# Precision engineering of macrophage reprogramming with RNA interference-loaded lipid nanoparticles: a game-changer in cancer immunotherapy

Sezen Gül, Juliette Vergnaud, François Fay, Elias Fattal

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Sezen Gül, Juliette Vergnaud, François Fay, Elias Fattal. Precision engineering of macrophage reprogramming with RNA interference-loaded lipid nanoparticles: a game-changer in cancer immunotherapy. Drug Delivery and Translational Research, In press, 10.1007/s13346-025-01970-1. hal-05272960

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Submitted on 22 Sep 2025

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# Precision engineering of macrophage reprogramming with RNA interference-loaded lipid nanoparticles: a game-changer in cancer immunotherapy

Sezen Gül<fnref n="1" /> · Juliette Vergnaud<fnref n="1" /> · François Fay<fnref n="1" /> · Elias Fattal<fnref n="1" />

Received: 16 April 2025 / Accepted: 8 September 2025

© The Author(s) 2025

## Abstract

Tumor-associated macrophages (TAMs) represent solid tumors' most prevalent immune cell subset. These cells primarily adopt an immunosuppressive phenotype in the tumor microenvironment, promoting tumor initiation and progression. Their ability to shift between distinct activation states identifies TAMs as ideal targets for cancer treatment. Consequently, reprogramming TAMs from an immunosuppressive to an immunostimulatory state has emerged as a promising therapeutic approach to fight cancer. RNA interference has gained significant attention as a therapeutic modality due to its potential to selectively inhibit the expression of one or several critical proteins for the pro-tumorous activities of TAMs. However, the efficiency of RNA interference is limited by its susceptibility to nuclease degradation, rapid clearance from the body, and poor cellular uptake. These limitations necessitate the development of delivery systems to enhance their therapeutic potential. Among the nanocarriers we discuss in this review, lipid nanoparticles (LNPs) have been widely recognized as the most effective for siRNA or miRNA, providing stability, high gene silencing efficiency, and biocompatibility. The clinical application of LNPs has been further advanced by recent progress in microfluidics, enabling reproducible and scalable production of LNPs with high encapsulation efficiency. The increasing number of preclinical studies shows the growing interest in cancer immunotherapy using RNA interference-LNPs. In this review, we summarize the current knowledge on macrophage biology and its role in cancer, explore advancements in RNA interference-LNP technology, review ongoing research efforts, and discuss key translational challenges that must be addressed for the clinical success of RNA interference-LNP-based macrophage reprogramming.

**Keywords** Tumor-associated macrophages · Reprogramming · Lipid nanoparticles · RNA interference

## Abbreviations

<table><tr><td>ADA</td><td>Anti-drug antibody</td></tr><tr><td>ADCC</td><td>Antibody-dependent cellular cytotoxicity</td></tr><tr><td>ADCP</td><td>Antibody-dependent cellular phagocytosis</td></tr><tr><td>Ago2</td><td>Argonaute-2</td></tr><tr><td>ANG2</td><td>Angiopoietin-2</td></tr><tr><td>ApoE</td><td>Apolipoprotein E</td></tr><tr><td>Arg1</td><td>Arginase-1</td></tr></table>

<table><tr><td>BMDM</td><td>Bone marrow-derived macrophage</td></tr><tr><td>C3 (or 5)</td><td>Complement component 3 (or 5)</td></tr><tr><td>CAR</td><td>Chimeric antigen receptor</td></tr><tr><td>CARPA</td><td>Complement activation-related pseudo allergy</td></tr><tr><td>Cas9</td><td>CRISPR-associated protein 9</td></tr><tr><td>CCL</td><td>C-C chemokine ligand</td></tr><tr><td>CCR</td><td>C-C chemokine receptor</td></tr><tr><td>CD</td><td>Cluster of differentiation</td></tr><tr><td>CD169</td><td>Sialic acid binding Ig-like lectin 1 (also known as Siglec-1)</td></tr><tr><td>CD206</td><td>Cluster of differentiation 206 (also known as mannose receptor)</td></tr><tr><td>cGAMP</td><td>Cyclic guanosine monophosphate-adenosine monophosphate</td></tr><tr><td>CHOL</td><td>Cholesterol</td></tr></table>

<figure><img src="image_3.png" /></figure>

<footnote>Elias Fattal
elias.fattal@universite-paris-saclay.fr</footnote>

<footnote n="1">¹ Université Paris-Saclay, CNRS, Institut Galien Paris-Saclay, Orsay 91400, France</footnote>
<table>
  <tr>
    <td>COVID-19</td>
    <td>Coronavirus disease 2019</td>
    <td>KLF4</td>
    <td>Kruppel-like factor 4</td>
  </tr>
  <tr>
    <td>COX-2</td>
    <td>Cyclooxygenase-2</td>
    <td>Lamp1</td>
    <td>Lysosomal-associated membrane protein 1</td>
  </tr>
  <tr>
    <td>CpG</td>
    <td>Cytosine-phosphate-guanine</td>
    <td>LDLR</td>
    <td>Low-density lipoprotein receptor</td>
  </tr>
  <tr>
    <td>CPP</td>
    <td>Cell-penetrating peptide</td>
    <td>LNP</td>
    <td>Lipid nanoparticle</td>
  </tr>
  <tr>
    <td>CRISPR</td>
    <td>Clustered regularly interspaced short palindromic repeats</td>
    <td>LPS</td>
    <td>Lipopolysaccharide</td>
  </tr>
  <tr>
    <td>CSF-1</td>
    <td>Colony-stimulating factor 1</td>
    <td>M2pep</td>
    <td>M2-targeting peptide</td>
  </tr>
  <tr>
    <td>CSF-1R</td>
    <td>Colony-stimulating factor 1 receptor</td>
    <td>MARCO</td>
    <td>Macrophage receptor with collagenous structure</td>
  </tr>
  <tr>
    <td>CXCL</td>
    <td>C-X-C motif chemokine ligand</td>
    <td>MDSC</td>
    <td>Myeloid-derived suppressor cell</td>
  </tr>
  <tr>
    <td>DAMPs</td>
    <td>Damage-associated molecular patterns</td>
    <td>MerTK</td>
    <td>MER proto-oncogene tyrosine kinase</td>
  </tr>
  <tr>
    <td>DCs</td>
    <td>Dendritic cells</td>
    <td>MHC II</td>
    <td>Major histocompatibility complex II</td>
  </tr>
  <tr>
    <td>DLin-MC3-DMA</td>
    <td>(6Z,9Z,28Z,31Z)-Heptatriaconta-6,9,28,31-tetraen-19-yl 4-(dimethyl-amino)butanoate</td>
    <td>miRNA</td>
    <td>MicroRNA</td>
  </tr>
  <tr>
    <td>DMG</td>
    <td>1,2-dimyristoyl-sn-glycerol</td>
    <td>MMP</td>
    <td>Matrix metalloproteinase</td>
  </tr>
  <tr>
    <td>DOPE</td>
    <td>1,2-dioleoyl-sn-glycero-3-phospho-ethanolamine</td>
    <td>MPS</td>
    <td>Mononuclear phagocyte system</td>
  </tr>
  <tr>
    <td>DOTAP</td>
    <td>1,2-dioleoyl-3-trimethylammonium-propane</td>
    <td>mRNA</td>
    <td>Messenger RNA</td>
  </tr>
  <tr>
    <td>DSG</td>
    <td>1,2-distearoyl-sn-glycerol</td>
    <td>NF-κB</td>
    <td>Nuclear factor kappa B</td>
  </tr>
  <tr>
    <td>DSPC</td>
    <td>Distearolyphosphatidylcholine</td>
    <td>NK cells</td>
    <td>Natural killer cells</td>
  </tr>
  <tr>
    <td>dsRNA</td>
    <td>Double-stranded RNA</td>
    <td>NO</td>
    <td>Nitric oxide</td>
  </tr>
  <tr>
    <td>EC</td>
    <td>European Commission</td>
    <td>NPC1</td>
    <td>Niemann-Pick type C1</td>
  </tr>
  <tr>
    <td>ECM</td>
    <td>Extracellular matrix</td>
    <td>OX40L</td>
    <td>OX40 ligand</td>
  </tr>
  <tr>
    <td>EEA1</td>
    <td>Early endosome antigen 1</td>
    <td>PD-1</td>
    <td>Programmed cell death protein 1</td>
  </tr>
  <tr>
    <td>EGF</td>
    <td>Epidermal growth factor</td>
    <td>PDGF</td>
    <td>Platelet-derived growth factor</td>
  </tr>
  <tr>
    <td>EPR</td>
    <td>Enhanced permeability and retention</td>
    <td>PD-L1</td>
    <td>Programmed cell death ligand 1</td>
  </tr>
  <tr>
    <td>FDA</td>
    <td>United States Food and Drug Administration</td>
    <td>PEG</td>
    <td>Polyethylene glycol</td>
  </tr>
  <tr>
    <td>FGF</td>
    <td>Fibroblast growth factor</td>
    <td>PI3K</td>
    <td>Phosphoinositide 3 kinase</td>
  </tr>
  <tr>
    <td>Fizz1</td>
    <td>Found in inflammatory zone 1 (also known as Retnla)</td>
    <td>pK<sub>a</sub></td>
    <td>Acid dissociation constant</td>
  </tr>
  <tr>
    <td>GM-CSF</td>
    <td>Granulocyte-macrophage colony-stimulating factor</td>
    <td>PO4</td>
    <td>Phosphodiester</td>
  </tr>
  <tr>
    <td>HA2</td>
    <td>Hemagglutinin 2</td>
    <td>PPAR</td>
    <td>Peroxisome proliferator-activated receptor gamma</td>
  </tr>
  <tr>
    <td>hATTR</td>
    <td>Hereditary transthyretin amyloidosis</td>
    <td>PRR</td>
    <td>Pattern recognition receptor</td>
  </tr>
  <tr>
    <td>HIF</td>
    <td>Hypoxia-inducible factor</td>
    <td>PS</td>
    <td>Phosphorotioate</td>
  </tr>
  <tr>
    <td>HIV-1 TAT</td>
    <td>Human immunodeficiency virus type 1 trans-activator of transcription</td>
    <td>PV L2</td>
    <td>L2 protein of papillomavirus</td>
  </tr>
  <tr>
    <td>HO1</td>
    <td>Heme oxygenase-1</td>
    <td>Rab</td>
    <td>Ras-associated protein</td>
  </tr>
  <tr>
    <td>IDO</td>
    <td>Indoleamine 2,3-dioxygenase</td>
    <td>RelA</td>
    <td>Nuclear factor kappa-B p65 subunit (also known as p65)</td>
  </tr>
  <tr>
    <td>IFN-γ</td>
    <td>Interferon-gamma</td>
    <td>RGD</td>
    <td>Arginine-glycine-aspartic acid</td>
  </tr>
  <tr>
    <td>Ig</td>
    <td>Immunoglobulin</td>
    <td>RISC</td>
    <td>RNA-induced silencing complex</td>
  </tr>
  <tr>
    <td>IKK</td>
    <td>IκB kinase</td>
    <td>RNAi</td>
    <td>RNA interference</td>
  </tr>
  <tr>
    <td>IL</td>
    <td>Interleukin</td>
    <td>ROS</td>
    <td>Reactive oxygen species</td>
  </tr>
  <tr>
    <td>iNOS</td>
    <td>Inducible nitric oxide synthase</td>
    <td>siRNA</td>
    <td>Small interfering RNA</td>
  </tr>
  <tr>
    <td>IRF</td>
    <td>Interferon regulatory factor</td>
    <td>siRNA-LNP</td>
    <td>SiRNA-loaded LNPs</td>
  </tr>
  <tr>
    <td>IT</td>
    <td>Intratumoral</td>
    <td>SIRPα</td>
    <td>Signal-regulatory protein alpha</td>
  </tr>
  <tr>
    <td>IV</td>
    <td>Intravenous</td>
    <td>SNALP</td>
    <td>Stable nucleic acid-lipid nanoparticle</td>
  </tr>
  <tr>
    <td>IκBα</td>
    <td>Inhibitor of nuclear factor kappa B alpha</td>
    <td>STAT</td>
    <td>Signal transducer and activator of transcription</td>
  </tr>
  <tr>
    <td>JAK</td>
    <td>Janus kinase</td>
    <td>STING</td>
    <td>Stimulator of interferon genes</td>
  </tr>
  <tr>
    <td></td>
    <td></td>
    <td>TAMs</td>
    <td>Tumor-associated macrophages</td>
  </tr>
  <tr>
    <td></td>
    <td></td>
    <td>TGF-β</td>
    <td>Transforming growth factor beta</td>
  </tr>
  <tr>
    <td></td>
    <td></td>
    <td>TIE2</td>
    <td>Tyrosine kinase with immunoglobulin and EGF homology domains 2</td>
  </tr>
  <tr>
    <td></td>
    <td></td>
    <td>TIM-3</td>
    <td>T-cell immunoglobulin and</td>
  </tr>
</table>
<table><tr><td>TLR</td><td>mucin-domain containing 3</td></tr><tr><td>T<sub>m</sub></td><td>Toll-like receptor<br>Gel-to-liquid phase transition temperature</td></tr><tr><td>TME</td><td>Tumor microenvironment</td></tr><tr><td>TNF</td><td>Tumor necrosis factor</td></tr><tr><td>TNF-α</td><td>Tumor necrosis factor alpha</td></tr><tr><td>Treg</td><td>Regulatory T cell</td></tr><tr><td>VEGF</td><td>Vascular endothelial growth factor</td></tr><tr><td>VISTA</td><td>V-domain immunoglobulin suppressor of T-cell activation</td></tr><tr><td>Ym1</td><td>Chitinase-like protein 3 (also known as Chi3l3)</td></tr></table>

## Introduction

The tumor microenvironment (TME) is composed of a broad array of cellular components such as fibroblasts, endothelial cells, stromal cells, immune cells, and cancerous cells, along with non-cellular elements such as extracellular matrix (ECM), signaling molecules, and extracellular vesicles [1]. In this dynamic environment, macrophages are particularly abundant and can adapt their function in response to local signals [2]. In many solid tumors, tumor-associated macrophages (TAMs) are predominantly polarized toward a pro-tumoral phenotype, supporting tumor progression by suppressing immune responses, promoting angiogenesis, and facilitating tissue remodeling [3]. The functional polarizability of macrophages provides an opportunity to develop targeted therapeutic strategies.

Recent studies have focused on reprogramming macrophages from a pro-tumoral to an anti-tumoral state as a promising strategy to treat cancer [4–6]. Various repolarization approaches have been investigated, including small-molecule drugs [7, 8] and monoclonal antibodies [9, 10]. However, due to their non-specificity, these strategies are often accompanied by potential systemic toxicity and other adverse effects. In this context, RNA-interference-based therapeutics have been identified as powerful tools to selectively modulate gene expression in macrophages and, thereby, their activity [11, 12]. However, efficient nucleic acid delivery to TAMs remains a significant challenge [13, 14].

Lipid nanoparticles (LNPs) have appeared as a leading delivery platform for RNAs, overcoming several barriers, including RNA degradation, poor cellular uptake, and limited endosomal escape [13]. The clinical success of LNPs in delivering siRNA (Patisiran, Alnylam Pharmaceuticals [12]) and mRNA (mRNA-1273, Moderna; BNT162b2, Pfizer-BioNTech [15]) has further proven the effectiveness of this platform in various therapeutic applications.

Consequently, RNA-loaded LNPs hold great promise for precisely modulating TAM activity, paving the way for the next generation of cancer immunotherapies [13]. However, several challenges must be overcome for their translation to clinics, including efficient targeting of macrophages in the TME, optimization of intracellular delivery, and minimization of off-target effects [13, 16].

This literature review provides a comprehensive overview of macrophage reprogramming using RNA interference-LNPs. We start by describing the biology of macrophages, their role in cancer, and therapeutic reprogramming strategies. Then, we introduce the mechanism of siRNA and miRNA-based gene silencing, LNPs as RNA delivery systems, and key aspects that should be considered to optimize the efficacy of RNA interference-LNPs. Finally, we highlight the state-of-the-art applications of RNA interference-LNPs in TAM reprogramming, along with critical challenges and future perspectives that will drive the clinical translation of this approach. We hope to advance theoretical understanding and the application of RNA interference-LNP-based TAM reprogramming in cancer therapy by addressing these key factors.

## Macrophages in health and disease

Macrophages are highly specialized immune cells that arise from two distinct developmental pathways. While tissue-resident macrophages derive mainly from embryonic origins, bone marrow-derived macrophages (BMDMs) originate from circulating monocytes produced in the bone marrow [17, 18]. Tissue-resident macrophages (e.g., microglia, Kupffer cells, Langerhans cells, and alveolar macrophages) are capable of self-renewal and have a longer life span than BMDMs [4, 17–20]. Belonging to the mononuclear phagocyte system (MPS) [17], these cells play a vital role in providing host defense against infections and maintaining tissue homeostasis [4, 21]. They are crucial modulators and effector cells in inflammatory responses [22].

Macrophages have long been known for their ability to shift between distinct functional states based on environmental cues [23, 24]. This remarkable plasticity enables them to adapt to the specific needs of the microenvironment but also underlies their involvement in the development and progression of various diseases, including cancer, infection, chronic inflammation, and autoimmune diseases.

## Macrophage polarization: M1 vs. M2 phenotypes

The polarization into various activation states operates on a spectrum, and macrophages can take on intermediate phenotypes depending on the specific stimuli they encounter
within the local tissue environment. Despite this complex-
ity, macrophage polarization is generally categorized into
two major groups: the pro-inflammatory M1 and the anti-
inflammatory M2 states [2, 4, 17, 25–27].

