is to achieve enhanced drug efficacy and synergistic effects. The combination of nanomaterials with these immunomodulators can provide a comprehensive strategy for improving the TME, strengthening the body's natural defence mechanisms, and addressing issues such as tumor growth, metastasis, and recurrence. (2) The development of novel drugs and functions. This category focuses on expanding options for optimal drug delivery and synergistic enhancement by either developing entirely new drugs or uncovering new functions of existing drugs. Nanomaterials play a crucial role in this approach, facilitating precise drug delivery, minimizing side effects, and enhancing therapeutic efficacy. The aim is to explore innovative ways to modulate macrophage polarization, improve the immune response, and achieve better outcomes in cancer treatment.

Conclusions

There are three main approaches to utilizing nanomaterials for reducing the proportion of M2 cells in TAMs. (1) Pathway-specific modulation. This involves using activators or inhibitors to specifically target one or several pathways for M2 to M1 repolarization. Nanoparticles are often employed as carriers to modify delivery conditions, optimizing drug delivery efficiency. (2) Modulating key conditions in polarization. This approach aims to influence the polarization process by manipulating key conditions that affect the production of pro- or anti-inflammatory factors. For instance, iron oxide nanoparticles can promote M1 macrophage polarization by inducing the production of ROS through the Fenton reaction. (3) Interference with macrophages. Nanomaterials can interfere with macrophages by loading natural substances or synthetic substances that influence polarization. For example, exosomes from M1-type macrophages, rich in various pro-inflammatory factors, can effectively alter the phenotypic ratio of TAMs. Additionally, miRNA, siRNA, and plasmids can directly modify the expression of functional proteins or interfere with the maintenance of the M2 phenotype at the gene transcription level. In summary, the integration of nanomaterials with immunotherapies holds great promise for enhancing proinflammatory macrophage polarization, thereby improving the tumor microenvironment, boosting the body's natural defenses, and achieving more effective anti-tumor immune responses.

Author contributions

Chen Liang and Yihan Zhang conceptualised this systematic review. Chen Liang searched the literature and screened the titles and abstracts. Yihan Zhang, Siyao Wang, Nan Zhang and Xiaoli Liu reviewed all full-text articles. Siyao Wang, Wangbo Jiao and Jingyi Guo extracted the data. Chen Liang, Yihan Zhang, Wangbo Jiao and Nan Zhang did formal analysis of and visualised. Xiaoli Liu acquired funding. Xiaoli Liu were responsible for project administration. Nan Zhang and Xiaoli Liu supervised the systematic review. All authors were responsible for the methodology and review and editing of the manuscript. All authors debated, discussed, edited, and approved the final version of the manuscript. All authors had final responsibility for the decision to submit the manuscript for publication.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

This work was supported by the National Key Research and Development Program of China (Grant number: 2022YFC2408000), National Natural Science Foundation of China (NSFC) for Excellent Young Scientists (Grant number: 82322039), NSFC projects (Grant numbers: 82072063, 32001005, 32101136, and 82202306), Key Research and Development Program of Shaanxi Province (Grant number: 2023-YBSF-132), Shaanxi Province Youth Science and Technology New Star (Grant number: 2022KJXX-09), Natural Science Foundation of Shaanxi Province (Grant numbers: 2020JQ610), Medical-Engineering Cross Project of the First Affiliated Hospital of Xi’an Jiaotong University (Grant number: QYJC02), and Science Foundation of Nanjing Chia Tai Tianqing Project (Grant number: TQ202215).

References

  1. L. Maiorino, J. Dassler-Plenker, L. Sun and M. Egeblad, Annu. Rev. Pathol., 2022, 17, 425–457 CrossRef CAS PubMed.
  2. V. Kumar, S. Patel, E. Tcyganov and D. I. Gabrilovich, Trends Immunol., 2016, 37, 208–220 CrossRef CAS PubMed.
  3. O. W. H. Yeung, C.-M. Lo, C.-C. Ling, X. Qi, W. Geng, C.-X. Li, K. T. P. Ng, S. J. Forbes, X.-Y. Guan, R. T. P. Poon, S.-T. Fan and K. Man, J. Hepatol., 2015, 62, 607–616 CrossRef CAS PubMed.
  4. J. Wu, W. Gao, Q. Tang, Y. Yu, W. You, Z. Wu, Y. Fan, L. Zhang, C. Wu, G. Han, X. Zuo, Y. Zhang, Z. Chen, W. Ding, X. Li, F. Lin, H. Shen, J. Tang, Y. Zhang and X. Wang, Hepatology, 2021, 73, 1365–1380 CrossRef CAS PubMed.