Polarization of macrophages into the M1 state is driven
by pathogen-associated molecular patterns (e.g., LPS from
gram-negative bacteria) or pro-inflammatory cytokines (e.g.,
IFN-γ). It is essential for immune defense [21, 27]. M1 mac-
rophages secrete high levels of pro-inflammatory cytokines,
including TNF-α, IL-1β, IL-6, and IL-12, crucial for recruit-
ing and activating T cells, natural killer cells, and dendritic
cells. They also enhance the adaptive immune response by
presenting antigens to T cells and can kill tumor cells or
pathogens directly through phagocytosis. Furthermore, their
production of nitric oxide (NO) and reactive oxygen spe-
cies (ROS) may provoke apoptosis in neighboring cells [4,
23]. Conversely, M2 activation is typically induced by anti-
inflammatory cytokines such as IL-4, IL-13, and IL-10 [27,
28]. These cells promote tissue repair, angiogenesis, ECM
remodeling, and the resolution of inflammation through the
secretion of anti-inflammatory cytokines, including IL-10

and TGF-β, and growth factors [4, 23, 26, 28]. The activa-
tion state of macrophages can be determined based on their
distinct cytokine or chemokine secretion profiles, cell sur-
face receptors, transcriptional regulators, and other media-
tors (Fig. 1).

The M1/M2 classification represents the extremes of a
functional spectrum, and macrophages undergo a dynamic
transition between these two states in response to environ-
mental signals. Importantly, dysregulation of this balance
has been associated with various diseases. One example
is cancer, where macrophages are often skewed towards a
tumor-supportive M2-like phenotype.

Role of macrophages in cancer resistance

TAMs represent solid tumors' most abundant immune popu-
lation, pivotal in shaping the TME [2, 31]. These immune
cells originate from tissue-resident macrophages or circulat-
ing monocytes, which are recruited to the tumor site and dif-
ferentiate into macrophages [2]. Specific chemokines (e.g.,
CCL2, CCL3, CCL5, CCL15, CCL26, CXCL8, CXCL12),

<figure><img src="image_4.png" /><figcaption>**Fig. 1** Macrophage polarization and marker expression in different types of activated macrophages: M1 (left) vs. M2 (right).
Adapted from [22, 23, 29, 30]</figcaption></figure>
cytokines (e.g., CSF-1, GM-CSF), and complement proteins (e.g., C5) are crucial in the recruitment of macrophages to the tumor site [1–3, 32].

Two distinct polarization phenotypes, M1 and M2, can be identified within the TME. While M1 macrophages contribute to inflammatory and anti-tumor immune responses, M2 macrophages participate in tumor cell proliferation, survival, and metastasis, as well as angiogenesis and immunosuppression (Fig. 2). Consequently, macrophages play a dual role in tumor progression, where their quantity and polarization state affect patient survival, with the M2-like phenotype being strongly linked to poor clinical outcomes in most solid tumors [27, 33–40].

The TME is typically characterized by hypoxia, low pH, and elevated interstitial fluid pressure, which are primarily caused by the abnormal formation of new blood vessels [31]. In the TME, several functional determinants, including hypoxia, tumor-derived lactate, IL-4, IL-13, and IL-10, collectively induce the differentiation of macrophages into the pro-tumor M2 phenotype [3]. These M2-like macrophages enhance immunosuppression through the secretion of cytokines such as TGF-β and IL-10 [6, 27, 41]. M2-like macrophages also inhibit the activation and function of effector

immune cells by expressing immune checkpoint molecules, including PD-L1, TIM-3, and VISTA [4]. They suppress the activity of cytotoxic (CD8+) and helper (CD4+) T cells via the action of various molecules, including IL-10, TGF-β, CCL2, cathepsin K, COX-2, and matrix metalloproteinases (MMPs), while promoting the recruitment of regulatory T cells (Tregs) [2, 41]. Moreover, these cells promote angiogenesis by producing factors like VEGF, PDGF, TGF-β, CXCL8, MMP9, TIE2, and ANG2, thereby facilitating oxygen and nutrient delivery to the tumor [2]. The secretion of molecules such as MMPs, serine proteases, and cathepsins by these cells also contributes to tumor invasion and metastasis by degrading the ECM and disrupting cell-cell/cell-ECM interactions [2, 42]. Additionally, TAMs support cancer stem cells’ survival, self-renewal, and tumorigenicity through factors such as IL-6 and TGF-β [43, 44]. Finally, these cells are critical in developing resistance to conventional cancer treatments, including chemotherapy, radiotherapy, and immunotherapies [2, 27, 41, 45].

Despite their predominantly pro-tumoral role within the TME, macrophages can also progress into an anti-tumoral M1-like phenotype. M1-like macrophages have been shown to hinder cancer progression by inducing tumor cell

<figure><img src="image_5.png" /><figcaption>**Fig. 2** Tumor-promoting and suppressing roles of TAMs. TAMs can be polarized into two states with distinct functions depending on external stimuli. ADCC, antibody-dependent cellular cytotoxicity; ADCP,</figcaption></figure>

antibody-dependent cellular phagocytosis; DCs, dendritic cells; NK cells, natural killer cells. Adapted from [2, 30]
apoptosis by producing ROS and NO. They also possess the potential to phagocytose tumor cells and present tumor-specific antigens for adaptive antitumor immunity [2, 30]. This functional duality offers a groundbreaking therapeutic opportunity in cancer treatment, where TAMs can be reprogrammed from tumor supporters into potent tumor fighters.

## Molecular targets and therapeutic approaches for macrophage reprogramming

Reprogramming TAMs from the immunosuppressive M2 to the immunostimulatory M1 phenotype holds great promise for treating cancer. Restoring the anti-tumor function of these cells can stimulate a robust immune response to promote tumor clearance [4–6].

Although several TAM-related therapeutic strategies, such as the inhibition of macrophage recruitment into tumors and macrophage survival, are currently under investigation, TAM reprogramming by molecular targeting stands out as the most promising approach [30, 41, 46]. This strategy may suppress the pro-tumoral functions of TAMs and activate

their anti-tumoral activities. M2-to-M1 repolarization can enhance the efficacy of other anti-tumor therapies, including chemotherapy and radiotherapy, as well as immunotherapies currently in clinical use, including immune checkpoint inhibitors and chimeric antigen receptor (CAR) T cells [2, 46].

Various strategies have been devised to induce M2-to-M1 reprogramming of TAMs (Fig. 3). To begin with, the activation of toll-like receptors (TLR) has been shown to drive macrophages toward an M1-like phenotype. TLRs are key pattern recognition receptors expressed in TAMs, enabling these cells to detect damage-associated molecular patterns (DAMPs) and initiate immune responses [7]. The activation of toll-like receptors (TLR) has been addressed using a TLR7 agonist (Imiquimod), approved by the FDA, illustrating the possibility of using these types of molecules in anti-tumor therapy [2, 7, 29]. Other TLR activators have been applied, including poly(I: C) (TLR3 agonist) [47–49] and synthetic unmethylated cytosine-guanine (CpG) oligodeoxynucleotides (TLR9 agonist) [50–52], which have also been shown to repolarize TAMs and enhance immunostimulatory activity. Nevertheless, the systemic administration of

<figure><img src="image_6.png" /><figcaption>**Fig. 3** TAM reprogramming strategies and targets: M2-to-M1 polar- ization can be induced by activating immunostimulatory mediators or</figcaption></figure>

inhibiting immunosuppressive ones. Adapted from [2]
free TLR agonists, mostly small molecules, has been limited
due to the side effects of a systemic interferon reaction [53].
However, it has stimulated the development of local deliv-
ery systems and nanoparticulate drug carriers with little
clinical success [54–56].

Another similar approach involves using the stimulator of interferon genes (STING) agonists. STING, a cytoplasmic protein in the endoplasmic reticulum, is crucial for detecting cytosolic DNA caused by cellular damage. Its activation in TAMs stimulates IRF3, type I interferon genes, and pro-inflammatory cytokines [54, 55]. At least twenty agonists of STING, most of them small molecules, have been clinically evaluated in Phase 1 and 2 trials. The first trials, which involved the intratumoral administration of synthetic cyclic dinucleotides (e.g., ADU-S100, MK-1454), demonstrated limited cell penetration, susceptibility to enzymatic degradation, and insufficient efficacy [56–58]. Consequently, liposomes loaded with STING agonist cGAMP have yielded more promising results in murine models of breast cancer and lung metastasis [59, 60]. Other approaches using nanoparticles or exosomes are under investigation [61, 62].

Inducing CD40 activation using monoclonal antibodies (mAbs) is another effective strategy for stimulating the anti-tumor functions of TAMs [9]. CD40 is a protein belonging to the TNF receptor family that is expressed on TAMs [63], and its stimulation can increase the release of TNF-α and NO from TAMs, enhancing CD8+T cell activation [29, 63]. CD40 agonists are currently being assessed in clinical trials in combination with chemotherapy [64]. The combination of antibodies targeting CD40 and CSF-1R has been shown to effectively treat preclinical tumor models that were not responsive to immune checkpoint inhibitors by impairing the recruitment of new TAMs towards immunosuppressive cells, reprogramming TAMs, and activating cytotoxic T cells, thus unleashing potent antitumor immunity [65, 66]. Various anti-CD40 mAbs have been clinically evaluated alongside immune checkpoint inhibitors, chemotherapy, and other targeted therapies [67]. However, several of those have been discontinued due to modest efficacy and dose-limiting toxicities such as cytokine release syndrome, liver toxicity, and enhanced angiogenesis [68]. A similar mechanism of action has been observed for anti-MARCO mAbs in murine models of breast, colon, and melanoma cancers, promoting the anti-tumoral functions of macrophages in tumors [10]. These antibodies target the pattern-recognition scavenger receptor MARCO, which is overexpressed in TAMs and associated with a poor prognosis in breast, lung, and liver cancers [69–71]. Moreover, bispecific antibodies targeting angiopoietin-2 (Ang-2) and vascular endothelial growth factor (VEGF) have been shown to reprogram TAMs and delay tumor growth in murine glioma models. Combining Ang-2/VEGF bispecific antibodies with 5-fluorouracil (5-FU) and

irinotecan in colorectal cancer, or with temozolomide in glioma, has shown significant benefits compared to anti-VEGF combined with chemotherapy [72, 73].

Another interesting approach has focused on using mAbs to reprogram TAMs into antitumor effectors by manipulating the CD47-signal regulatory protein alpha (SIRPα) axis. SIRPα, which is expressed on the surface of phagocytic cells such as macrophages, interacts with CD47 which is overexpressed by cancer cells. This interaction inhibits phagocytosis, acting as a “don’t eat me” signal for tissue homeostasis [74]. In preclinical cancer models, the pharmacological inhibition of CD47 restores macrophages’ ability to phagocytose and kill tumor cells [75–77]. Although antibodies able to inhibit SIRPα showed satisfactory antitumor activity in lung cancer models, their effects are limited in time [78]. Self-assembling SIRPα-blocking antibodies with CSF-1R inhibitors have successfully reprogrammed TAMs into M1 antitumor effectors. This combined therapy activates antitumor macrophages by hindering CD47-SIRPα ligation while inhibiting the recruitment of new TAMs [79, 80]. Clinical trials using anti-CD47 mAbs or CD47-Fc fusion proteins are ongoing for the treatment of hematological cancers or refractory solid tumors, either alone or in combination with anti-PD-1 therapy or anti-CD20 (Rituximab®) to target B cells [81].

Macrophage polarization is also associated with altera-
tions in cellular metabolism, as indicated by their differen-
tial metabolization of glucose, lipids, amino acids, oxygen,
and iron [2]. While M1 macrophages predominantly depend
on glycolysis, M2 macrophages utilize oxidative phos-
phorylation [82, 83]. Fatty acid oxidation is crucial for M2
polarization [84]. The L-Arginine catabolic pathway leads
to NO and L-citruline production by iNOS in the M1 state,
whereas Arg1 produces ornithine and urea in the M2 state.
Thus, increased expression of Arg1 is linked to immunosup-
pressive activities [85]. The overexpression of indoleamine
2,3-dioxygenase (IDO), an enzyme catabolizing tryptophan
into kynurenine, has been associated with the induction
of M2-like TAMs [86, 87]. Furthermore, hypoxia induces
TAMs polarization toward an M2-like phenotype [88].
Regarding iron metabolism, the M2 state is characterized by
an elevated iron release and limited iron storage compared
to the M1 [89]. Various therapeutic approaches mediating
glycolysis, arginase, IDO, hypoxia, or iron metabolism in
macrophages have been investigated for their potential in
reprogramming, with promising results. Finally, it has been
demonstrated that traditional chemotherapeutic agents (e.g.,
doxorubicin) [3], oncolytic viruses [90], and low doses of
radiation [91, 92] shift macrophages towards an M1-like
state by triggering the release of DAMPs by cancer cells,
which stimulate the pattern recognition receptors (PRRs) on
TAMs [2].
Epigenetic regulation of macrophages has been investi-
gated through the mediation of histone deacetylases [93, 94],
histone methyltransferases, or histone demethylases [94],
with several current clinical trials evaluating the potential
of combining epigenetic modifications with immune check-
point inhibitors [95]. Furthermore, various targets to modu-
late gene transcription of TAMs toward the M1-like subtype
have been addressed using nucleic acids such as siRNA,
microRNA (miRNA) [2]. Their delivery will be discussed
in more detail later in this review, but they were designed to
inhibit mediators, including STAT6 [96], 1κBα [97, 98], and
CSF-1R [99–101]. Upregulation of miRNAs such as miR-
125a [102], miR-125b [103], and miR155 [104] induced
successful TAM repolarization toward the M1 phenotype
and enhancement of antitumor immune response. More-
over, mRNAs encoding OX40L [105], CD80, and CD86
[106], administered intratumorally, could overcome the
local immunosuppressive environment of a tumor. Finally,
the CRISPR/Cas9 system and lentiviral vectors have been
employed to edit the genome of TAMs directly [2]. How-
ever, these gene-editing techniques still pose some chal-
lenges in clinical settings, particularly regarding their safety.

A recent review focusing on the clinical landscape of macrophage-reprogramming cancer immunotherapies has stressed that, despite the large number of targets and clinical trials, only a few exceeded Phase 2 [107]. Common reasons for this failure include toxicity due to the indiscriminate activation of macrophages (e.g., TLR agonists), leading to severe adverse effects [108], and the insufficient sustained inhibition of signaling pathways involved in macrophage reprogramming (e.g., STING) [109, 110]. One of the reasons could be that most of those strategies are based on intracellular targets that are difficult to reach in a clinical setting [111]. Additionally, despite advances in the development of humanized and fully human antibodies, there is still a risk of patients developing anti-drug antibodies (ADAs) against the therapeutic antibody. ADAs can alter their pharmacokinetics, neutralize the antibody's effect, and even lead to infusion reactions [112].

Compared to antibodies and small molecule drugs, which exert their therapeutic action by binding to particular proteins and require the identification of highly active and specific target proteins related to diseases, siRNA and miRNA provide a more promising therapeutic approach regarding their easier design and shorter development period, as well as the possibility to theoretically knock down any disease-associated genes [113–116].

RNA interference and administration
hurdles

MicroRNAs (miRNAs) and small interfering RNAs (siRNAs) are small RNA molecules important for gene regulation through RNA interference (RNAi). While siRNAs are designed to block one target gene, miRNAs can target multiple genes [118]. New strategies have been developed focusing on miRNA as therapeutic candidates (in the form of miRNA mimics) or as molecular targets using antimicroRNAs (Antagomirs) as therapeutic moieties [117, 118].

Depending on the target tissue and the administration
route, there are various barriers to the delivery of free ther-
apeutic RNA to its site of action. Following intravenous
injection, the RNA formulation must overcome a variety of
in vivo barriers: enzymatic degradation by serum or tissue
nucleases, renal clearance, uptake by the MPS, extravasa-
tion and transport across the interstitial space, transport
across the cell plasma membrane, endosomal entrapment,
and lysosomal degradation (Fig. 4) [119–122]. Moreover,
another barrier consists of their degradation by endogenous
nucleases. RNA are also quickly cleared by glomerular
filtration in the kidneys. Another biological barrier is the
uptake by the MPS, which is a population of phagocytic
cells that effectively eliminate pathogens, cellular debris,
and foreign substances from the blood circulation and tis-
sues. After systemic administration, higher concentrations
of RNA are observed in the liver and spleen due to high
blood flow to these organs, their discontinuous vessels, and
numerous tissue macrophages. The crossing of cell mem-
branes poses another challenge for free RNA delivery, given
that it is a hydrophilic molecule with a net negative charge
[121, 122]. It is also noteworthy that high levels of RNA
have the potential to activate the innate immune system via
the TLR pathways [120, 122]. Subsequently, the half-life
of unmodified and free RNA in serum has been reported to
range from several minutes to 1 h [122], with the majority
exhibiting a half-life of approximately 10 min [121, 123].

Different strategies have been proposed to address the
abovementioned challenges. The first approach involves
altering RNA through chemical modifications, and the sec-
ond focuses on developing nanoparticle-based RNA delivery
systems. Regarding the initial strategy, RNA, particularly
siRNA, can be chemically modified on various groups,
such as bases, sugars, or phosphate groups, to enhance its
in vivo stability by increasing its resistance to nucleases
and avoiding its immune recognition. Typical modifications
include the conversion of the phosphodiester (PO4) group
into the phosphorotioate (PS) group and the replacement of
the 2'-hydroxyl group of the ribose ring by various groups,
including 2'-O-methyl, 2'-O-methoxyethyl, and 2'-fluoro.
Those chemical modifications should be designed and
**Fig. 4** Physiological barriers to systemic siRNA delivery: Various in vivo barriers to free siRNA delivery: (1) degradation by endonucleases, (2) uptake by the MPS, (3) renal clearance, (4) extravasation and transport across the interstitial space, and (5) transport across the cell membrane.