  5. N. Horikawa, K. Abiko, N. Matsumura, J. Hamanishi, T. Baba, K. Yamaguchi, Y. Yoshioka, M. Koshiyama and I. Konishi, Clin. Cancer Res., 2017, 23, 587–599 CrossRef CAS PubMed.
  6. D. Alizadeh, M. Trad, N. T. Hanke, C. B. Larmonier, N. Janikashvili, B. Bonnotte, E. Katsanis and N. Larmonier, Cancer Res., 2014, 74, 104–118 CrossRef CAS PubMed.
  7. Q. Zhang, S. Liu, H. Wang, K. Xiao, J. Lu, S. Chen, M. Huang, R. Xie, T. Lin and X. Chen, Adv. Sci., 2023, 10 CAS.
  8. Y. Wang, Q. Zhao, B. Zhao, Y. Zheng, Q. Zhuang, N. Liao, P. Wang, Z. Cai, D. Zhang, Y. Zeng and X. Liu, Adv. Sci., 2022, 9 CAS.
  9. D. Henrik Heiland, V. M. Ravi, S. P. Behringer, J. H. Frenking, J. Wurm, K. Joseph, N. W. C. Garrelfs, J. Strähle, S. Heynckes, J. Grauvogel, P. Franco, I. Mader, M. Schneider, A.-L. Potthoff, D. Delev, U. G. Hofmann, C. Fung, J. Beck, R. Sankowski, M. Prinz and O. Schnell, Nat. Commun., 2019, 10 Search PubMed.
  10. M. Yi, J. Zhang, A. Li, M. Niu, Y. Yan, Y. Jiao, S. Luo, P. Zhou and K. Wu, J. Hematol. Oncol., 2021, 14 Search PubMed.
  11. T.-L. Yeung, C. S. Leung, K.-K. Wong, G. Samimi, M. S. Thompson, J. Liu, T. M. Zaid, S. Ghosh, M. J. Birrer and S. C. Mok, Cancer Res., 2013, 73, 5016–5028 CrossRef CAS PubMed.
  12. S. A. Lim, J. Wei, T.-L. M. Nguyen, H. Shi, W. Su, G. Palacios, Y. Dhungana, N. M. Chapman, L. Long, J. Saravia, P. Vogel and H. Chi, Nature, 2021, 591, 306–311 CrossRef CAS PubMed.
  13. N. Wang, H. Liang and K. Zen, Front. Immunol., 2014, 5, 614 Search PubMed.
  14. A. Shapouri-Moghaddam, S. Mohammadian, H. Vazini, M. Taghadosi, S. A. Esmaeili, F. Mardani, B. Seifi, A. Mohammadi, J. T. Afshari and A. Sahebkar, J. Cell. Physiol., 2018, 233, 6425–6440 CrossRef CAS PubMed.
  15. G. Maduraiveeran and W. Jin, Trends Environ. Anal. Chem., 2017, 13, 10–23 CrossRef CAS.
  16. M. Cao, R. Cai, L. Zhao, M. Guo, L. Wang, Y. Wang, L. Zhang, X. Wang, H. Yao, C. Xie, Y. Cong, Y. Guan, X. Tao, Y. Wang, S. Xu, Y. Liu, Y. Zhao and C. Chen, Nat. Nanotechnol., 2021, 16, 708–716 CrossRef CAS PubMed.
  17. Q. Chen, X. Ma, L. Xie, W. Chen, Z. Xu, E. Song, X. Zhu and Y. Song, Nanoscale, 2021, 13, 4855–4870 RSC.
  18. S. Bai, N. Yang, X. Wang, F. Gong, Z. Dong, Y. Gong, Z. Liu and L. Cheng, ACS Nano, 2020, 14, 15119–15130 CrossRef CAS PubMed.
  19. W. Ma, J. Mao, X. Yang, C. Pan, W. Chen, M. Wang, P. Yu, L. Mao and Y. Li, Chem. Commun., 2019, 55, 159–162 RSC.
  20. T. Fang, X. Cao, L. Wang, M. Chen, Y. Deng and G. Chen, Bioactive Mater., 2024, 32, 530–542 CrossRef CAS PubMed.
  21. Q. Cui, J.-Q. Wang, Y. G. Assaraf, L. Ren, P. Gupta, L. Wei, C. R. Ashby, D.-H. Yang and Z.-S. Chen, Drug Resist. Updates, 2018, 41, 1–25 CrossRef PubMed.
  22. Y. Wang, H. Xu, D. Wang, Y. Lu, Y. Zhang, J. Cheng, X. Xu, X. Chen and J. Li, Acta Biomater., 2024, 174, 358–371 CrossRef CAS PubMed.
  23. X. Zheng, Y. Liu, Y. Liu, J. Zang, K. Wang, Z. Yang, N. Chen, J. Sun, L. Huang, Y. Li, L. Xue, H. Zhi, X. Zhang, M. Yu, S. Chen, H. Dong and Y. Li, Biomaterials, 2024, 306, 122474 CrossRef CAS PubMed.
  24. R. A. Franklin, W. Liao, A. Sarkar, M. V. Kim, M. R. Bivona, K. Liu, E. G. Pamer and M. O. Li, Science, 2014, 344, 921–925 CrossRef CAS PubMed.
  25. Y. Lavin, A. Mortha, A. Rahman and M. Merad, Nat. Rev. Immunol., 2015, 15, 731–744 CrossRef CAS PubMed.
  26. S. Epelman, K. J. Lavine and G. J. Randolph, Immunity, 2014, 41, 21–35 CrossRef CAS PubMed.
  27. Z. Bian, Y. Gong, T. Huang, C. Z. W. Lee, L. Bian, Z. Bai, H. Shi, Y. Zeng, C. Liu, J. He, J. Zhou, X. Li, Z. Li, Y. Ni, C. Ma, L. Cui, R. Zhang, J. K. Y. Chan, L. G. Ng, Y. Lan, F. Ginhoux and B. Liu, Nature, 2020, 582, 571–576 CrossRef CAS PubMed.
  28. P. Italiani and D. Boraschi, Front. Immunol., 2014, 5, 514 Search PubMed.
  29. S. Saeed, J. Quintin, H. H. D. Kerstens, N. A. Rao, A. Aghajanirefah, F. Matarese, S.-C. Cheng, J. Ratter, K. Berentsen, M. A. van der Ent, N. Sharifi, E. M. Janssen-Megens, M. Ter Huurne, A. Mandoli, T. van Schaik, A. Ng, F. Burden, K. Downes, M. Frontini, V. Kumar, E. J. Giamarellos-Bourboulis, W. H. Ouwehand, J. W. M. van der Meer, L. A. B. Joosten, C. Wijmenga, J. H. A. Martens, R. J. Xavier, C. Logie, M. G. Netea and H. G. Stunnenberg, Science, 2014, 345 Search PubMed.
  30. F. Ginhoux, J. L. Schultze, P. J. Murray, J. Ochando and S. K. Biswas, Nat. Immunol., 2015, 17, 34–40 CrossRef PubMed.
  31. W. J. Kaiser, H. Sridharan, C. Huang, P. Mandal, J. W. Upton, P. J. Gough, C. A. Sehon, R. W. Marquis, J. Bertin and E. S. Mocarski, J. Biol. Chem., 2013, 288, 31268–31279 CrossRef CAS PubMed.
  32. D. Hirayama, T. Iida and H. Nakase, Int. J. Mol. Sci., 2017, 19 Search PubMed.
  33. Z. Asadzadeh, E. Safarzadeh, S. Safaei, A. Baradaran, A. Mohammadi, K. Hajiasgharzadeh, A. Derakhshani, A. Argentiero, N. Silvestris and B. Baradaran, Cancers, 2020, 12 Search PubMed.
  34. D. Fraccarollo, R. Geffers, P. Galuppo and J. Bauersachs, Basic Res. Cardiol., 2024, 119, 243–260 CrossRef CAS PubMed.
  35. F. A. W. Verreck, T. de Boer, D. M. L. Langenberg, M. A. Hoeve, M. Kramer, E. Vaisberg, R. Kastelein, A. Kolk, R. de Waal-Malefyt and T. H. M. Ottenhoff, Proc. Natl. Acad. Sci. U. S. A., 2004, 101, 4560–4565 CrossRef CAS PubMed.