Adapted from [121, 124]

<figure><img src="image_7.png" /></figure>

tested so as not to affect gene silencing adversely. As for the second strategy, scientists have developed a variety of nano-carriers, including lipid-based and polymer-based systems, which can protect the siRNA from degradation, facilitate its cellular uptake, and deliver it to target sites [116, 122].

## Non-lipid nanoparticles for the delivery of RNA interference in macrophage reprogramming

This review focuses on using lipid nanoparticles to deliver RNA interference (siRNA, miRNA) for reprogramming macrophages. However, other types of M2-targeted or non-targeted nanoparticles have also been developed to deliver siRNA or miRNA. These nanoparticle platforms vary significantly in composition, for example, some utilize an amphiphilic cationic β-cyclodextrin (CD) incorporating CSF-1R siRNA and a targeting peptide (M2pep) [125]. Others are based on cationic polymers, such as poly(ethylenimine), that can be coupled with hyaluronic acid to target the CD44 receptor [103, 126].

Indeed, silencing STAT6 was first carried out using polyethyleneimine or polypropylenimine nanoparticles [96]. JAK/STAT pathway plays a central role in regulating macrophage activation states. The IL-4- or IL-13-induced activation of STAT6 is crucial in expressing M2-associated

genes such as Arg1, KLF4, PPARγ, CD206, and Fizz1. Moreover, STAT3, which IL-10 activates, is also associated with the M2 state by activating genes such as IL-10, TGF-β1, CD206, and Arg1 [127]. In the study by Walther et al. [96], the researchers demonstrated that siRNA-mediated silencing of STAT6 using the cationic polymers is a promising approach to trigger M2-to-M1 polarization in vitro, resulting in enhanced tumor cell phagocytosis in a co-culture model.

The classical and alternative pathways of NF-κB signaling also function as critical regulators of TAM polarization [128, 129]. Activation of the NF-κB pathway has been linked to both anti-tumor and pro-tumor functions in TAMs [97, 129, 130]. Although the mechanism by which NF-κB modulates TAM polarization is still an ongoing area of research, several studies have recently demonstrated that activation of the classical NF-κB pathway induces an M1-like state in macrophages [97, 131]. Therefore, silencing molecules associated with NF-κB p50:RelA inhibition, such as IκBα, can promote pro-inflammatory signaling and shift macrophages toward an anti-tumor M1 phenotype [97, 131]. In a study by Ortega et al. [97], the researchers employed mannosylated methacrylate-based nanoparticles to deliver siRNA against IκBα to activate the NF-κB pathway and boost anti-tumor functions in macrophages, yielding promising results. In a separate study, Glass et al. [98] have also shown that the treatment with this mannose-functionalized
polymeric nanoparticles loaded with siRNA targeting IκBα repolarized macrophages toward a pro-inflammatory phenotype and significantly decreased tumor burden in mouse models of ovarian cancer [131].

Another polarization modulator is CSF-1R, which has been implicated in the infiltration, survival, and immunosuppressive function of TAMs [132, 133]. Sun et al. [125] demonstrated that targeting the CSF-1R with siRNA through the use of cyclodextrin-based nanoparticles decorated with M2 macrophage-targeting peptide promoted the immunos timulatory activities of macrophages in vivo, enhanced the helper and cytotoxic T cell infiltration in the TME, and triggered cancer cell apoptosis in a mouse model of prostate cancer.

Treatment strategies simultaneously targeting TAMs through multiple pathways are an elegant option to address the tumor's complex nature. Combination strategies can overcome therapeutic resistance and enhance immune responses, improving treatment efficacy compared to single-agent therapies [6, 101]. Pan et al. [134] illustrated that the combined administration of siRNAs against CSF-1R and signal-regulatory protein alpha (SIRPα) effectively reprograms IL-4-stimulated BMDMs towards an M1-like state, promoting macrophage-induced phagocytosis of cancer cells. Additionally, administering these nanoparticles to Lewis lung carcinoma-implanted mice resulted in a notable reduction in tumor size. Similarly, Cheng et al. [100] presented an innovative approach employing DNA tetrahedron nanostructures loaded with siRNA against CSF-1R and immune adjuvant CpG for pro-inflammatory macrophage reprogramming. The treatment induced apoptosis and necrosis in 4T1 tumor cells in vitro and inhibited tumor growth in 4T1 xenograft tumor-bearing mice. Moreover, the study of Li et al. [101] demonstrated that the treatment with nanomicelles that are actively targeted to M2 TAMs for the co-delivery of siRNA against CSF-1R and the PI3K-γ inhibitor NVP-BEZ 235 effectively remodeled the TME by increasing M1 polarization and decreasing myeloid-derived suppressor cell (MDSC) infiltration in the context of pancreatic cancer. In another study, Xiao et al. [6] showed that the M2-targeted co-delivery of siRNA against IKKβ and the STAT6 inhibitor AS1517499 by pH-responsive micelleplexes efficiently induced M2-to-M1 polarization in vivo and effectively attenuated tumor growth and metastasis of the 4T1 breast tumor in mice. Using CD44 targeting hyaluronic acid-poly(ethylenimine) (HA-PEI)-based nanoparticles encapsulating miR-125b, it was possible to transfect TAMs in lung tissues in a non-small cell lung cancer mouse model and to successfully repolarize them into the M1 phenotype [103].

## Lipid nanoparticles for the delivery of RNA interference in macrophage reprogramming

Compared to cationic nanoparticles, LNPs allow for higher encapsulation efficiency and greater stability in biological fluids. LNPs are much less toxic than cationic liposomes, which have a persistent positive charge that leads to higher cytotoxicity and instability in vivo due to non-specific interactions with serum proteins. Polymeric nanoparticles offer versatility in terms of material properties and controlled release. However, they often face challenges in achieving high encapsulation efficiency for nucleic acids, efficient endosomal escape, and favorable biocompatibility profiles compared to LNPs. Some polymeric systems also suffer from poor serum stability and can induce immunogenicity. One final advantage of LNPs is the reproducibility of manufacturing techniques, especially those using microfluidics, which allow precise control over particle size, uniformity, and encapsulation efficiency. This leads to highly reproducible batches. These scalable methods enable the large-scale production required for clinical trials and widespread therapeutic use. Importantly, as LNPs have already been clinically validated to deliver siRNA and mRNA for several applications [113] they have naturally attracted the widespread attention from both academia and industry.

## Composition influence on physico-chemical and biological properties of LNPs

LNPs have been developed as vehicles to overcome the challenges associated with RNA interference delivery by efficiently encapsulating RNA, shielding it from serum nucleases and immune system molecules, decreasing its renal clearance, and facilitating its transmembrane transport and endosomal escape [135]. Functionalizing the LNP surface with targeting moieties may also contribute to the selective delivery of RNA to specific cells, although tissue distribution should theoretically remain similar to non-targeted LNP [136]. This section provides an overview of the mechanism of LNP-mediated siRNA delivery and then emphasizes the critical role of lipid composition in optimizing RNA interference-LNP performance.

The lipid composition impacts the therapeutic efficacy of siRNA-LNPs [16]. In general, LNPs consist of four main constituents (Fig. 5): an ionizable cationic lipid (40–50 mol%), a helper phospholipid (10–15 mol%), cholesterol (38–50 mol%), and polyethylene glycol (PEG) coupled to a lipid moiety, generally phospholipid (1.5–2 mol%) [13, 135, 137].
<figure><img src="image_8.png" /><figcaption>**Fig. 5** Schematic representation of RNA-LNP structure and its main components. Ionizable lipids, helper phospholipids, cholesterol, and</figcaption></figure>

PEG-lipids are illustrated with their associated characteristics.
Adapted from [13]

Ionizable lipids

The critical importance of ionizable cationic lipids in the formulation stems from the fact that they are relatively uncharged at the physiological pH of 7.4. In contrast, they become positively charged at pH values lower than their acid dissociation constant (pKₐ). This leads to efficient RNA encapsulation in LNPs [138]. During LNP production, which is carried out at acidic pH (pH ~4), the protonation of ionizable lipids contributes to the encapsulation of anionic nucleic acids within nanoparticles as a result of electrostatic interactions, allowing high encapsulation efficiencies [16].

Ionizable lipids play an essential role in the intracellular trafficking of RNA after cell uptake. Cell uptake of nanoparticles primarily occurs through endocytosis, which can be classified into phagocytosis and pinocytosis. Phagocytosis is a process that occurs exclusively in professional phagocytes such as macrophages, monocytes, and neutrophils to clear large particles (e.g., microorganisms and apoptotic cells). In contrast, pinocytosis can occur in almost any cell through four distinct mechanisms: clathrin-dependent endocytosis, caveolae-dependent endocytosis, macropinocytosis, and clathrin/caveolae-independent endocytosis.

Clathrin-mediated endocytosis is the predominant route for nucleic acid-loaded lipid-based nanoparticles, leading

to lysosomal degradation unless endosomal escape occurs. Caveolae-mediated uptake provides an alternative pathway, allowing transport to intracellular compartments such as the Golgi and endoplasmic reticulum. LNPs may also enter cells via macropinocytosis, characterized by membrane ruffling and large vesicle formation that either fuse with lysosomes or recycle back to the membrane. In addition to these established routes, alternative pathways may occur, though their underlying mechanisms remain to be discovered [140]. Clathrin-mediated endocytosis (Fig. 6) begins with the invasion of the plasma membrane to create an endocytic vesicle. This vesicle then fuses with a sorting endosome. Its internal pH decreases as it matures due to the action of membrane-bound ATP-driven proton pumps [141] from the pH of 6.0-6.5 in early endosomes to the pH of 5.0-5.5 in late endosomes, and finally to the pH of 4.5-5.0 in lysosomes [137].

To avoid degradation of RNA in the hydrolytic lysosomal environment and achieve successful gene silencing effects, RNA needs to be delivered to the cytoplasm. If endosomal escape does not occur, the RNA-LNP system is either excreted from cells or degraded in hydrolase-rich lysosomes [137]. LNPs provide efficient endosomal escape due to the peculiar properties of the ionizable lipids. Indeed, at the acidic pH of endosomal vesicles, the positively charged
<figure><img src="image_9.png" /><figcaption>**Fig. 6** Schematic representation of RNA-LNP uptake, intracellular trafficking, and endosomal escape: Clathrin-mediated endocytosis and macropinocytosis were illustrated. Endosomal trafficking through the cell can be tracked by the Rab family of proteins, including Rab5,</figcaption></figure>

LNP lipids interact with the negatively charged endosomal lipids, creating a cone-shaped geometry that causes the phospholipid bilayer structures to convert into hexagonal $H_{II}$ phases, destabilizing the endosomal membrane and leading to the release of siRNAs into the cytoplasm [138]. Being neutral at the physiological pH, these lipids help to reduce the cytotoxicity of LNPs and their clearance by the fixed and free macrophages [142]. In addition, the gene-silencing potency of LNPs is highly dependent on the $pK_a$ values of ionizable cationic lipids [142]. A study by Jayaraman et al. showed a strong bell-shaped curve correlation

Rab7, and Rab11, which are associated with early, late, and recycling endosomes, respectively. Endosomal escape has been reported from different endocytic compartments in different studies. Adapted from [139]

between the apparent $pK_a$ of LNPs and their potency, with an optimal $pK_a$ range of 6.2–6.5. From a library of ionizable lipids consisting of a dilinoleyl-based hydrophobic tail and various head groups, the authors distinguished the ionizable lipid (6Z,9Z,28Z,31Z)-heptatriaconta-6,9,28,31-tetraen-19-yl 4-(dimethylamino)butanoate (DLin-MC3-DMA) with an apparent $pKa$ of 6.44 [143]. Patisiran (Alnylam Pharmaceuticals), the first siRNA therapeutic approved by the United States Food and Drug Administration (FDA) and the European Medicines Agency (EMA) in 2018 [12], employs the ionizable lipid DLin-MC3-DMA [5, 144]. Together
with DLin-MC3-DMA, FDA-approved ionizable lipids such as SM-102 and ALC-0315 (used in the formulations of Moderna and Pfizer-BioNTech's mRNA-LNP vaccines, respectively [145]) provide a solid foundation for further LNP advancements in the context of RNA delivery [146]. Various ionizable lipids have been developed to translate clinically siRNA-LNP formulations, including unsaturated, multi-tail, polymeric, biodegradable, and branched-tail ionizable lipids [138]. Moreover, ionizable lipid-like materials, such as C12-200, have been successfully used to prepare LNP-based siRNA systems [147–149]. Optimization studies of ionizable lipids have significantly improved the gene-silencing efficiency of LNPs [142]. Studies have demonstrated that only a tiny proportion (<3.5%) of internalized RNA undergoes endosomal escape and reaches the cytoplasm following LNP-mediated delivery, while the majority is either degraded in lysosomes or recycled out of the cell [150, 151]. Using siRNAs labeled with gold nanoparticles, the endosomal escape was shown to be inefficient (~1–2%) even for the optimized LNP formulations [150]. Endosomal escape is considered the major bottleneck for LNP-based therapeutics, and its better understanding is essential for developing more efficient siRNA-LNP systems [139].

Despite their effectiveness for cytoplasmic release, ionizable lipids have been shown to stimulate the immune system. It was shown that the amine headgroups in ionizable lipids stimulate immune responses to lipid nanoparticles by binding to receptors such as TLR4 and CD1d and promoting lipid-raft formation [152]. Recent studies have demonstrated their propensity to activate transcription factors, such as Nuclear Factor-kappa B (NF-κB) and Interferon Regulatory Factor (IRF) through TLR4 signaling [153, 154]. These findings underscore the pivotal role of ionizable lipid components in mediating inflammatory responses. These inflammatory responses likely contribute to the side effects observed with RNA therapeutics involving LNPs but may also enhance RNA vaccine efficacy [155].

## Helper lipids

In addition to ionizable lipids, helper lipids are needed to improve the stability as well as the encapsulation and delivery efficiencies of LNPs. The term 'helper lipid' encompasses a variety of lipid types, including phospholipids, sterols, and PEG-lipids [16, 156]. Distearolyphosphatidylcholine (DSPC) and 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE) are the most commonly used helper phospholipids in LNP formulations [16]. Phospholipids with a conical geometry (e.g., DOPE) enhance the LNP-mediated intracellular delivery of nucleic acids by promoting the formation of hexagonal lipid phases; however, they result in low stability due to the increased tendency

for bilayer fusion and higher interaction with plasma proteins. On the other hand, saturated phosphatidylcholines with their cylindrical shape (e.g., DSPC) provide higher stability and longer in vivo half-life for LNPs thanks to their high gel-to-liquid phase transition temperatures ($T_m$) [156]. Saturated helper lipids are better suited for delivering short siRNAs [110], while unsaturated lipids are more compatible with transporting longer mRNAs [147].

## Cholesterol

Along with helper phospholipids, cholesterol (CHOL) is widely used in LNP formulations. The incorporation of CHOL between phospholipids enhances the stability of the lipid bilayer and significantly decreases the adsorption of serum proteins to the LNP surface [156]. The effect of CHOL on membrane fluidity changes depending on the situation. It increases membrane rigidity when inserted between phospholipids with low $T_m$ and enhances membrane fluidity when inserted between phospholipids with high $T_m$ [16]. CHOL also facilitates membrane fusion [15, 147, 157]. Interestingly, the substitution of CHOL with its analog β-sitosterol enhances fusion with the endosomal membrane, leading to increased transfection efficiency [158].

## PEG-lipids

Finally, PEG-lipids play a crucial role in modulating the transfection efficiency and stability of LNP formulations. These lipids also affect the size and polydispersity of nanocarriers, encapsulation efficiency, biodistribution, and immune response [16]. PEG-lipids on the nanoparticle surface provide a hydrophilic steric barrier for the nanocarrier, avoiding particle aggregations and resulting in more homogeneous populations [16]. It has been observed that formulations without or with very low amounts of PEG-lipids lead to unstable and large LNPs (hydrodynamic diameter > 200 nm) with a polydisperse size distribution [159]. In contrast, using PEG-lipids as low as 0.5 mol% leads to stable, homogeneous, and small nanoparticles (~60 nm) [160]. Numerous studies have also shown that the nanoparticle size decreases as the molar percentage of PEG-lipids is increased in the range of 0.5–5 mol% [147, 160, 161]. Moreover, the hydrophilic steric hindrance provided by PEG-lipids prevents the attachment of plasma proteins (e.g., opsonins) to the LNP surface, reducing their capture by the MPS [20, 162]. PEG-lipids are required for higher stability and longer circulation times; however, their presence reduces cellular uptake efficiency or endosomal escape processes [163–165]. Typically, a PEG lipid content of ≤2 mol% is sufficient to achieve stealth characteristics without compromising efficient nanoparticle uptake by
target cells [13]. Both the PEG chain and the anchoring lipid significantly influence the in vivo behavior of LNPs [166]. PEG2000, with a molecular weight of 2000 g/mol (~45 repetition units), is frequently used as it optimally balances extended circulation time and efficient gene delivery [164, 166, 167]. In contrast, shorter PEGs (≤ PEG1000) are ineffective in preventing protein corona formation and extending systemic circulation, and longer PEGs (≥ PEG5000) can significantly hinder cellular uptake and endosomal escape [166]. Regarding the lipid anchor, optimization studies have led to the development of diffusible PEG-lipids with C14 alkyl chains, which improve transfection efficiency thanks to their ability to rapidly detach from the LNP in the presence of a lipid sink [135]. In blood circulation, these lipids spontaneously transfer from LNPs to acceptor sites such as plasma lipoproteins and erythrocytes [162]. For example, DMG-PEG (C14) has been demonstrated to diffuse from LNPs in blood circulation quickly, enabling apolipoprotein E (ApoE) binding to the surface and subsequently leading to effective hepatocyte targeting [16, 168]. The desorption rate of a PEG-lipid from LNP decreases as its hydrophobic alkyl chain length increases [16, 162]. PEGs with longer lipid chains, such as DSPE-PEG (C18), can prolong blood circulation, potentially increasing LNP accumulation in extrahepatic organs and tumors [16, 166]. The type of PEG-lipid significantly impacts the LNP behavior and, therefore, should be selected based on the therapeutic target and the administration route. Some examples of PEG-lipids used in clinically approved LNP formulations include PEG-c-DMG (Patisiran, Alnylam Pharmaceuticals), PEG-DMG (mRNA-1273, Moderna) and ALC-0159 (BNT162b2, Pfizer-BioNTech) [16].

## Key aspects in reprogramming macrophages with RNA-LNPs

The therapeutic outcome of reprogramming macrophages using RNA-LNPs depends on several factors, such as the administration route, the targeting specificity, and the efficacy of RNA interference delivery. This section examines three critical aspects: local vs. systemic delivery approaches, passive vs. active targeting, and strategies to improve intracellular RNA interference delivery efficiency.

### Local vs. systemic delivery approaches

Local administration enables precise targeting of macrophages at specific sites, such as local tumors. This method circumvents the majority of barriers encountered in systemic administration and could reduce systemic side effects and enhance therapeutic outcomes by increasing RNA interference concentrations at the tumor site. The efficacy

of intratumorally administered nanoparticles is determined by several factors, including uniform dispersion throughout the tumor, an extended residence time, and internalization by target cells, all of which are influenced by nanoparticle characteristics [169]. Depending on the tumor size, the dose and injection rate must be tightly controlled to prevent leakage from the tumor and off-target effects. Although promising, this technique is invasive and necessitates professional injection skills [140, 169, 170]. The most critical barrier to its application is the difficulty of reaching deep tumor tissues because of their limited accessibility, requiring long needles or open surgeries. Furthermore, the use of long needles could harm healthy organs [169]. The number of studies using intratumoral (IT) administration of nanoparticles has been expanding in the last decade [169]. Most clinical trials on LNPs for cancer treatment have employed local delivery, primarily through IT injection [16]. However, this approach is inadequate for treating tumors with metastases or hematologic cancers [13].

On the other hand, systemic delivery refers to administering RNA interference-LNPs into the bloodstream, typically via intravenous (IV) injection. This approach is essential in metastatic cancers, as it allows for the simultaneous targeting of macrophages in multiple organs or tissues. Nevertheless, it encounters obstacles such as rapid clearance by the MPS, nonspecific uptake by healthy organs, and off-target effects (Fig. 7) [140]. Following systemic administration, the LNP surface is rapidly coated with plasma proteins (e.g., albumin, immunoglobulins, complement proteins, and apolipoproteins), forming a protein corona. This process, known as opsonization, enhances the elimination of nanoparticles by phagocytic cells [171]. Once administered intravenously, RNA-LNPs demonstrate a preferential accumulation in the liver and spleen, which can be attributed to the filtering functions of these organs and the presence of macrophages that phagocytose foreign particles [20, 140]. A 2022 review by Albertsen et al. identified 40 clinical trials investigating LNPs, of which 22 used local administration, such as intramuscular injection for vaccines and intratumoral delivery for cancer. Among the remaining trials, 11 employed intravenous administration, 7 for liver targeting, and 4 for cancer treatment [16]. The distribution of these trials highlights the difficulty of achieving effective non-liver targeting through systemic delivery routes. Therefore, attaining precise RNA interference-LNP delivery to extrahepatic targets requires optimizing targeting strategies, which will be examined in the following section.

### Passive, active, and endogenous targeting

Targeting TAMs for drug delivery holds great promise for cancer treatment. Main strategies include passive, active,
<figure><img src="image_10.png" /><figcaption>**Fig. 7** Challenges associated with systemic delivery of RNA interfer-
ence-LNPs: Formation of protein corona on the LNP surface could
cause (1) RNA interference leakage, (2) aggregation of LNPs, (3) lost</figcaption></figure>

targeting ability, (4) clearance by the MPS, or (5) nonspecific uptake
by healthy organs.
Adapted from [140]

and endogenous targeting (Fig. 8). These mechanisms can
be employed individually or in combination to govern the
biodistribution of LNPs [172].

Passive targeting involves controlling the properties of
nanoparticles to take advantage of certain natural anatomi-
cal or physiological features or a pathophysiological condi-
tion [172]. For example, TAM targeting benefits from the
natural physiology of macrophages and tumor-associated
alterations in the tissue environment, and, as they are profes-
sional phagocytes, they naturally tend to internalize LNPs
via phagocytosis [140, 173]. Another passive targeting strat-
egy is to use particles with hydrophilic coatings (e.g., PEG)
that typically exhibit prolonged circulation times and evade
the MPS clearance [140, 171, 174], thereby enhancing the
probability of passive uptake by tumor sites. Nevertheless,
PEGylation may also restrain cellular uptake or the endo-
somal escape process [140]. Leaky vasculature and poor
lymphatic drainage of tumors allow for passive targeting of
macrophages within the TME via a phenomenon known as
the enhanced permeability and retention (EPR) effect [175].
Doxil®, a PEGylated liposomal delivery system encapsulat-
ing doxorubicin currently in clinical use, employs passive
targeting of tumors due to the EPR effect [173]. It has been
reported that nanoparticles with a size smaller than that of
the fenestrations in tumor vessels (200–800 nm) [140, 173,
175] are capable of permeating the TME, with the optimal
size range being approximately 20–200 nm [173]. Further-
more, smaller LNPs can more effectively infiltrate stromal-
rich tumor tissues, enhancing tumor accumulation [140].

Nevertheless, it should be noted that the EPR effect is less
effective in poorly vascularized tumors or those with dense
stromal barriers [13]. In brief, passive targeting is limited by
non-specific cellular uptake. It lacks the specificity neces-
sary for effective TAM delivery, requiring the development
of advanced targeting strategies.

Active targeting is based on targeting moieties that selec-
tively guide nanocarriers to the targeted cells and increase
therapeutic efficacy while reducing off-target effects [126].
In this approach, the surface of nanocarriers is decorated
with molecules (e.g., antibodies, aptamers, peptides, or small
molecules) [140] specific to the receptor on macrophages.
The endocytic uptake of actively targeted LNPs by macro-
phages occurs through specific receptor-ligand interactions
involving mannose receptors, scavenger receptors, and Fc
receptors [176]. It has been demonstrated that nanoparticles
targeted to Fc and mannose receptors exhibit a notably
shorter time to be internalized compared to those targeted
to scavenger receptors, indicating the critical role of Fc and
mannose receptors in the efficient uptake of nanoparticles
[176]. In the context of cancer, the precise targeting of M2
TAMs is essential, and significant efforts have been made to
develop strategies for this purpose. The mannose receptor
CD206 is frequently used to target anti-inflammatory M2
macrophages due to its high expression on these cells [98].
Consequently, numerous studies have explored mannose-
functionalized nanoparticles for actively delivering thera-
apeutics to M2-like macrophages [97, 98, 131, 177, 178],
demonstrating the efficacy of CD206-mediated uptake.
<figure><img src="image_11.png" /><figcaption>**Fig. 8** Targeting strategies of siRNA-LNPs. (a) Passive targeting relies primarily on LNP size and tumor-associated alterations in the tissue environment. (b) Active targeting utilizes ligands targeting cell-specific receptors. (c) Endogenous targeting depends on the protein</figcaption></figure>

corona that directs LNPs to specific sites in the body through receptor interaction or in situ cellular hitchhiking by immune cells that deliver the LNPs to the tumor.
Adapted from [140]

Sialic acid-decorated nanocarriers have also shown potential for targeting M2 macrophages through specific interactions with CD169 (Siglec-1), a receptor highly expressed in these cells [99]. Other molecules, including folate [133] and anti-CD206 antibodies [179], have proven highly effective in targeting M2 TAMs. However, these targeting ligands also significantly bind to tissue-resident macrophages in healthy organs, dendritic cells, and epithelial cells [101, 180]. To specifically target M2 TAMs while avoiding non-specific binding to other leukocytes, some researchers have identified a peptide sequence (M2-targeting peptide, M2pep). Following the decoration of the nanoparticle surface with the M2pep, several authors demonstrated increased efficacy in delivering specific inhibitors and RNA interference to turn M2 macrophages into the immunostimulatory phenotype, M1 subtype [6, 101, 125, 180]. Kuninty et al. [181] conducted an interesting study targeting M2 macrophages. They designed liposomes containing peroxidized phospholipids, which are recognized and internalized by scavenger receptors on M2 macrophages. Delivering a STAT6 inhibitor (AS1517499), zoledronic acid, or cell wall lipopeptides to these cells inhibited the premetastatic microenvironment and tumor growth [181].

In addition to active and passive approaches, endogenous targeting emerges as a novel paradigm depending on a better understanding of how the protein corona regulates nanoparticle delivery. In this strategy, the nanoparticle is designed to interact with a particular subgroup of plasma proteins after intravenous administration, triggering internalization by specific cells [172]. The physicochemical properties of LNP formulations, together with patient-specific parameters such as sex and age, determine the composition of the proteins adsorbed. The protein corona governs the interaction of LNPs with macrophages [20, 140]. For instance, the coating of the LNP surface with complement 3 (C3) increased splenic distribution through complement receptors on macrophages in the spleen [182]. In another study, the protein corona significantly elevated the internalization of nanoparticles by M2 macrophages, which can be linked to the overexpression of phagocytic surface receptors against proteins adsorbed on nanoparticles [183]. The polarization state of macrophages plays a vital role in nanoparticle uptake [184–186], which could affect the pharmacokinetics and pharmacodynamics of the drug delivery system. An endogenous targeting mechanism, unrelated to macrophage-directed delivery, has been successfully utilized in Patisiran (Alnylam Pharmaceuticals). It involves the
adsorption of ApoE onto the LNP surface, enabling recognition by low-density lipoprotein receptors (LDLRs) highly expressed on hepatocytes, thereby promoting selective liver accumulation [16, 168]. Another example, though again unrelated to macrophages, revealed an endogenous targeting strategy in solid tumors via the use of LNPs engineered to recruit vitronectin to their protein corona, contributing to αVβ3 integrin-mediated delivery to endothelial cells lining tumor blood vessels and enhancing siRNA transfection in tumor cells [187].

Another endogenous mechanism involves in situ cellular hitchhiking of nanoparticles that can lead to their accumulation in disease sites [188, 189]. Nanoparticles can be engineered to be internalized by blood circulating immune cells, such as monocytes and neutrophils, which naturally extravasate and infiltrate tumor tissues or metastatic sites, carrying the nanoparticles directly to the desired location [190]. This process is particularly effective for reaching metastatic lymph nodes or areas of inflammation associated with tumors. For example, this process has been described for cyclic RGD-decorated lipid nanoparticles in tumor mouse models [191]. In the context of macrophage reprogramming, Kuang et al. [192] designed lipid-based nanoparticles that target circulating monocytes and hitchhike with them to the central site of a glioblastoma in a mouse model [192]. The DOX·HCl contained within these nanoparticles is then released, inducing immunogenic cell death and the release of calreticulin, which contributes to macrophage reprogramming, dendritic cell maturation, and T cell activation [192]. Despite the preliminary success of hitchhiking strategy, efforts should focus on enhancing nanomaterials' targeting efficiency and specificity to circulatory cells to enable their effective hitchhiking and delivery to specific tissues or cells. Further research is needed to optimize the selection and design of ligands or functional groups on the surface of nanomaterials to ensure efficient recognition and binding to the desired target. Premature release of loaded drugs during hitchhiking can impair the migration, homing, and other functions of hitchhiked cells or proteins, resulting in unpredictable therapeutic efficacy.

Ultimately, each of the three targeting strategies described in Fig. 8—passive, active, and endogenous—could play a role in optimizing macrophage-directed drug delivery.

## Improving intracellular delivery efficiency

Transfection efficiency is significantly influenced by LNP composition. For instance, PEG-lipids can hinder interactions between LNPs and cellular membranes, necessitating careful optimization of the PEG chain, anchoring lipid, and PEG-lipid molar ratio in the formulations [140]. A strategy to overcome this problem includes the development of

pH-sensitive PEG-lipids, which remain stable under physiological conditions while detaching from the surface of LNPs in acidic microenvironments. This approach retains PEG's stealth properties while reducing its adverse effects on transfection efficiency. In the study of Xiao et al. [6], researchers designed micelleplexes functionalized with M2pep, where these peptides were embedded within a pH-sensitive PEG corona. The cleavage of the surface-bound PEG-lipids in the acidic TME (pH ~6.5–6.8) enables the precise delivery of therapeutic agents to M2 TAMs. As seen in this example, one strategy to enhance cellular uptake is to induce endocytosis. This can be achieved by surface modification of LNPs by conjugating receptor-targeting ligands or cell-penetrating peptides (CPPs) (Fig. 9a) [140]. Modifying LNPs with the RGD peptide (Arg-Gly-Asp)-based ionizable lipids [193], the macrophage-targeting peptide CRV (sequence CRVLRSGSC) [146], or the protamine-derived CPP [194] has been shown to facilitate nanoparticle internalization. While enhancing endocytic uptake could improve cytoplasmic availability, non-endocytic delivery approaches offer a direct route to the cytoplasm and avoid endosomal entrapment. An interesting strategy consists of mimicking viral mechanisms of cell entry via membrane fusion, allowing the bypass of endocytic pathways to enhance cytoplasmic delivery (Fig. 9a). Entos Pharmaceuticals® engineered a fusogenic proteolipid vehicle consisting of neutral lipids and fusion-associated small transmembrane proteins, which enables the direct delivery of nucleic acids into the cytoplasm [195].

Although LNP endocytosis is effective, obstacles such as lysosomal degradation and poor RNA bioavailability in the cytoplasm highlight the necessity to enhance endosomal escape to obtain better therapeutic outcomes. The mechanisms underlying endosomal escape have evolved significantly over the past few decades. In the late 1990s, the proton sponge hypothesis emerged to explain nanoparticles containing cationic polymers. This model proposes that the cationic polymers buffer the acidic endosomal environment, causing osmotic swelling and subsequent membrane rupture [196]. In this context, the research by our group has significantly contributed to developing liposome-protamine systems for siRNA delivery [197]. Next, researchers identified an alternative mechanism involving cationic lipids (e.g., DOTAP) in LNP formulations. These cationic lipids interact with negatively charged endosomal membrane lipids via electrostatic interactions, destabilizing the bilayer structure and facilitating cargo release [198, 199]. In the 2000s, multiple mechanisms have been proposed to explain how endosomal escape occurs, including the flip-flop, membrane fusion, destabilization, and pore formation models [140]. While positively charged lipid-based nanoparticles typically demonstrate a higher cellular uptake, they
<figure><img src="image_12.png" /><figcaption>**Fig. 9** Strategies to improve intracellular delivery efficiency of RNA-LNPs. (a) Different strategies to enhance cellular uptake: modification of LNPs with receptor targeting ligands, cell penetrating peptides (CPPs), or fusogenic proteins. (b) Different strategies to improve endosomal escape: incorporation of inverted cone-shaped lipids into</figcaption></figure>

are also associated with a higher risk of cytotoxicity and increased opsonization by anionic serum proteins [200]. A breakthrough in LNP technology came with the introduction of ionizable cationic lipids, which remain neutral at physiological pH but become positively charged in the acidic environment of endosomes [138, 201]. This pH-responsive behavior enables escape mainly via the flip-flop mechanism, where lipid rearrangement induces the formation of non-bilayer hexagonal phases, promoting membrane fusion and cargo release [140]. This advancement was pivotal in developing siRNA- and mRNA-based LNP therapies, including coronavirus disease 2019 (COVID-19) vaccines [15].

The endosomal escape process is challenging to investigate due to its transient nature and short-lived duration. Even though it is widely accepted that nucleic acid cargos are released into the cytoplasm before fusing with the lysosome, the specific sites where this release occurs continue to be debated [140]. Various studies are reporting that LNPs

formulation and modification of LNPs with thermo/photosensitive molecules, or pathogen-derived peptides/proteins. (c) An example strategy to reduce exocytosis is the inhibition of NPC1. Adapted from [140]

release the siRNA cargo in early endosomes [150], late endosomes [151], or hybrid compartments having the properties of early and late endosomes [150, 151]. This underscores the impact of LNPs' physicochemical properties and different cell types on the endosomal escape process. Regarding the structure of lipids in LNPs, the ionizable lipids can be engineered to mimic inverted-cone phospholipids to trigger the formation of hexagonal phases, leading to efficient cargo escape. Another strategy includes the introduction of unsaturated bonds or biodegradable groups into ionizable lipids [138]. Moreover, incorporating unsaturated phosphatidylethanolamines, such as DOPE, into the formulation increases the endosomal escape efficiency by inducing hexagonal membrane transformations (Fig. 9b) [156]. Similarly, modifications to CHOL or its substitution with analogs can be employed as alternative strategies to optimize endosomal escape. For example, replacing CHOL with plant-derived β-sitosterol has improved the transfection efficiency of
LNPs, potentially thanks to its ability to facilitate enhanced fusion with the endosome [158, 202]. Furthermore, modifying LNPs with pathogen-derived peptides or proteins (e.g., HIV-1 TAT, PV L2, HA2, and CADY) represents another strategy to facilitate endosomal escape through membrane destabilization, fusion, or pore formation (Fig. 9b) [140]. Stimuli-responsive LNPs (e.g., thermoresponsive, photoresonspective) have also been investigated to enhance endosomal escape (Fig. 9b) [203, 204].