  36. F. O. Martinez, L. Helming and S. Gordon, Annu. Rev. Immunol., 2009, 27, 451–483 CrossRef CAS PubMed.
  37. S. Spranger and T. F. Gajewski, Nat. Rev. Cancer, 2018, 18, 139–147 CrossRef CAS PubMed.
  38. S. Jhunjhunwala, C. Hammer and L. Delamarre, Nat. Rev. Cancer, 2021, 21, 298–312 CrossRef CAS PubMed.
  39. J. G. Abelin, D. B. Keskin, S. Sarkizova, C. R. Hartigan, W. Zhang, J. Sidney, J. Stevens, W. Lane, G. L. Zhang, T. M. Eisenhaure, K. R. Clauser, N. Hacohen, M. S. Rooney, S. A. Carr and C. J. Wu, Immunity, 2017, 46, 315–326 CrossRef CAS PubMed.
  40. S. Wang, Z. He, X. Wang, H. Li and X.-S. Liu, eLife, 2019, 8 Search PubMed.
  41. E. Alspach, D. M. Lussier, A. P. Miceli, I. Kizhvatov, M. DuPage, A. M. Luoma, W. Meng, C. F. Lichti, E. Esaulova, A. N. Vomund, D. Runci, J. P. Ward, M. M. Gubin, R. F. V. Medrano, C. D. Arthur, J. M. White, K. C. F. Sheehan, A. Chen, K. W. Wucherpfennig, T. Jacks, E. R. Unanue, M. N. Artyomov and R. D. Schreiber, Nature, 2019, 574, 696–701 CrossRef CAS PubMed.
  42. M. Saxena, S. H. van der Burg, C. J. M. Melief and N. Bhardwaj, Nat. Rev. Cancer, 2021, 21, 360–378 CrossRef CAS PubMed.
  43. H. H. Van Acker, M. Versteven, F. S. Lichtenegger, G. Roex, D. Campillo-Davo, E. Lion, M. Subklewe, V. F. Van Tendeloo, Z. N. Berneman and S. Anguille, J. Clin. Med., 2019, 8, 579 CrossRef CAS PubMed.
  44. J. Liu, M. Fu, M. Wang, D. Wan, Y. Wei and X. Wei, J. Hematol. Oncol., 2022, 15, 28 CrossRef PubMed.
  45. J. Yu, H. Sun, W. Cao, Y. Song and Z. Jiang, Exp. Hematol. Oncol., 2022, 11, 3 CrossRef CAS PubMed.
  46. S. Anguille, Y. Willemen, E. Lion, E. L. Smits and Z. N. Berneman, Cytotherapy, 2012, 14, 647–656 CrossRef CAS PubMed.
  47. N. P. Restifo, M. E. Dudley and S. A. Rosenberg, Nat. Rev. Immunol., 2012, 12, 269–281 CrossRef CAS PubMed.
  48. Z. Bai, Y. Zhou, Z. Ye, J. Xiong, H. Lan and F. Wang, Front. Immunol., 2021, 12, 808964 CrossRef CAS PubMed.
  49. B. Lin, L. Du, H. Li, X. Zhu, L. Cui and X. Li, Biomed. Pharmacother., 2020, 132, 110873 CrossRef CAS PubMed.
  50. L. Zhao and Y. J. Cao, Front. Immunol., 2019, 10, 2250 CrossRef CAS PubMed.
  51. Z. Niu, G. Chen, W. Chang, P. Sun, Z. Luo, H. Zhang, L. Zhi, C. Guo, H. Chen, M. Yin and W. Zhu, J. Pathol., 2020, 253, 247–257 CrossRef PubMed.
  52. T. Zhang, H. Ma, X. Zhang, S. Shi and Y. Lin, Adv. Funct. Mater., 2023, 33, 2213401 CrossRef CAS.
  53. W. Zhang, L. Liu, H. Su, Q. Liu, J. Shen, H. Dai, W. Zheng, Y. Lu, W. Zhang, Y. Bei and P. Shen, Br. J. Cancer, 2019, 121, 837–845 CrossRef CAS PubMed.
  54. S. Zanganeh, G. Hutter, R. Spitler, O. Lenkov, M. Mahmoudi, A. Shaw, J. S. Pajarinen, H. Nejadnik, S. Goodman, M. Moseley, L. M. Coussens and H. E. Daldrup-Link, Nat. Nanotechnol., 2016, 11, 986–994 CrossRef CAS PubMed.