Interestingly, limiting exocytosis also represents an alternative strategy to increase the siRNA availability in the cytoplasm [140]. Altering the LNP composition, such as using hydroxycholesterols instead of cholesterol [202], or inhibiting a critical modulator of the exocytosis pathway, such as Niemann-Pick type C1 (NPC1) (Fig. 9c) [149], has been demonstrated to improve the retention of lipid-based nanoparticles.

Despite considerable progress in recent years and ongoing efforts, the intracellular delivery efficiency of siRNA-LNP systems continues to pose a significant challenge. Addressing this limitation is crucial for harnessing their full therapeutic potential.

## Duration of the inhibitory effect of RNA interference

Achieving long-term therapeutic knockout effects often requires repeated dosing, which can sometimes limit its application. Ongoing research aims to further prolong this inhibition and to enable more effective and less frequent therapeutic interventions. Although naked siRNAs and miRNAs are rapidly degraded, LNP delivery can significantly extend their stability and gene-inhibiting effects, which generally range from days to several weeks depending on the formulation and application [205].

One in vitro study revealed that siRNA protected in solid lipid nanoparticles (SLNPs) retains functional activity after a six-day incubation at 37 °C [206]. Another study measured the duration of the inhibitory effect obtained using a hydrophobic ion pairing approach that employs the cationic lipid DOTAP to load siRNA into tristearin SLNPs [207]. Intra-dermal injection of these nanocarriers into the footpads of mice resulted in prolonged siRNA release over 10–13 days.

The liver-targeted Patisiran was administered once every 3 weeks during the Phase III trial [208]. However, few reports show how long the inhibitory effects last in cancer cells. So far, there has been significant variability in dosage frequency regarding Phase I cancer RNAi clinical trials, ranging from once to twice per week to twice a month [209–211].

Regarding the activity in macrophages, past studies on siRNA have shown that its dilution due to cell division may affect the duration of gene silencing [212]. The siRNA

molecules can achieve target protein inhibition superior to 80% at nanomolar concentrations, and their enhanced intracellular stability enables knockdown that can last for weeks in nondividing cells [212]. Using polymer nanoparticles to deliver siRNA against TNF-α oversecreted in macrophages, the inhibition lasted at least one week [213]. Regarding miRNA and given these factors, it is more accurate to think of miRNA silencing in macrophages as a dynamic and continuous process that can last as long as the miRNA is present and active, and its target mRNA is being expressed. Like for siRNA, the strength and specificity of the silencing effect might fluctuate based on the cellular environment and all other factors listed above.

## Preclinical studies using siRNA or miRNA-LNPs

This section reviews selected preclinical studies published recently that utilize siRNA or miRNA-LNPs to reprogram the TME, yielding promising therapeutic outcomes. (Table 1). Shobaki et al. [5] developed siRNA-LNPs based on a pH-sensitive cationic lipid CL4H6 to silence STAT3 and HIF-1α in TAMs. Following intravenous administration, siRNA-loaded CL4H6-LNPs demonstrated a high uptake and efficient gene silencing in TAMs in a human tumor xenograft of renal cell carcinoma (OS-RC-2) model, triggering an anti-tumor therapeutic response. Notably, the treatment was associated with an increased infiltration of macrophages into the TME, an increased tendency toward M1 polarization, and a reduction in angiogenesis and tumor cell activation [5].

In the study by Zhou et al. [214], the researchers synthesized siRNA-LNPs targeting the MerTK receptor on TAMs, which play a role in clearing apoptotic cells. They showed that inhibiting MerTK results in the accumulation of apoptotic cells within the TME, which triggers a pro-inflammatory response. Their treatment enhanced antitumor immunity in both liver and peritoneal metastasis models of colorectal cancer. While focusing on inhibiting MerTK-mediated efferocytosis, the results suggest a functional reprogramming of TAMs toward the M1 phenotype. This is evidenced by increased and decreased classical M1 and M2 markers in the IL-4-treated BMDM cellular model.

Furthermore, Yong et al. [215] developed anti-PD-L1 antibody-functionalized LNPs loaded with siRNA against heme oxygenase-1 (HO1) to simultaneously target cancer cells and tumor myeloid cells, aiming to achieve a dual effect of enhanced chemotherapeutic efficacy and immunological reprogramming. The findings demonstrated that HO1 inhibition sensitizes tumor cells to conventional chemotherapeutics and boosts the immune response by reprogramming tumor myeloid cells. Following LNP treatment with doxorubicin, a notable reduction in total myeloid cells
<table><caption>**Table 1** Preclinical studies employing RNA interference-LNPs in cancer immunotherapy</caption><thead><tr><th>Target</th><th>Composition</th><th>Targeting ligand</th><th>Cell/animal model</th><th>Administration route for in vivo studies</th><th>Effects</th><th>Ref</th></tr></thead><tbody><tr><td rowspan="4"><strong>siRNA</strong></td><td>siSTAT3 &amp;<br>siHIF-1α</td><td>CL4H6: CHOL:<br>PEG- lipid (DMG-PEG2000 or<br>DSG-PEG2000)</td><td>None</td><td>- Mice bearing human<br>tumor xenograft of renal<br>cell carcinoma (OS-RC-2)</td><td>IV</td><td>- Higher infiltration of macrophages into the TME and increase in the<br>level of M1 macrophages<br>- Reduced angiogenesis and tumor cell activation/invasiveness</td></tr><tr><td>siMerTK</td><td>DLin-MC3-DMA:<br>DSPC: CHOL:<br>DMG-PEG2000</td><td>None</td><td>- IL-4-treated BMDMs<br>- Mice bearing CT26 and<br>MC38 liver metastasis &amp;<br>Mice bearing CT26 peritoneal metastasis of colorectal cancer</td><td>IV (liver metastasis)<br>IP (peritoneal metastasis)</td><td>- Increased level of M1 (iNOS) and decreased level of M2 (Arg1) markers in vitro<br>- Reduced tumor growth and better survival in vivo</td></tr><tr><td>siHO1</td><td>Lipid 8:<br>DSPC: CHOL:<br>DMG-PEG2000</td><td>Anti-PD-L1<br>antibody</td><td>- Ex vivo bone marrow cells<br>- Mice bearing B16F10<br>melanoma</td><td>IV</td><td>- Increased levels of pro-inflammatory (TNF-α and IL12p40) and<br>decreased levels of anti-inflammatory (IL-10) cytokines in ex vivo study<br>- Enhanced sensitivity to chemotherapeutics and improved responsiveness<br>to immune checkpoint inhibitor therapy<br>- Reduced TAMs in the TME, higher infiltration of CD8+ cytotoxic T<br>cells, and reduced tumor growth and prolonged survival (in combination<br>with chemotherapy and an immune checkpoint inhibitor)</td></tr><tr><td>siPDL1 &amp;<br>mOX40L</td><td>DLin-MC3-DMA:<br>DOPE: CHOL:<br>C16-PEG2000</td><td>None</td><td>- Mouse macrophage cell<br>line, J774<br>- Mice bearing B16F10<br>melanoma</td><td>IT</td><td>- Increased level of M1-associated markers (CD80 and CD86) in vitro<br>- Reduced tumor growth, higher infiltration of CD4+ and CD8+ cells in<br>the TME, and immune activation within tumor-draining lymph nodes<br>- Internalization by immune cells (CD45+leukocytes) within the TME,<br>indicating their potential to reprogram TAMs</td></tr><tr><td rowspan="2"><strong>miRNA</strong></td><td>miRNA-199-5p</td><td>Dlin-MC3 DMA:<br>DMG-PEG:<br>DSPC: CHOL<br>DSPE-PEG-M2<br>pep</td><td>M2 targeting Peptide</td><td>-</td><td>IV</td><td>- Significant anti-tumor effect with an improved immune<br>microenvironment<br>- Reprogramming of M2-like macrophages through downregulation of<br>miR-148a-3p and miR-1981-5p</td></tr><tr><td>miRNA-204-5p</td><td>DODAP:<br>PEG2000-CER:<br>DSPC: CHOL</td><td>None</td><td>- -In vitro: THP-1<br>differentiated<br>- In vivo: A375 melanoma<br>and M14 melanoma mouse<br>model</td><td>IV</td><td>- Reduced melanoma cell growth<br>- Restricted recruitment and reprogramming of pro-tumoral macrophages</td></tr><tr><td>miRNA-155</td><td>EDOPC: DC-CHOL: DPHPE:<br>DSPE-PEG</td><td>Anti-SIRPα<br>antibody</td><td>-</td><td>IT</td><td>- Reprogramming of TAMs<br>- Activation of T cells' phagocytic activity against tumor cells through the<br>blockade of CD47-SIRPα interaction</td></tr></tbody></table>

<figure><img src="image_13.png" /></figure>
and M2-like TAMs in the tumor was observed in B16F10
melanoma-bearing mice. Further investigation on ex vivo
bone marrow cells indicated that the treatment inhibits the
differentiation of monocytes into TAMs and increases the
level of pro-inflammatory cytokines, including TNF-α and
IL12p40, while decreasing the anti-inflammatory cytokine
IL-10.

In another study, Walters et al. [105] successfully formu-
lated LNPs that encapsulate a combination of siRNA against
PD-L1 and mRNA encoding OX40L. The objective was to
silence and stimulate the expression of immunosuppressive
and immunostimulatory immune checkpoint targets, respec-
tively, for reprogramming the TME towards a more immu-
nostimulatory state. The researchers showed that these
SNALPs increased the M1-associated markers CD80 and
CD86 in a mouse macrophage cell line, J774. Subsequent
intratumoral administration in mice bearing B16F10 mela-
noma has resulted in a higher level of CD4+ and CD8+ infil-
trates in the tumor and a reduction in tumor growth. While
not directly related to TAMs, the internalization of LNPs by
immune cells (CD45+leukocytes) within the TME suggests
that they have the potential to be developed for reprogram-
ming TAMs in vivo.

Xia et al. [216] delivered an LNP-entrapped siRNA
targeting DICER1, a mutation highly expressed in TAMs
and closely associated with M2 polarization in colorectal
cancer liver metastasis. After intravenous administration,
the siRNA exerted a significant anti-tumor effect with an
improved immune microenvironment in a colorectal cancer
liver metastasis mouse model. Macrophage depletion exper-
iments further suggested that this effect largely depended on
the presence of TAMs. Mechanistically, DICER inhibition
reprogrammed M2-like macrophages by downregulating
miR-148a-3p and miR-1981-5p [216].

There are two cases where LNPs were used to deliver
miRNA for macrophage reprogramming in cancer. In the
first one, LNPs co-encapsulating miRNA-199-5p and
miRNA-204-5p, combined with target therapy, inhibited
tumor growth after intravenous administration in a mela-
noma mouse model and blocked the development of drug
resistance. Mechanistically, they acted by directly reducing
melanoma cell growth and indirectly hampering the recruit-
ment and reprogramming of pro-tumoral macrophages
[217]. In a recent study, lipid nanoparticles were modified
with an anti-SIRPα antibody for the targeted delivery of
miRNA-155 to TAMs to enhance their anti-tumoral phe-
notypes within the tumor microenvironment [218]. The
SIRPα-specific binding of the LNPs to the surface of TAMs
allowed their reprogrammation through the intracellular
delivery of miR155. These reprogrammed TAMs increase
the secretion of pro-inflammatory cytokines. In addition to
TAM-specific miRNA delivery, the binding of SIRPα by the

anti-SIRPα antibody blocks the interaction between CD47 on tumor cells and SIRPα on TAMs. This interruption of the CD47-SIRPα interaction activates the phagocytic activity of T cells against tumor cells [218]. Taken as a whole, all these fascinating results are too recent, and their clinical translation remains ongoing. However, the further advancement of these strategies should be eased by the availability of LNP formulations already on the market.

Challenges and future directions

Although promising, there are several challenges associated
with RNA interference-LNP-mediated macrophage repro-
gramming. This section will mainly focus on the delivery
challenges. However, concerning target cells, one of the
key hurdles is the incomplete understanding of macrophage
heterogeneity. Macrophages exhibit diverse phenotypes and
functions within different physiological and pathological
contexts. While the M1/M2 polarization model provides a
valuable framework, it oversimplifies the complex spectrum
of macrophage states observed in vivo, especially in the
dynamic TME. Context-dependent changes in expression
characterize polarization, and it is essential to note that not
all M1 or M2 markers necessarily upregulate or downregu-
late upon activation. Therefore, single-marker assessments
may misclassify macrophages, highlighting the importance
of employing a panel of M1 and M2 markers [219]. More-
over, emerging single-cell sequencing [220–224] and spa-
tial transcriptomics [225–227] techniques may allow a more
profound understanding of macrophage diversity in vivo.
These advanced methods have already revealed distinct
subpopulations of TAMs, but the molecular mechanisms
governing their plasticity remain poorly understood [228].

In addition to the above, targeting specific tissues or cells
beyond the liver using RNA-LNPs via IV administration
represents another ongoing challenge [16, 229]. The need to
target particular macrophage subsets within the TME makes
it even more complex, where M1-like and M2-like pheno-
types coexist. While targeting M2 TAMs, it should be con-
sidered that the drug delivery system has a minimal effect on
the tissue-resident M2 macrophages in healthy organs [6] to
prevent the activation of M1 macrophages in non-target tis-
sues, which could lead to a systemic inflammatory reaction
[29]. Considering all these challenges, it is unsurprising that
local injection has been predominantly used over IV admin-
istration in clinical trials using RNA interference-LNPs [16].
However, intratumoral injection is unsuitable for treating
metastatic or hematologic cancers [13]. Therefore, develop-
ing advanced targeting strategies (e.g., active or endogenous
targeting) is needed to increase the therapeutic efficacy of
RNA-LNPs while reducing the risk of side effects [6, 125].
Understanding and modulating the protein corona could improve nanoparticle biodistribution [140, 229]. Recent research has revealed that selective organ targeting (SORT) LNPs can achieve preferential accumulation in extrahepatic organs, such as the spleen and lungs. This is accomplished by manipulating nanoparticle surface interactions with serum proteins, ultimately guiding receptor-mediated uptake [229]. Also, optimizing surface modifications, such as PEGylation, is essential to prolong circulation time, minimize hepatic sequestration, and improve tumor accumulation [13]. Moreover, due to tumors' highly complex immune microenvironment, macrophage-centered immunotherapies alone may not be potent enough to eliminate tumors [228], and the combination of TAM reprogramming with other therapeutic modalities (e.g., chemotherapy, radiotherapy, or immunotherapy) should be further explored [2, 46]. LNP-mediated co-delivery strategies, including multiple RNAs targeting distinct pathways or siRNA-mRNA pairs, also require further investigation [13, 105]. In addition, the typical characteristics of TME, such as acidity, abnormal vasculature, hypoxia, elevated interstitial pressure, and dense stromal network, could restrict the efficient delivery of RNA interference-LNPs. These complexities highlight the necessity for appropriate in vitro (e.g., 3D models) and in vivo models to evaluate the distribution of siRNA-LNPs [13]. Recent efforts have also explored various strategies, such as pH-sensitive nanoparticles [6], to exploit the TME-associated characteristics to enhance drug delivery to tumors. At the cellular level, there is a need to understand endosomal escape better in order to improve the amount of RNA reaching the cytoplasm.

Another critical research gap regarding RNA interference-LNPs is long-term safety concerns. LNPs pose immunogenicity and toxicity challenges, primarily due to ionizable cationic lipids and PEG-lipids [13]. The immunogenicity of ionizable cationic lipids has been primarily linked to the hydrophilic amine headgroup, which has been demonstrated to trigger both the innate and adaptive immune pathways by inducing lipid-raft formation and binding to the receptors TLR4 and CD1d [152]. A critical challenge, therefore, is to design new ionizable lipids that are more effective in endosomal escape and less immunogenic. Another major concern is the risk of complement activation-related pseudoallergy (CARPA), a hypersensitivity reaction caused by the interaction of PEGylated LNPs with the complement system. While PEGylation improves the pharmacokinetics of LNPs, repeated administration could elicit anti-PEG IgG and IgM responses, activating the complement cascade [140]. Therefore, a deeper investigation into the interplay between LNP components and immune system molecules is essential to enhance the safety profile of siRNA-LNPs [152]. Additionally, the binding of anti-PEG antibodies on PEGylated LNPs

accelerates nanoparticle clearance by immune cells through Fc receptor-mediated pathways, reducing the efficacy of subsequent treatments. Thus, emerging strategies focus on replacing PEG with alternative molecules to reduce safety concerns while optimizing therapeutic efficacy [140]. Long-term off-target effects represent another key issue. The possibility of siRNA-LNP accumulation in non-target organs poses a risk of cumulative toxicity, inflammation, and disruption of normal tissue function [140]. Beyond off-target effects, while RNA interference-LNP-based macrophage reprogramming is promising, its stability over time is uncertain. There is a possibility that reprogrammed macrophages could revert to their tumor-promoting states due to ongoing signals from the TME. Thus, long-term studies are required to assess the durability of macrophage reprogramming.

## Conclusion

Macrophages can act as tumor supporters or fighters, and their plasticity makes them an attractive target for therapeutic reprogramming to treat cancer. siRNA and miRNA-LNPs represent a potent platform for regulating macrophage function thanks to their precise gene silencing capabilities and the efficient delivery properties of LNPs. Recent advances in LNP composition and targeting strategies have greatly enhanced the therapeutic potential of this drug delivery system. However, several challenges remain. Issues related to macrophage complexity, in vivo targeting specificity and long-term safety concerns must be addressed for its clinical translation as a viable cancer immunotherapy strategy. Unlocking the full potential of RNA interference-LNP-based macrophage reprogramming will provide a transformative approach to treating cancer and a wide range of macrophage-related disorders, including chronic inflammation, infection, and autoimmune diseases.

**Acknowledgements** The authors thank the French Institut National du Cancer (2021-084 project) for granting a fellowship to SZ. Figures 1, 2, 3, 4, 5, 6, 7, 8 and 9 were produced using Biorender.

**Author contributions** Material preparation, data collection and the first draft of the manuscript was written by SG and revised by JV, FF and EF.

**Funding** Open access funding provided by Université Paris-Saclay. The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

## Declarations

**Ethics approval and consent to participate** This article does not contain any studies with human participants or animals performed by any of the authors.
**Consent for publication** Not applicable.

**Competing interests** The authors have no relevant financial or non-financial interests to disclose.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

## References

1. Labani-Motlagh A, Ashja-Mahdavi M, Loskog A. The tumor microenvironment: A milieu hindering and obstructing antitumor immune responses. Front Immunol. 2020;11:1–22.

2. Belgiovine C, Digifico E, Anfray C, Ummarino A, Andón FT. Targeting tumor-associated macrophages in anti-cancer therapies: convincing the traitors to do the right thing. J Clin Med. 2020;9:1–24.

3. Mantovani A, Allavena P. The interaction of anticancer therapies with tumor-associated macrophages. J Exp Med. 2015;212:435–45.

4. Strizova Z, Benesova I, Bartolini R, Novysedlak R, Cecrdlova E, Foley LK, et al. M1/M2 macrophages and their overlaps - myth or reality? Clin Sci. 2023;137:1067–93.

5. Shobaki N, Sato Y, Suzuki Y, Okabe N, Harashima H. Manipulating the function of tumor-associated macrophages by siRNA-loaded lipid nanoparticles for cancer immunotherapy. J Control Release. 2020;325:235–48.

6. Xiao H, Guo Y, Li B, Li X, Wang Y, Han S, et al. M2-Like Tumor-Associated Macrophage-Targeted codelivery of STAT6 inhibitor and IKKβ SiRNA induces M2-to-M1 repolarization for cancer immunotherapy with low immune side effects. ACS Cent Sci. 2020;6:1208–22.

7. Cassetta L, Pollard JW. Targeting macrophages: therapeutic approaches in cancer. Nat Rev Drug Discov. 2018;17:887–904.

8. Corrales L, Glickman LH, McWhirter SM, Kanne DB, Sivick KE, Katibah GE, et al. Direct activation of STING in the tumor microenvironment leads to potent and systemic tumor regression and immunity. Cell Rep. 2015;11:1018–30.

9. Vonderheide RH. CD40 agonist antibodies in cancer immunotherapy. Annu Rev Med. 2020;71:47–58.

10. Georgoudaki AM, Prokopec KE, Boura VF, Hellqvist E, Sohn S, Östling J, et al. Reprogramming Tumor-Associated macrophages by antibody targeting inhibits cancer progression and metastasis. Cell Rep. 2016;15:2000–11.

11. Yamada Y, Sato Y, Nakamura T, Harashima H. Innovative cancer nanomedicine based on immunology, gene editing, intracellular trafficking control. J Control Release. 2022;348:357–69.

12. Hu B, Zhong L, Weng Y, Peng L, Huang Y, Zhao Y et al. Therapeutic siRNA: state of the art. Signal Transduct Target Ther. 2020;5:101. Available from: https://doi.org/10.1038/s41392-020-0-207-x

13. El Moukhtari SH, Garbayo E, Amundarain A, Pascual-Gil S, Carrasco-León A, Prosper F, et al. Lipid nanoparticles for SiRNA delivery in cancer treatment. J Control Release. 2023;361:130–46.

14. Saw PE, Song EW. SiRNA therapeutics: a clinical reality. Sci China Life Sci. 2020;63:485–500.

15. Fang E, Liu X, Li M, Zhang Z, Song L, Zhu B, et al. Advances in COVID-19 mRNA vaccine development. Signal Transduct Target Ther. 2022;7:1–31.

16. Albertsen CH, Kulkarni J, Witzigmann D, Petersson K, Simonsen JB. The role of lipid components in lipid nanoparticles for vaccines and gene therapy. Adv Drug Deliv Rev. 2022;114416.

17. Italiani P, Boraschi D. From monocytes to M1/M2 macrophages: phenotypical vs. functional differentiation. Front Immunol. 2014;5:1–22.

18. Nielsen SR, Schmid MC. Macrophages as Key Drivers of Cancer Progression and Metastasis. Mediators Inflamm. 2017;2017.

19. Dey A, Allen J, Hankey-Giblin PA. Ontogeny and polarization of macrophages in inflammation: blood monocytes versus tissue macrophages. Front Immunol. 2015;6:1–15.

20. Back PI, Yu M, Modaresahmadi S, Hajimirzaei S, Zhang Q, Islam MR et al. Immune implications of Cholesterol-Containing lipid nanoparticles. ACS Nano. 2024.

21. Chen S, Saeed AFUH, Liu Q, Jiang Q, Xu H, Xiao GG et al. Macrophages in immunoregulation and therapeutics. Signal Transduct Target Ther. 2023;8.

22. Martinez FO, Gordon S. The M1 and M2 paradigm of macrophage activation: time for reassessment. F1000Prime Rep. 2014;6:1–13.

23. Huang X, Li Y, Fu M, Xin H-B. Polarizing macrophages in vitro. In: Rousselet G, editor. Macrophages methods Protoc methods mol biol. Springer Nature; 2018. pp. 119–26.

24. Tran TH, Rastogi R, Shelke J, Amiji MM. Modulation of macrophage functional Polarity towards Anti-Inflammatory phenotype with plasmid DNA delivery in CD44 targeting hyaluronic acid nanoparticles. Sci Rep. 2015;5:1–15.

25. Quail DF, Joyce JA. Molecular pathways: Deciphering mechanisms of resistance to macrophage-targeted therapies. Clin Cancer Res. 2017;23:876–84.

26. Ross EA, Devitt A, Johnson JR. Macrophages: the good, the bad, and the gluttony. Front Immunol. 2021;12:1–22.

27. Jayasingam SD, Citartan M, Thang TH, Mat Zin AA, Ang KC, Ch'ng ES. Evaluating the polarization of Tumor-Associated macrophages into M1 and M2 phenotypes in human cancer tissue: technicalities and challenges in routine clinical practice. Front Oncol. 2020;9:1–9.

28. Mantovani A, Sica A, Sozzani S, Allavena P, Vecchi A, Locati M. The chemokine system in diverse forms of macrophage activation and polarization. Trends Immunol. 2004;25:677–86.

29. Genard G, Lucas S, Michiels C. Reprogramming of tumor-associated macrophages with anticancer therapies: radiotherapy versus chemo- and immunotherapies. Front Immunol. 2017;8.

30. Molgora M, Colonna M. Turning enemies into allies—reprogramming tumor-associated macrophages for cancer therapy. Med. 2021;2:666–81.

31. Li L, Yu R, Cai T, Chen Z, Lan M, Zou T, et al. Effects of immune cells and cytokines on inflammation and immunosuppression in the tumor microenvironment. Int Immunopharmacol. 2020;88:106939.

32. Qin R, Ren W, Ya G, Wang B, He J, Ren S, et al. Role of chemokines in the crosstalk between tumor and tumor-associated macrophages. Clin Exp Med. 2023;23:1359–73.

33. Hu G, Guo M, Xu J, Wu F, Fan J, Huang Q, et al. Nanoparticles targeting macrophages as potential clinical therapeutic agents against cancer and inflammation. Front Immunol. 2019;10:1998.

34. Jung KY, Cho SW, Kim YA, Kim D, Oh BC, Park DJ, et al. Cancers with higher density of tumor-associated macrophages
were associated with poor survival rates. J Pathol Transl Med. 2015;49:318-24.

35. wen Zhang Q, Liu L, Gong C, yang, Shi Hshan, Zeng Yhui, Wang X et al. ze., Prognostic Significance of Tumor-Associated Macrophages in Solid Tumor: A Meta-Analysis of the Literature. PLoS One. 2012;7.

36. Ren CX, Leng RX, Fan YG, Pan HF, Li BZ, Wu CH, et al. Intratumoral and peritumoral expression of CD68 and CD206 in hepatocellular carcinoma and their prognostic value. Oncol Rep. 2017;38:886-98.

37. Massi D, Rulli E, Cossa M, Valeri B, Rodolfo M, Merelli B, et al. The density and Spatial tissue distribution of CD8 + and CD163 + immune cells predict response and outcome in melanoma patients receiving MAPK inhibitors. J Immunother Cancer. 2019;7:1-13.

38. Fortis SP, Sofopoulos M, Sotiriadou NN, Haritos C, Vaxevanis CK, Anastasopoulou EA et al. Differential intratumoral distributions of CD8 and CD163 immune cells as prognostic biomarkers in breast cancer. J Immunother Cancer. 2017;5.

39. Su CY, Fu XL, Duan W, Yu PW, Zhao YL. High density of CD68 + tumor-associated macrophages predicts a poor prognosis in gastric cancer mediated by IL-6 expression. Oncol Lett. 2018;15:6217-24.

40. Kostine M, Briaire-de Bruijn IH, Cleven AHG, Vervat C, Corver WE, Schilham MW et al. Increased infiltration of M2-macrophages, T-cells and PD-L1 expression in high grade leiomyosarcomas supports immunotherapeutic strategies. Oncoimmunology. 2018;7.

41. Chen Y, Song Y, Du W, Gong L, Chang H, Zou Z. Tumor-associated macrophages: an accomplice in solid tumor progression. J Biomed Sci. 2019;26:1-13.

42. Fu LQ, Du WL, Cai MH, Yao JY, Zhao YY, Mou XZ. The roles of tumor-associated macrophages in tumor angiogenesis and metastasis. Cell Immunol. 2020;353:104119.

43. Jinushi M, Chiba S, Yoshiyama H, Masutomi K, Kinoshita I, Dosaka-Akita H, et al. Tumor-associated macrophages regulate tumorigenicity and anticancer drug responses of cancer stem/initiating cells. Proc Natl Acad Sci U S A. 2011;108:12425-30.

44. Fan QM, Jing YY, Yu GF, Kou XR, Ye F, Gao L, et al. Tumor-associated macrophages promote cancer stem cell-like properties via transforming growth factor-beta1-induced epithelial-mesenchymal transition in hepatocellular carcinoma. Cancer Lett. 2014;352:160-8.

45. Song S, Xia H, Guo M, Wang S, Zhang S, Ma P, et al. Role of macrophage in nanomedicine-based disease treatment. Drug Deliv. 2021;28:752-66.

46. Quaranta V, Schmid MC. Macrophage-Mediated subversion of Anti-Tumour immunity. Cells. 2019;8:747.

47. Shime H, Matsumoto M, Oshiumi H, Tanaka S, Nakane A, Iwakura Y, et al. Toll-like receptor 3 signaling converts tumor-supporting myeloid cells to tumoricidal effectors. Proc Natl Acad Sci U S A. 2012;109:2066-71.

48. Maeda A, Digifico E, Andon FT, Mantovani A, Allavena P. Poly(I:C) stimulation is superior than imiquimod to induce the antitumoral functional profile of tumor-conditioned macrophages. Eur J Immunol. 2019;49:801-11.

49. Dacoba TG, Anfray C, Mainini F, Allavena P, Alonso MJ, Torres Andón F, et al. Arginine-Based Poly(I:C)-Loaded nanocomplexes for the polarization of macrophages toward M1-Antitumoral effectors. Front Immunol. 2020;11:1-17.

50. Wang G, Zhao J, Zhang M, Wang Q, Chen B, Hou Y, et al. Ferumoxytol and Cpg oligodeoxynucleotide 2395 synergistically enhance antitumor activity of macrophages against NSCLC with EGFR1858r/t790m mutation. Int J Nanomed. 2019;14:4503-15.

51. Dong X, Yang A, Bai Y, Kong D, Lv F. Dual fluorescence imaging-guided programmed delivery of doxorubicin and CpG nanoparticles to modulate tumor microenvironment for effective chemo-immunotherapy. Biomaterials. 2020;230:119659.

52. Shi Y, Felder MAR, Sondel PM, Rakhmilevich AL. Synergy of anti-CD40, CpG and MPL in activation of mouse macrophages. Mol Immunol. 2015;66:208-15.

53. Turco V, Pfleiderer K, Hunger J, Horvat NK, Karimian-Jazi K, Schregel K et al. T cell-independent eradication of experimental glioma by intravenous TLR7/8-agonist-loaded nanoparticles. Nat Commun 2023 141. 2023 [cited 2025 Jul 18];14:1-15. Available from: https://www.nature.com/articles/s41467-023-36321-6

54. Miao L, Qi J, Zhao Q, Wu QN, Wei DL, Wei XL, et al. Targeting the STING pathway in tumor-associated macrophages regulates innate immune sensing of gastric cancer cells. Theranostics. 2020;10:498-515.

55. Li Y, James SJ, Wyllie DH, Wynne C, Czibula A, Bukhari A, et al. TMEM203 is a binding partner and regulator of STING-mediated inflammatory signaling in macrophages. Proc Natl Acad Sci U S A. 2019;116:16479-88.

56. Amouzegar A, Chelvanambi M, Filderman JN, Storkus WJ, Luke JJ. STING Agonists as Cancer Therapeutics. Cancers. 2021, Vol 13, Page 2695. 2021 [cited 2025 Jul 18];13:2695. Available from: https://www.mdpi.com/2072-6694/13/11/2695/htm

57. Huang C, Shao N, Huang Y, Chen J, Wang D, Hu G, et al. Overcoming challenges in the delivery of STING agonists for cancer immunotherapy: A comprehensive review of strategies and future perspectives. Mater Today Bio. 2023;23:100839.

58. Harrington KJ, Brody J, Ingham M, Strauss J, Cemerski S, Wang M et al. Preliminary results of the first-in-human (FIH) study of MK-1454, an agonist of stimulator of interferon genes (STING), as monotherapy or in combination with pembrolizumab (pembro) in patients with advanced solid tumors or lymphomas. Ann Oncol. 2018 [cited 2025 Jul 18];29:vii712. Available from: https://www.annalsofoncology.org/action/showFullText?pii=S0923753419504069

59. Cheng N, Watkins-Schulz R, Junkins RD, David CN, Johnson BM, Montgomery SA et al. A nanoparticle-incorporated STING activator enhances antitumor immunity in PD-L1-insensitive models of triple-negative breast cancer. JCI Insight. 2018;3.

60. Liu Y, Crowe WN, Wang L, Lu Y, Petty WJ, Habib AA, et al. An inhalable nanoparticulate STING agonist synergizes with radiotherapy to confer long-term control of lung metastases. Nat Commun. 2019;10:1-15.

61. Yang Y, Fang Y, Du X, Ying Z, Lu X, Zhou J. Application of nanoparticles with activating STING pathway function in tumor synergistic therapy. Int Immunopharmacol. 2025;148:114013.

62. McAndrews KM, Che SPY, LeBleu VS, Kalluri R. Effective delivery of STING agonist using exosomes suppresses tumor growth and enhances antitumor immunity. J Biol Chem. 2021 [cited 2025 Jul 18];296:100523. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC8042450/

63. Zhang JQ, Zeng S, Vitiello GA, Seifert AM, Medina BD, Beckman MJ, et al. Macrophages and CD8β T cells mediate the antitumor efficacy of combined CD40 ligation and Imatinib therapy in Gastrointestinal stromal tumors. Cancer Immunol Res. 2018;6:434-47.

64. Ji ZZ, Chan MKK, Chan ASW, Leung KT, Jiang X, To KF, et al. Tumour-associated macrophages: versatile players in the tumour microenvironment. Front Cell Dev Biol. 2023;11:1-18.

65. Wiehagen KR, Girgis NM, Yamada DH, Smith AA, Chan SR, Grewal IS et al. Combination of CD40 agonism and CSF-1R blockade reconditions tumor-associated macrophages and drives potent antitumor immunity. Cancer Immunol Res. 2017 [cited 2025 Jul 19];5:1109-21. Available from: /cancerimmunolres/article/5/12/1109/468777/Combination-of-CD40-Agonism-and-CSF-1R-Blockade.
66. Perry CJ, Muñoz-Rojas AR, Meeth KM, Kellman LN, Amezquita RA, Thakral D et al. Myeloid-targeted immunotherapies act in synergy to induce inflammation and antitumor immunity. J Exp Med. 2018 [cited 2025 Jul 19];215:877-93. Available from: https://doi.org/10.1084/jem.20171435

67. Anfray C, Ummarino A, Andón FT, Allavena P. Current Strategies to Target Tumor-Associated-Macrophages to Improve Anti-Tumor Immune Responses. Cells 2020, Vol 9, Page 46. 2019 [cited 2025 Jul 19];9:46. Available from: https://www.mdpi.com/2073-4409/9/1/46/htm

68. Salomon R, Dahan R. Next generation CD40 agonistic antibodies for cancer immunotherapy. Front Immunol. 2022;13:940674. Available from: www.frontiersin.org.