  55. P. Conde, M. Rodriguez, W. van der Touw, A. Jimenez, M. Burns, J. Miller, M. Brahmachary, H.-M. Chen, P. Boros, F. Rausell-Palamos, T. J. Yun, P. Riquelme, A. Rastrojo, B. Aguado, J. Stein-Streilein, M. Tanaka, L. Zhou, J. Zhang, T. L. Lowary, F. Ginhoux, C. G. Park, C. Cheong, J. Brody, S. J. Turley, S. A. Lira, V. Bronte, S. Gordon, P. S. Heeger, M. Merad, J. Hutchinson, S.-H. Chen and J. Ochando, Immunity, 2015, 42, 1143–1158 CrossRef CAS PubMed.
  56. S. M. Abdin, D. Paasch, A. Kloos, M. C. Oliveira, M.-S. Jang, M. Ackermann, A. Stamopoulou, P. J. Mroch, C. S. Falk, C. S. von Kaisenberg, A. Schambach, M. Heuser, T. Moritz, G. Hansen, M. Morgan and N. Lachmann, J. Immunother. Cancer, 2023, 11, e007705 CrossRef PubMed.
  57. I. Larionova, G. Tuguzbaeva, A. Ponomaryova, M. Stakheyeva, N. Cherdyntseva, V. Pavlov, E. Choinzonov and J. Kzhyshkowska, Front. Oncol., 2020, 10, 566511 CrossRef PubMed.
  58. Y. Komohara, Y. Fujiwara, K. Ohnishi and M. Takeya, Adv. Drug Delivery Rev., 2016, 99, 180–185 CrossRef CAS PubMed.
  59. R. H. Deng, M. Z. Zou, D. Zheng, S. Y. Peng, W. Liu, X. F. Bai, H. S. Chen, Y. Sun, P. H. Zhou and X. Z. Zhang, ACS Nano, 2019, 13, 8618–8629 CrossRef CAS PubMed.
  60. Y. Sang, Q. Deng, F. Cao, Z. Liu, Y. You, H. Liu, J. Ren and X. Qu, ACS Nano, 2021, 15, 19298–19309 CrossRef CAS PubMed.
  61. T. Kawasaki and T. Kawai, Front. Immunol., 2014, 5, 461 Search PubMed.
  62. W. Gao, Y. Xiong, Q. Li and H. Yang, Front. Physiol., 2017, 8, 508 CrossRef PubMed.
  63. T. Duan, Y. Du, C. Xing, H. Y. Wang and R. F. Wang, Front. Immunol., 2022, 13, 812774 CrossRef CAS PubMed.
  64. B. Wei, J. Pan, R. Yuan, B. Shao, Y. Wang, X. Guo and S. Zhou, Nano Lett., 2021, 21, 4231–4240 CrossRef CAS PubMed.
  65. S. Y. Kim, S. Kim, J. E. Kim, S. N. Lee, I. W. Shin, H. S. Shin, S. M. Jin, Y. W. Noh, Y. J. Kang, Y. S. Kim, T. H. Kang, Y. M. Park and Y. T. Lim, ACS Nano, 2019, 13, 12671–12686 CrossRef CAS PubMed.
  66. C. Ravindran, Y. C. Cheng and S. M. Liang, Cell. Immunol., 2010, 260, 113–118 CrossRef CAS PubMed.
  67. H. Shan, W. Dou, Y. Zhang and M. Qi, Nanoscale, 2020, 12, 22268–22280 RSC.
  68. H. M. Wu, J. Wang, B. Zhang, L. Fang, K. Xu and R. Y. Liu, Life Sci., 2016, 161, 51–59 CrossRef CAS PubMed.
  69. H. R. Chinnery, S. McLenachan, N. Binz, Y. Sun, J. V. Forrester, M. A. Degli-Esposti, E. Pearlman and P. G. McMenamin, Am. J. Pathol., 2012, 180, 209–220 CrossRef CAS PubMed.
  70. H. Cai, S. Shukla and N. F. Steinmetz, Adv. Funct. Mater., 2020, 30, 1908743 CrossRef CAS PubMed.
  71. R. Chen, J. Wang, X. Dai, S. Wu, Q. Huang, L. Jiang and X. Kong, Arthritis Res. Ther., 2022, 24, 266 CrossRef CAS PubMed.
  72. N. Huangfu, W. Zheng, Z. Xu, S. Wang, Y. Wang, J. Cheng, Z. Li, K. Cheng, S. Zhang, X. Chen and J. Zhu, Int. Immunopharmacol., 2020, 83, 106432 CrossRef PubMed.
  73. T. Maj, W. Wang, J. Crespo, H. Zhang, W. Wang, S. Wei, L. Zhao, L. Vatan, I. Shao, W. Szeliga, C. Lyssiotis, J. R. Liu, I. Kryczek and W. Zou, Nat. Immunol., 2017, 18, 1332–1341 CrossRef CAS PubMed.
  74. X. Fu, Y. Huang, H. Zhao, E. Zhang, Q. Shen, Y. Di, F. Lv, L. Liu and S. Wang, Adv. Mater., 2021, 33, e2102570 CrossRef PubMed.
  75. J. Chen, Y. Dou, Y. Tang and X. Zhang, Nanomedicine, 2020, 25, 102173 CrossRef CAS PubMed.
  76. J. Chen, Y. Dou, Y. Tang and X. Zhang, Nanomedicine, 2020, 25, 102173 CrossRef CAS PubMed.
  77. H. Xiao, Y. Guo, B. Li, X. Li, Y. Wang, S. Han, D. Cheng and X. Shuai, ACS Cent. Sci., 2020, 6, 1208–1222 CrossRef CAS PubMed.
  78. J. Cui, X. Wang, J. Li, A. Zhu, Y. Du, W. Zeng, Y. Guo, L. Di and R. Wang, ACS Nano, 2023, 17, 1464–1484 CrossRef CAS PubMed.
  79. Y. C. Wang, F. He, F. Feng, X. W. Liu, G. Y. Dong, H. Y. Qin, X. B. Hu, M. H. Zheng, L. Liang, L. Feng, Y. M. Liang and H. Han, Cancer Res., 2010, 70, 4840–4849 CrossRef CAS PubMed.
  80. Y. Lin, J. L. Zhao, Q. J. Zheng, X. Jiang, J. Tian, S. Q. Liang, H. W. Guo, H. Y. Qin, Y. M. Liang and H. Han, Front. Immunol., 2018, 9, 1744 CrossRef PubMed.
  81. D. F. Tschaharganeh, X. Chen, P. Latzko, M. Malz, M. M. Gaida, K. Felix, S. Ladu, S. Singer, F. Pinna, N. Gretz, C. Sticht, M. L. Tomasi, S. Delogu, M. Evert, B. Fan, S. Ribback, L. Jiang, S. Brozzetti, F. Bergmann, F. Dombrowski, P. Schirmacher, D. F. Calvisi and K. Breuhahn, Gastroenterology, 2013, 144, 1530–1542 CrossRef CAS PubMed.
  82. A. A. Svoronos, D. M. Engelman and F. J. Slack, Cancer Res., 2016, 76, 3666–3670 CrossRef CAS PubMed.
  83. A. Thind and C. Wilson, J. Extracell. Vesicles, 2016, 5, 31292 CrossRef PubMed.
  84. J. S. Erdem, T. Závodná, T. K. Ervik, Ø. Skare, T. Hron, K. H. Anmarkrud, A. Kuśnierczyk, J. Catalán, D. G. Ellingsen, J. Topinka and S. Zienolddiny-Narui, Front. Immunol., 2023, 14, 1111123 CrossRef CAS PubMed.
  85. M. Zhao, A. Zhuang and Y. Fang, J. Oncol., 2022, 2022, 9514697 Search PubMed.
  86. N. Chen, L. Feng, K. Lu, P. Li, X. Lv and X. Wang, Oncol. Lett., 2019, 18, 95–100 CAS.
  87. R. T. Martinez-Nunez, F. Louafi and T. Sanchez-Elsner, J. Biol. Chem., 2011, 286, 1786–1794 CrossRef CAS PubMed.
  88. L. Yang, J. Sun, Q. Liu, R. Zhu, Q. Yang, J. Hua, L. Zheng, K. Li, S. Wang and A. Li, Adv. Sci., 2019, 6, 1802012 CrossRef PubMed.
  89. X. Zang, X. Zhang, X. Zhao, H. Hu, M. Qiao, Y. Deng and D. Chen, Mol. Pharm., 2019, 16, 1714–1722 CrossRef CAS PubMed.
  90. W. Tai, Molecules, 2019, 24 Search PubMed.
  91. W. Tai, J. Controlled Release, 2019, 307, 98–107 CrossRef CAS PubMed.
  92. S. Cao, P. E. Saw, Q. Shen, R. Li, Y. Liu and X. Xu, Biomaterials, 2022, 280, 121264 CrossRef CAS PubMed.
  93. T. Huang, Q. Feng, Z. Wang, W. Li, Z. Sun, J. Wilhelm, G. Huang, T. Vo, B. D. Sumer and J. Gao, Adv. Healthcare Mater., 2021, 10, e2000549 CrossRef PubMed.