69. Bergamaschi A, Tagliabue E, Sørlie T, Naume B, Triulzi T, Orlandi R et al. Extracellular matrix signature identifies breast cancer subgroups with different clinical outcome. J Pathol. 2008 [cited 2025 Jul 19];214:357-67. Available from: https://onlinelibrary.wiley.com/doi/full/https://doi.org/10.1002/path.2278

70. Sun H, Song J, Weng C, Xu J, Huang M, Huang Q et al. Association of decreased expression of the macrophage scavenger receptor MARCO with tumor progression and poor prognosis in human hepatocellular carcinoma. J Gastroenterol Hepatol. 2017 [cited 2025 Jul 19];32:1107-14. Available from: https://onlinelibrary.wiley.com/doi/full/https://doi.org/10.1111/jgh.13633

71. La Fleur L, Boura VF, Alexeyenko A, Berglund A, Pontén V, Mattsson JSM et al. Expression of scavenger receptor MARCO defines a targetable tumor-associated macrophage subset in non-small cell lung cancer. Int J Cancer. 2018 [cited 2025 Jul 19];143:1741-52. Available from: https://onlinelibrary.wiley.com/doi/full/https://doi.org/10.1002/ijc.31545

72. Mueller T, Freystein J, Lucas H, Schmoll HJ. Efficacy of a Bispecific Antibody Co-Targeting VEGFA and Ang-2 in Combination with Chemotherapy in a Chemoresistant Colorectal Carcinoma Xenograft Model. Mol 2019, Vol 24, Page 2865. 2019 [cited 2025 Jul 19];24:2865. Available from: https://www.mdpi.com/1420-3049/24/16/2865/htm

73. Solecki G, Osswald M, Weber D, Glock M, Ratliff M, Müller HJ et al. Differential Effects of Ang-2/VEGF-A Inhibiting Antibodies in Combination with Radio- or Chemotherapy in Glioma. Cancers 2019, Vol 11, Page 314. 2019 [cited 2025 Jul 19];11:314. Available from: https://www.mdpi.com/2072-6694/11/3/314/htm

74. Murata Y, Kotani T, Ohnishi H, Matozaki T. The CD47-SIRPα signalling system: its physiological roles and therapeutic application. J Biochem. 2014 [cited 2025 Jul 19];155:335-44. Available from: https://doi.org/10.1093/jb/mvu017

75. Yang H, Shao R, Huang H, Wang X, Rong Z, Lin Y. Engineering macrophages to phagocytose cancer cells by blocking the CD47/SIRPα axis. Cancer Med. 2019 [cited 2025 Jul 19];8:4245-53. Available from: https://onlinelibrary.wiley.com/doi/full/https://doi.org/10.1002/cam4.2332

76. Schürch CM, Roelli MA, Forster S, Wasmer MH, Brühl F, Maire RS et al. Targeting CD47 in Anaplastic Thyroid Carcinoma Enhances Tumor Phagocytosis by Macrophages and Is a Promising Therapeutic Strategy. Thyroid. 2019 [cited 2025 Jul 19];29:979-92. Available from: https://www.liebertpub.com/doi/https://doi.org/10.1089/thy.2018.0555

77. Gu S, Ni T, Wang J, Liu Y, Fan Q, Wang Y et al. CD47 Blockade Inhibits Tumor Progression through Promoting Phagocytosis of Tumor Cells by M2 Polarized Macrophages in Endometrial Cancer. J Immunol Res. 2018 [cited 2025 Jul 19];2018:6156757. Available from: https://onlinelibrary.wiley.com/doi/full/https://doi.org/10.1155/2018/6156757

78. Alvey CM, Spinler KR, Irianto J, Pfeifer CR, Hayes B, Xia Y et al. SIRPA-Inhibited, Marrow-Derived Macrophages Engorge, Accumulate, and Differentiate in Antibody-Targeted Regression of Solid Tumors. Curr Biol. 2017 [cited 2025 Jul 19];27:2065-2077.

e6. Available from: https://www.cell.com/action/showFullText?p ii=S0960982217307066

79. Ramesh A, Kumar S, Nandi D, Kulkarni A. CSF1R- and SHP2-Inhibitor-Loaded Nanoparticles Enhance Cytotoxic Activity and Phagocytosis in Tumor-Associated Macrophages. Adv Mater. 2019 [cited 2025 Jul 19];31:1904364. Available from: https://onlinelibrary.wiley.com/doi/full/https://doi.org/10.1002/adma.201904364

80. Kulkarni A, Chandrasekar V, Natarajan SK, Ramesh A, Pandey P, Nirgud J et al. A designer self-assembled supramolecule amplifies macrophage immune responses against aggressive cancer. Nat Biomed Eng 2018 28. 2018 [cited 2025 Jul 19];2:589-99. Available from: https://www.nature.com/articles/s41551-018-0254-6

81. Advani R, Flinn I, Popplewell L, Forero A, Bartlett NL, Ghosh N et al. CD47 Blockade by Hu5F9-G4 and Rituximab in Non-Hodgkin's Lymphoma. N Engl J Med. 2018 [cited 2025 Jul 19];379:1711-21. Available from: https://www.nejm.org/doi/full/https://doi.org/10.1056/NEJMoa1807315

82. Zhang C, Yang M, Ericsson AC. Function of macrophages in disease: current Understanding on molecular mechanisms. Front Immunol. 2021;12:1-12.

83. Huang SCC, Smith AM, Everts B, Colonna M, Pearce EL, Schilling JD, et al. Metabolic reprogramming mediated by the mTORC2-IRF4 signaling axis is essential for macrophage alternative activation. Immunity. 2016;45:817-30.

84. Huang SCC, Everts B, Ivanova Y, O'Sullivan D, Nascimento M, Smith AM, et al. Cell-intrinsic lysosomal lipolysis is essential for alternative activation of macrophages. Nat Immunol. 2014;15:846-55.

85. Rath M, Müller I, Kropf P, Closs EI, Munder M. Metabolism via arginase or nitric oxide synthase: two competing arginine pathways in macrophages. Front Immunol. 2014;5:1-10.

86. Wang XF, Wang HS, Wang H, Zhang F, Wang KF, Guo Q, et al. The role of indoleamine 2,3-dioxygenase (IDO) in immune tolerance: focus on macrophage polarization of THP-1 cells. Cell Immunol. 2014;289:42-8.

87. Chen X, Yao J, Zhang MY, Li R, Liu X, Qu YQ. IDO1 promotes the progression of NSCLC by regulating the polarization of M2 macrophages. Int J Gen Med. 2023;16:1713-33.

88. Song M, Liu T, Shi C, Zhang X, Chen X. Bioconjugated manganese dioxide nanoparticles enhance chemotherapy response by priming tumor-Associated macrophages toward M1-like phenotype and attenuating tumor hypoxia. ACS Nano. 2016;10:633-47.

89. Jung M, Mertens C, Brüne B. Macrophage iron homeostasis and polarization in the context of cancer. Immunobiology. 2015;220:295-304.

90. Burke S, Shergold A, Elder MJ, Whitworth J, Cheng X, Jin H, et al. Oncolytic Newcastle disease virus activation of the innate immune response and priming of antitumor adaptive responses in vitro. Cancer Immunol Immunother. 2020;69:1015-27.

91. Teresa Pinto A, Laranjeiro Pinto M, Patrícia Cardoso A, Monteiro C, Teixeira Pinto M, Filipe Maia A, et al. Ionizing radiation modulates human macrophages towards a pro-inflammatory phenotype preserving their pro-invasive and pro-angiogenic capacities. Sci Rep. 2016;6:1-15.

92. Klug F, Prakash H, Huber PE, Seibel T, Bender N, Halama N, et al. Low-Dose irradiation programs macrophage differentiation to an iNOS+/M1 phenotype that orchestrates effective T cell immunotherapy. Cancer Cell. 2013;24:589-602.

93. Guerriero JL, Sotayo A, Ponichtera HE, Castrillon JA, Pourzia AL, Schad S, et al. Class IIa HDAC Inhibition reduces breast tumours and metastases through anti-tumour macrophages. Nature. 2017;543:428-32.
94. de Groot AE, Pienta KJ. Epigenetic control of macrophage polarization: implications for targeting tumor-associated macrophages. Oncotarget. 2018;9:20908-27.

95. Gomez S, Tabernacki T, Kobyra J, Roberts P, Chiappinelli KB. Combining epigenetic and immune therapy to overcome cancer resistance. Semin Cancer Biol. 2020;65:99-113.

96. Walther M, Jenke R, Aigner A, Ewe A. Efficient polymeric nanoparticles for RNAi in macrophage reveal complex effects on polarization markers upon knockdown of STAT3/STAT6. Eur J Pharm Biopharm. 2024;197:114232.

97. Ortega RA, Barham W, Sharman K, Tikhomirov O, Giorgio TD, Yull FE. Manipulating the NF-κB pathway in macrophages using mannosylated, siRNA-delivering nanoparticles can induce immunostimulatory and tumor cytotoxic functions. Int J Nanomed. 2016;11:2163-77.

98. Jürgens DC, Winkeljann B, Kolog Gulko M, Jin Y, Möller J, Winkeljann J, et al. Efficient and targeted SiRNA delivery to M2 macrophages by smart polymer blends for M1 macrophage repolarization as a promising strategy for future cancer treatment. ACS Biomater Sci Eng. 2024;10:166-77.

99. Sun Y, Cronin MF, Mendonça MCP, Guo J, O'Driscoll CM. Sialic acid-targeted cyclodextrin-based nanoparticles deliver CSF-1R SiRNA and reprogram tumour-associated macrophages for immunotherapy of prostate cancer. Eur J Pharm Sci. 2023;185:106427.

100. Cheng J, Wang S, Min Q, Song J, Tian Y. Reconstructed adoptive macrophages with DNA-tetrahedron-CpG/siRNA for synergistic solid tumor immunotherapy. Colloids Surf Physicochem Eng Asp. 2022;637:128184.

101. Li M, Li M, Yang Y, Liu Y, Xie H, Yu Q, et al. Remodeling tumor immune microenvironment via targeted Blockade of PI3K-γ and CSF-1/CSF-1R pathways in tumor associated macrophages for pancreatic cancer therapy. J Control Release. 2020;321:23-35.

102. Zhao JL, Huang F, He F, Gao CC, Liang SQ, Ma PF, et al. Forced activation of Notch in macrophages represses tumor growth by upregulating MIR-125a and disabling tumor-associated macrophages. Cancer Res. 2016;76:1403-15.

103. Parayath NN, Parikh A, Amiji MM. Repolarization of Tumor-Associated macrophages in a genetically engineered nonsmall cell lung cancer model by intraperitoneal administration of hyaluronic Acid-Based nanoparticles encapsulating MicroRNA-125b. Nano Lett. 2018;18:3571-9.

104. Zang X, Zhang X, Zhao X, Hu H, Qiao M, Deng Y, et al. Targeted delivery of MiRNA 155 to tumor associated macrophages for tumor immunotherapy. Mol Pharm. 2019;16:1714-22.

105. Walters AA, Santacana-Font G, Li J, Routabi N, Qin Y, Claes N, et al. Nanoparticle-Mediated in situ molecular reprogramming of immune checkpoint interactions for cancer immunotherapy. ACS Nano. 2021;15:17549-64.

106. Haabeth OAW, Blake TR, McKinlay CJ, Tveita AA, Sallets A, Waymouth RM, et al. Local delivery of OX40L, CD80, and CD86 mRNA kindles global anticancer immunity. Cancer Res. 2019;79:1624-34.

107. Rannikko JH, Hollmén M. Clinical landscape of macrophage-reprogramming cancer immunotherapies. Br J Cancer 2024 1314. 2024 [cited 2025 Jul 19];131:627-40. Available from: https://www.nature.com/articles/s41416-024-02715-6

108. Engel AL, Holt GE, Lu H. The pharmacokinetics of Toll-like receptor agonists and the impact on the immune system. Expert Rev Clin Pharmacol. 2011 [cited 2025 Jul 20];4:275. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC3105468/

109. Zhang X, Chen Y, Liu X, Li G, Zhang S, Zhang Q, et al. STING in cancer immunoediting: modeling tumor-immune dynamics throughout cancer development. Cancer Lett. 2025;612:217410.

110. Andón FT, Leon S, Ummarino A, Redin E, Allavena P, Serrano D et al. Innate and Adaptive Responses of Intratumoral Immunotherapy with Endosomal Toll-Like Receptor Agonists. Biomed

2022, Vol 10, Page 1590. 2022 [cited 2025 Jul 20];10:1590. Available from: https://www.mdpi.com/2227-9059/10/7/1590/htm

111. Malyshev I, Malyshev Y. Current Concept and Update of the Macrophage Plasticity Concept: Intracellular Mechanisms of Reprogramming and M3 Macrophage Switch Phenotype. Biomed Res Int. 2015 [cited 2025 Jul 20];2015:341308. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4561113/

112. van Brummelen EMJ, Ros W, Wolbink G, Beijnen JH, Schellens JHM. Antidrug Antibody Formation in Oncology: Clinical Relevance and Challenges. Oncologist. 2016 [cited 2025 Jul 20];21:1260-8. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC5061540/

113. Liu M, Wang Y, Zhang Y, Hu D, Tang L, Zhou B et al. Landscape of small nucleic acid therapeutics: moving from the bench to the clinic as next-generation medicines. Signal Transduct Target Ther 2025 101. 2025 [cited 2025 Jul 29];10:1-57. Available from: http://www.nature.com/articles/s41392-024-02112-8

114. Dong Y, Siegwart DJ, Anderson DG. Strategies, design, and chemistry in SiRNA delivery systems. Adv Drug Deliv Rev. 2019;144:133-47.

115. Tatiparti K, Sau S, Kashaw SK, Iyer AK. SiRNA delivery strategies: A comprehensive review of recent developments. Nanomaterials. 2017;7:1-17.

116. Fattal E, Fay F. Nanomedicine-based delivery strategies for nucleic acid gene inhibitors in inflammatory diseases. Adv Drug Deliv Rev. 2021;175:113809. Available from: https://www.sciencedirect.com/science/article/pii/S0169409X21001836

117. Rupaimoole R, Slack FJ. MicroRNA therapeutics: Towards a new era for the management of cancer and other diseases. Nat Rev Drug Discov. 2017;16:203-21. Available from: https://doi.org/10.1038/nrd.2016.246

118. Stenvang J, Petri A, Lindow M, Obad S, Kauppinen S. Inhibition of microRNA function by antimiR oligonucleotides. Silence. 2012;3:1. Available from: http://www.silencejournal.com/content/3/1/1

119. Dominska M, Dykxhoorn DM. Breaking down the barriers: SiRNA delivery and endosome escape. J Cell Sci. 2010;123:1183-9.

120. Whitehead KA, Langer R, Anderson DG. Knocking down barriers: advances in SiRNA delivery. Nat Rev Drug Discov. 2009;8:129-38.

121. Sajid MI, Moazzam M, Tiwari RK, Kato S, Cho KY. Overcoming barriers for SiRNA therapeutics: from bench to bedside. Pharmaceuticals. 2020;13:1-25.

122. Singh A, Trivedi P, Jain NK. Advances in siRNA delivery in cancer therapy. Artif Cells, Nanomedicine Biotechnol. 2018 [cited 2019 Oct 25];46:274-83. Available from: https://www.tandfonline.com/doi/full/https://doi.org/10.1080/21691401.2017.1307210

123. Wang J, Lu Z, Wientjes MG, Au JLS. Delivery of SiRNA therapeutics: barriers and carriers. AAPS J. 2010;12:492-503.

124. Moazzam M, Zhang M, Hussain A, Yu X, Huang J, Huang Y. The landscape of nanoparticle-based SiRNA delivery and therapeutic development. Mol Ther. 2024;32:284-312.

125. Sun Y, Cronin MF, Mendonça MCP, Guo J, O'Driscoll CM. M2pep-Modified Cyclodextrin-siRNA nanoparticles modulate the immunosuppressive tumor microenvironment for prostate cancer therapy. Mol Pharm. 2023;20:5921-36.

126. Wang F, You H, Liu H, Qi Z, Shi X, Jin Z, et al. Silencing PTPN2 with nanoparticle-delivered small interfering RNA remodels tumor microenvironment to sensitize immunotherapy in hepatocellular carcinoma. Acta Pharm Sin B. 2025;15:2915-29.

127. Sica A, Alberto M. Macrophage plasticity and polarization: in vivo veritas. J Clin Invest. 2012;122:787-95.

128. Liu T, Zhang L, Joo D, Sun SC. NF-κB signaling in inflammation. Signal Transduct Target Ther. 2017;2.
129. Cornice J, Verzella D, Arboretto P, Vecchiotti D, Capece D, Zazzeroni F et al. NF-κB: governing macrophages in cancer. *Genes* (Basel). 2024;15.

130. He R, He Y, Du R, Liu C, Chen Z, Zeng A, et al. Revisiting of TAMs in tumor immune microenvironment: insight from NF-κB signaling pathway. *Biomed Pharmacother*. 2023;165:115090.

131. Glass EB, Hoover AA, Bullock KK, Madden MZ, Reinfeld BI, Harris W, et al. Stimulating TAM-mediated anti-tumor immunity with mannose-decorated nanoparticles in ovarian cancer. *BMC Cancer*. 2022;22:1–19.

132. Xiang C, Li H, Tang W. Targeting CSF-1R represents an effective strategy in modulating inflammatory diseases. *Pharmacol Res*. 2023;187:106566.

133. Wang Q, Wang J, Xu K, Luo Z. Targeting the CSF1/CSF1R signaling pathway: an innovative strategy for ultrasound combined with macrophage exhaustion in pancreatic cancer therapy. *Front Immunol*. 2024;15:1–8.

134. Pan J, Ma Y, Li Y, Feng C, Liu Y. A designed nanomedicine reprograms the phenotype and enhances the phagocytic ability of macrophages to ameliorate lung cancer in a mouse model. *Biochem Eng J*. 2021;176:108172.

135. Kulkarni JA, Witzigmann D, Thomson SB, Chen S, Leavitt BR, Cullis PR, et al. The current landscape of nucleic acid therapeutics. *Nat Nanotechnol*. 2021;16:630–43.

136. Veiga N, Diesendruck Y, Peer D. Targeted lipid nanoparticles for RNA therapeutics and Immunomodulation in leukocytes. *Adv Drug Deliv Rev*. 2020;159:364–76.