  94. A. M. Reuss, D. Groos, M. Buchfelder and N. Savaskan, Int. J. Mol. Sci., 2021, 22, 5518 CrossRef CAS PubMed.
  95. K. Li, C. Lin, Y. He, L. Lu, K. Xu, B. Tao, Z. Xia, R. Zeng, Y. Mao, Z. Luo and K. Cai, ACS Nano, 2020, 14, 14164–14180 CrossRef CAS PubMed.
  96. S. Wang, Y. Xiao, J. Tian, B. Dai, Z. Tao, J. Liu, Z. Sun, X. Liu, Y. Li, G. Zhao, Y. Cui, F. Wang and S. Liu, Adv. Mater., 2024, 2311964,  DOI:10.1002/adma.202311964.
  97. Z. Yang, J. Shi, J. Xie, Y. Wang, J. Sun, T. Liu, Y. Zhao, X. Zhao, X. Wang, Y. Ma, V. Malkoc, C. Chiang, W. Deng, Y. Chen, Y. Fu, K. J. Kwak, Y. Fan, C. Kang, C. Yin, J. Rhee, P. Bertani, J. Otero, W. Lu, K. Yun, A. S. Lee, W. Jiang, L. Teng, B. Y. S. Kim and L. J. Lee, Nat. Biomed. Eng., 2020, 4, 69–83 CrossRef CAS PubMed.
  98. F. Zhang, N. N. Parayath, C. I. Ene, S. B. Stephan, A. L. Koehne, M. E. Coon, E. C. Holland and M. T. Stephan, Nat. Commun., 2019, 10, 3974 CrossRef CAS PubMed.
  99. L. Liu, H. Yi, H. He, H. Pan, L. Cai and Y. Ma, Biomaterials, 2017, 134, 166–179 CrossRef CAS PubMed.
  100. M. J. Su, H. Aldawsari and M. Amiji, Sci. Rep., 2016, 6, 30110 CrossRef CAS PubMed.
  101. N. N. Parayath, A. Parikh and M. M. Amiji, Nano Lett., 2018, 18, 3571–3579 CrossRef CAS PubMed.
  102. M. Trivedi, M. Talekar, P. Shah, Q. Ouyang and M. Amiji, Oncogenesis, 2016, 5, e250 CrossRef CAS PubMed.
  103. M. Talekar, M. Trivedi, P. Shah, Q. Ouyang, A. Oka, S. Gandham and M. M. Amiji, Mol. Ther., 2016, 24, 759–769 CrossRef CAS PubMed.
  104. M. B. Deci, M. Liu, J. Gonya, C. J. Lee, T. Li, S. W. Ferguson, E. E. Bonacquisti, J. Wang and J. Nguyen, Cell. Mol. Bioeng., 2019, 12, 375–388 CrossRef CAS PubMed.
  105. Q. Guo, X. Li, W. Zhou, Y. Chu, Q. Chen, Y. Zhang, C. Li, H. Chen, P. Liu, Z. Zhao, Y. Wang, Z. Zhou, Y. Luo, C. Li, H. You, H. Song, B. Su, T. Zhang, T. Sun and C. Jiang, ACS Nano, 2021, 15, 13826–13838 CrossRef CAS PubMed.
  106. J. Xi, R. Zhang, L. Wang, W. Xu, Q. Liang, J. Li, J. Jiang, Y. Yang, X. Yan, K. Fan and L. Gao, Adv. Funct. Mater., 2020, 31 CAS.
  107. G. E. Villalpando-Rodriguez, S. B. Gibson and J. Tejero, Oxid. Med. Cell. Longevity, 2021, 1–17 Search PubMed.
  108. S.-M. Jin, H. S. Lee, M. R. Haque, H. N. Kim, H. J. Kim, B. J. Oh, K. W. Lee, G. Kim, H. S. Kim, D. Y. Lee, J. B. Park, S. J. Kim, Y. Byun and J. H. Kim, Biomaterials, 2019, 214 Search PubMed.
  109. M. Z. Zou, W. L. Liu, F. Gao, X. F. Bai, H. S. Chen, X. Zeng and X. Z. Zhang, Adv. Mater., 2019, 31, e1904495 CrossRef PubMed.
  110. X. Liu, B. Yan, Y. Li, X. Ma, W. Jiao, K. Shi, T. Zhang, S. Chen, Y. He, X. J. Liang and H. Fan, ACS Nano, 2020, 14, 1936–1950 CrossRef CAS PubMed.
  111. H. Cheng, X. Fan, E. Ye, H. Chen, J. Yang, L. Ke, M. You, M. Liu, Y. W. Zhang, Y. L. Wu, G. Liu, X. J. Loh and Z. Li, Adv. Mater., 2022, 34, e2107674 CrossRef PubMed.
  112. X. Zhang, X. Yuan, H. Shi, L. Wu, H. Qian and W. Xu, J. Hematol. Oncol., 2015, 8, 83 CrossRef PubMed.
  113. D. Jafari, S. Shajari, R. Jafari, N. Mardi, H. Gomari, F. Ganji, M. Forouzandeh Moghadam and A. Samadikuchaksaraei, BioDrugs, 2020, 34, 567–586 CrossRef PubMed.
  114. R. Munagala, F. Aqil, J. Jeyabalan and R. C. Gupta, Cancer Lett., 2016, 371, 48–61 CrossRef CAS PubMed.
  115. R. A. Haraszti, M. C. Didiot, E. Sapp, J. Leszyk, S. A. Shaffer, H. E. Rockwell, F. Gao, N. R. Narain, M. DiFiglia, M. A. Kiebish, N. Aronin and A. Khvorova, J. Extracell. Vesicles, 2016, 5, 32570 CrossRef PubMed.
  116. H. Chen, S. Jiang, P. Zhang, Z. Ren and J. Wen, Int. Immunopharmacol., 2021, 99, 107960 CrossRef CAS PubMed.
  117. Y. W. Choo, M. Kang, H. Y. Kim, J. Han, S. Kang, J. R. Lee, G. J. Jeong, S. P. Kwon, S. Y. Song, S. Go, M. Jung, J. Hong and B. S. Kim, ACS Nano, 2018, 12, 8977–8993 CrossRef CAS PubMed.
  118. G. Deng, Z. Sun, S. Li, X. Peng, W. Li, L. Zhou, Y. Ma, P. Gong and L. Cai, ACS Nano, 2018, 12, 12096–12108 CrossRef CAS PubMed.
  119. C. Wan, Y. Sun, Y. Hu, J. Huang, L. Lu, Y. Gao, H. Zi, Q. He, J. Sun, J. F. Lovell, K. Yang and H. Jin, Nano Today, 2021, 41, 101323 CrossRef CAS.
  120. J. Ou, M. Zhu, X. Ju, D. Xu, G. Lu, K. Li, W. Jiang, C. Wan, Y. Zhao, Y. Han, Y. Tian and Z. Niu, Nano Lett., 2023, 23, 2056–2064 CrossRef CAS PubMed.
  121. X. Dai, J. Ruan, Y. Guo, Z. Sun, J. Liu, X. Bao, H. Zhang, Q. Li, C. Ye, X. Wang, C.-X. Zhao, F. Zhou, J. Sheng, D. Chen and P. Zhao, Chem. Eng. J., 2021, 422, 130109 CrossRef CAS.
  122. Z. Ma, M. Yang, M. F. Foda, K. Zhang, S. Li, H. Liang, Y. Zhao and H. Han, ACS Nano, 2022, 16, 17389–17401 CrossRef CAS PubMed.
  123. N. Kartikasari, M. Yamada, J. Watanabe, W. Tiskratok, X. He and H. Egusa, Sci. Rep., 2022, 12, 12250 CrossRef CAS PubMed.
  124. N. Kartikasari, M. Yamada, J. Watanabe, W. Tiskratok, X. He, Y. Kamano and H. Egusa, Acta Biomater., 2022, 137, 316–330 CrossRef CAS PubMed.
  125. M. C. Alupei, E. Licarete, L. Patras and M. Banciu, Cancer Lett., 2015, 356, 946–952 CrossRef CAS PubMed.
  126. W. Yin, X. Yu, X. Kang, Y. Zhao, P. Zhao, H. Jin, X. Fu, Y. Wan, C. Peng and Y. Huang, Small, 2018, 14, e1802372 CrossRef PubMed.
  127. Y. Wei, S. Wu, Z. Liu, J. Niu, Y. Zhou, J. Ren and X. Qu, Mater. Today, 2022, 56, 16–28 CrossRef CAS.

Footnote

These authors contributed equally to this work and should be considered cofirst authors.

This journal is © The Royal Society of Chemistry 2024
Click here to see how this site uses Cookies. View our privacy policy here.