137. Tieu T, Wei Y, Cifuentes-Rius A, Voelcker NH. Overcoming barriers: clinical translation of SiRNA nanomedicines. *Adv Ther*. 2021;4:1–24.

138. Han X, Zhang H, Butowska K, Swingle KL, Alameh MG, Weissman D, et al. An ionizable lipid toolbox for RNA delivery. *Nat Commun*. 2021;12:8–13.

139. Chatterjee S, Kon E, Sharma P, Peer D. Endosomal escape: A bottleneck for LNP-mediated therapeutics. *Proc Natl Acad Sci*. 2024;121:e2307800120.

140. Hu M, Li X, You Z, Cai R, Chen C. Physiological barriers and strategies of Lipid-Based nanoparticles for nucleic acid drug delivery. *Adv Mater*. 2024;36:1–28.

141. Yingchoncharoen P, Kalinowski DS, Richardson DR. Lipid-based drug delivery systems in cancer therapy: what is available and what is yet to come. *Pharmacol Rev*. 2016;68:701–87.

142. Kulkarni JA, Van Der Cullis PR. Lipid Nanoparticles Enabling Gene Therapies: From Concepts to Clinical Utility. *Nucleic Acid Ther*. 2018 [cited 2021 Mar 22];28:146–57. Available from: https://pubmed.ncbi.nlm.nih.gov/29683383/

143. Jayaraman M, Ansell SM, Mui BL, Tam YK, Chen J, Du X, et al. Maximizing the potency of SiRNA lipid nanoparticles for hepatic gene Silencing in vivo. *Angew Chemie - Int Ed.* 2012;51:8529–33.

144. Ding F, Zhang H, Li Q, Yang C. Identification of a potent ionizable lipid for efficient macrophage transfection and systemic anti-interleukin-1β SiRNA delivery against acute liver failure. *J Mater Chem B*. 2021;9:5136–49.

145. Xu X, Xia T. Recent advances in Site-Specific lipid nanoparticles for mRNA delivery. *ACS Nanosci Au*. 2023;3:192–203.

146. Tang C, Jing W, Han K, Yang Z, Zhang S, Liu M, et al. mRNA-Laden Lipid-Nanoparticle-Enabled in situ CAR-Macrophage engineering for the eradication of Multidrug-Resistant bacteria in a sepsis mouse model. *ACS Nano*. 2024;18:2261–78.

147. Kauffman KJ, Dorkin JR, Yang JH, Heartlein MW, Derosa F, Mir FF, et al. Optimization of lipid nanoparticle formulations for mRNA delivery in vivo with fractional factorial and definitive screening designs. *Nano Lett*. 2015;15:7300–6.

148. Courts G, Heidt T, Sebas M, Iwamoto Y, Jeon D, Truelove J, et al. In vivo Silencing of the transcription factor IRF5 reprograms

the macrophage phenotype and improves infarct healing. *J Am Coll Cardiol*. 2014;63:1556–66.

149. Koga JI, Nakano T, Dahlman JE, Figueiredo JL, Zhang H, Decano J, et al. Macrophage Notch ligand Delta-Like 4 promotes vein graft lesion development: implications for the treatment of vein graft failure. *Arterioscler Thromb Vasc Biol*. 2015;35:2343–53.

150. Gilleron J, Querbes W, Zeigerer A, Borodovsky A, Marsico G, Schubert U et al. Image-based analysis of lipid nanoparticle-mediated siRNA delivery, intracellular trafficking and endosomal escape. *Nat Biotechnol*. 2013 [cited 2021 Mar 24];31:638–46. Available from: https://www.nature.com/articles/nbt.2612

151. Wittrup A, Ai A, Liu X, Hamar P, Trifonova R, Charisse K, et al. Visualizing lipid-formulated SiRNA release from endosomes and target gene knockdown. *Nat Biotechnol*. 2015;33:870–6.

152. Chaudhary N, Kasiewicz LN, Newby AN, Arral ML, Yerneni SS, Melamed JR, et al. Amine headgroups in ionizable lipids drive immune responses to lipid nanoparticles by binding to the receptors TLR4 and CD1d. *Nat Biomed Eng*. 2024;8:1483–98.

153. Zelkoski AE, Lu Z, Sukumar G, Dalgard C, Said H, Alameh MG et al. Ionizable lipid nanoparticles of mRNA vaccines elicit NF-κB and IRF responses through toll-like receptor 4. *npj Vaccines* 2025 101. 2025 [cited 2025 Jul 29];10:1–13. Available from: https://www.nature.com/articles/s41541-025-01124-x

154. Nguyen HM, Alexander KE, Collinge M, Hickey JC, Lanz TA, Li J et al. mRNA-LNPs induce immune activation and cytokine release in human whole blood assays across diverse health conditions. *Mol Ther*. 2025 [cited 2025 Jul 29];33:2872–85. Available from: https://www.cell.com/action/showFullText?pii=S1525001624008189

155. Connors J, Joyner D, Mege NJ, Cusimano GM, Bell MR, Marcy J et al. Lipid nanoparticles (LNP) induce activation and maturation of antigen presenting cells in young and aged individuals. *Commun Biol* 2023 61. 2023 [cited 2025 Jul 29];6:1–13. Available from: https://www.nature.com/articles/s42003-023-04555-1

156. Cheng X, Lee RJ. The role of helper lipids in lipid nanoparticles (LNPs) designed for oligonucleotide delivery. *Adv Drug Deliv Rev*. 2016;99:129–37.

157. Yang ST, Kreutzberger AJB, Lee J, Kiessling V, Tamm LK. The role of cholesterol in membrane fusion. *Chem Phys Lipids*. 2016;199:136–43.

158. Patel S, Ashwanikumar N, Robinson E, Xia Y, Mihai C, Griffith JP, et al. Naturally-occurring cholesterol analogues in lipid nanoparticles induce polymorphic shape and enhance intracellular delivery of mRNA. *Nat Commun*. 2020;11:1–13.

159. Lokugamage MP, Vanover D, Beyersdorf J, Hatit MZC, Rotolo L, Echeverri ES, et al. Optimization of lipid nanoparticles for the delivery of nebulized therapeutic mRNA to the lungs. *Nat Biomed Eng*. 2021;5:1059–68.

160. Kulkarni JA, Witzigmann D, Leung J, Tam YYC, Cullis PR. On the role of helper lipids in lipid nanoparticle formulations of SiRNA. *Nanoscale*. 2019;11:21733–9.

161. Belliveau NM, Huft J, Lin PJ, Chen S, Leung AK, Leaver TJ et al. Microfluidic synthesis of highly potent limit-size lipid nanoparticles for in vivo delivery of siRNA. *Mol Ther - Nucleic Acids*. 2012 [cited 2021 Mar 22];1:e37. Available from: https://pubmed.ncbi.nlm.nih.gov/23344179/

162. Mui BL, Tam YK, Jayaraman M, Ansell SM, Du X, Tam YYC et al. Influence of polyethylene glycol lipid desorption rates on pharmacokinetics and pharmacodynamics of SiRNA lipid nanoparticles. *Mol Ther - Nucleic Acids*. 2013;2.

163. Tamaki HATTORIY, Sakasai K, Ozaki S. Effects of PEG anchors in pegylated SiRNA lipoplexes on in vitro gene-silencing effects and SiRNA biodistribution in mice. *Mol Med Rep*. 2020;22:4183–96.
164. Ge X, Chen L, Zhao B, Yuan W. Rationale and application of pegylated Lipid-Based system for advanced target delivery of SiRNA. Front Pharmacol. 2021;11:1-15.

165. Zhu X, Tao W, Liu D, Wu J, Guo Z, Ji X, et al. Surface de-PEGylation controls nanoparticle-mediated SiRNA delivery in vitro and in vivo. Theranostics. 2017;7:1990-2002.

166. Berger M, Degey M, Leblond Chain J, Maquoi E, Evrard B, Lechanteur A et al. Effect of PEG anchor and serum on lipid nanoparticles: development of a nanoparticles tracking method. Pharmaceutics. 2023;15.

167. Chen D, Ganesh S, Wang W, Amiji M. The role of surface chemistry in serum protein corona-mediated cellular delivery and gene Silencing with lipid nanoparticles. Nanoscale. 2019;11:8760-75.

168. Akinc A, Maier MA, Manoharan M, Fitzgerald K, Jayaraman M, Barros S et al. The Onpattro story and the clinical translation of nanomedicines containing nucleic acid-based drugs. Nat Nanotechnol. 2019. pp. 1084-7.

169. Yun WS, Kim J, Lim DK, Kim DH, Jeon SI, Kim K. Recent studies and progress in the intratumoral administration of Nano-Sized drug delivery systems. Nanomaterials. 2023;13.

170. Sheth RA, Wehrenberg-Klee E, Patel SP, Brock KK, Fotiadis N, de Baère T. Intratumoral injection of immunotherapeutics: state of the Art and future directions. Radiology. 2024;312.

171. Spada A, Emami J, Tuszynski JA, Lavasanif A. The uniqueness of albumin as a carrier in nanodrug delivery. Mol Pharm. 2021;18:1862-94.

172. Dilliard SA, Siegwart DJ. Passive, active and endogenous organ-targeted lipid and polymer nanoparticles for delivery of genetic drugs. Nat Rev Mater. 2023;8:282-300.

173. Attia MF, Anton N, Wallyn J, Omran Z, Vandamme TF. An overview of active and passive targeting strategies to improve the nanocarriers efficiency to tumour sites. J Pharm Pharmacol. 2019;71:1185-98.

174. Schöttler S, Becker G, Winzen S, Steinbach T, Mohr K, Landfester K, et al. Protein adsorption is required for stealth effect of poly(ethylene glycol)- and poly(phosphoester)-coated nanocarriers. Nat Nanotechnol. 2016;11:372-7.

175. Torchilin V. Tumor delivery of macromolecular drugs based on the EPR effect. Adv Drug Deliv Rev. 2011;63:131-5.

176. Gustafson HH, Holt-Casper D, Grainger DW, Ghandehari H. Nanoparticle uptake: The phagocyte problem. Nano Today. 2015;10:487-510. Available from: https://doi.org/10.1016/j.jantod.2015.06.006

177. Zhu S, Niu M, O'Mary H, Cui Z. Targeting of tumor-associated macrophages made possible by PEG-sheddable, mannose-modified nanoparticles. Mol Pharm. 2013;10:3525-30.

178. Zhao P, Yin W, Wu A, Tang Y, Wang J, Pan Z, et al. Dual-Targeting to cancer cells and M2 macrophages via biomimetic delivery of mannosylated albumin nanoparticles for Drug-Resistant cancer therapy. Adv Funct Mater. 2017;27:1-15.

179. Zhang C, Gao L, Cai Y, Liu H, Gao D, Lai J, et al. Inhibition of tumor growth and metastasis by photoimmunotherapy targeting tumor-associated macrophage in a sorafenib-resistant tumor model. Biomaterials. 2016;84:1-12.

180. Conde J, Bao C, Tan Y, Cui D, Edelman ER, Azevedo HS, et al. Dual targeted immunotherapy via in vivo delivery of biohybrid RNAi-peptide nanoparticles to tumour-associated macrophages and cancer cells. Adv Funct Mater. 2015;25:4183-94.

181. Kuninty PR, Binnemars-Postma K, Jarray A, Pednekar KP, Heinrich MA, Pijffers HJ et al. Cancer immune therapy using engineered 'tail-flipping' nanoliposomes targeting alternatively activated macrophages. Nat Commun 2022 131. 2022 [cited 2025 Jul 31];13:1-17. Available from: https://www.nature.com/articles/s41467-022-32091-9

182. Kimura S, Khalil IA, Elewa YHA, Harashima H. Novel lipid combination for delivery of plasmid DNA to immune cells in the spleen. J Control Release. 2021;330:753-64.

183. Binnemars-Postma KA, Ten Hoopen HW, Storm G, Prakash J. Differential uptake of nanoparticles by human M1 and M2 polarized macrophages: protein Corona as a critical determinant. Nanomedicine. 2016;11:2889-902.

184. Lee H, Vanhecke D, Balog S, Taladriz-Blanco P, Petri-Fink A, Rothen-Rutishauser B. The impact of macrophage phenotype and heterogeneity on the total internalized gold nanoparticle counts. Nanoscale Adv. 2024;6.

185. MacParland SA, Tsoi KM, Ouyang B, Ma XZ, Manuel J, Fawaz A, et al. Phenotype determines nanoparticle uptake by human macrophages from liver and blood. ACS Nano. 2017;11:2428-43.

186. Gallud A, Bondarenko O, Feliu N, Kupferschmidt N, Atluri R, Garcia-Bennett A, et al. Macrophage activation status determines the internalization of mesoporous silica particles of different sizes: exploring the role of different pattern recognition receptors. Biomaterials. 2017;121:28-40.

187. Chen D, Ganesh S, Wang W, Lupieri A, Amiji M. Role of vitronectin-rich protein Corona on tumor-specific SiRNA delivery and transfection with lipid nanoparticles. Nanomed (Lond). 2021;16:535-51.

188. Udofa E, Zhao Z. In situ cellular hitchhiking of nanoparticles for drug delivery. Adv Drug Deliv Rev. 2023 [cited 2025 Jul 27];204:115143. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC10841869/

189. Paoletti A, Ly B, Cailleau C, Gao F, de Ponfilly-Sotier MP, Pascaud J et al. Liposomal AntagomiR-155-5p Restores Anti-Inflammatory Macrophages and Improves Arthritis in Preclinical Models of Rheumatoid Arthritis. Arthritis Rheumatol (Hoboken, NJ). 2024 [cited 2025 Mar 4];76:18-31. Available from: https://pubmed.ncbi.nlm.nih.gov/37527031/

190. Hermosillo-Abundis C, Flood-Garibay JA, Ayala-Nunez V, Méndez-Rojas MA. Immune Cells as Trojan Horses for Cancer Nanotherapy. ACS Mater Lett. 2025 [cited 2025 Jul 29];7:156-71. Available from: https://pubs.acs.org/doi/full/https://doi.org/10.1021/acsmaterialslett.4c01523

191. Sofias AM, Toner YC, Meerwaldt AE, Van Leent MMT, Soulantidis G, Elschot M et al. Tumor Targeting by αVβ3-Integrin-Specific Lipid Nanoparticles Occurs via Phagocyte Hitchhiking. ACS Nano. 2020 [cited 2025 Jul 29];14:7832-46. Available from: https://pubs.acs.org/doi/full/https://doi.org/10.1021/acsnano.9b08693

192. Kuang J, Rao ZY, Zheng DW, Kuang D, Huang QX, Pan T et al. Nanoparticles Hitchhike on Monocytes for Glioblastoma Treatment after Low-Dose Radiotherapy. ACS Nano. 2023 [cited 2025 Jul 29];17:13333-47. Available from: https://pubs.acs.org/doi/abs/doi.org/10.1021/acsnano.3c01428

193. Qin J, Xue L, Gong N, Zhang H, Shepherd SJ, Haley RM, et al. RGD peptide-based lipids for targeted mRNA delivery and gene editing applications. RSC Adv. 2022;12:25397-404.

194. Asai T, Tsuzuku T, Takahashi S, Okamoto A, Dewa T, Nango M, et al. Cell-penetrating peptide-conjugated lipid nanoparticles for SiRNA delivery. Biochem Biophys Res Commun. 2014;444:599-604.

195. Brown DW, Wee P, Bhandari P, Bukhari A, Grin L, Vega H, et al. Safe and effective in vivo delivery of DNA and RNA using proteolipid vehicles. Cell. 2024;187:5357-e537524.

196. Vermeulen LMP, De Smedt SC, Remaut K, Braeckmans K. The proton sponge hypothesis: Fable or fact? Eur. J. Pharm. Biopharm. Elsevier B.V.; 2018. pp. 184-90.

197. Alshaer W, Hillaireau H, Vergnaud J, Mura S, Deloménie C, Sauvage F et al. Aptamer-guided siRNA-loaded nanomedicines for systemic gene silencing in CD-44 expressing murine triple-negative breast cancer model. J Control Release. 2018 [cited 2018
May 16];271:98-106. Available from: https://www-sciencedirect.com-insb.bib.cnrs.fr/science/article/pii/S0168365917310921?via%3Dihub

198. Zhi D, Zhang S, Cui S, Zhao Y, Wang Y, Zhao D. The headgroup evolution of cationic lipids for gene delivery. *Bioconjug Chem.* 2013;24:487-519.

199. Ponti F, Campolungo M, Melchiori C, Bono N, Candiani G. Cationic lipids for gene delivery: many players, one goal. *Chem Phys Lipids.* 2021;235:105032.

200. Resina S, Prevot P, Tjierry AR. Physico-chemical characteristics of lipoplexes influence cell uptake mechanisms and transfection efficacy. *PLoS ONE.* 2009;4.

201. Kulkarni JA, Darjuan MM, Mercer JE, Van Der Chen S, Thewalt JL, et al. On the formation and morphology of lipid nanoparticles containing ionizable cationic lipids and SiRNA. *ACS Nano.* 2018;12:4787-95.

202. Patel SK, Billingsley MM, Frazee C, Han X, Swingle KL, Qin J, et al. Hydroxycholesterol substitution in ionizable lipid nanoparticles for mRNA delivery to T cells. *J Control Release.* 2022;347:521-32.

203. Mo Y, Cheng MHY, D'Elia A, Doran K, Ding L, Chen J, et al. Light-Activated SiRNA endosomal release (LASER) by porphyrin lipid nanoparticles. *ACS Nano.* 2023;17:4688-703.

204. Alamoudi K, Martins P, Croissant JG, Patil S, Omar H, Khashab NM. Thermoresponsive pegylated bubble liposome nanovectors for efficient SiRNA delivery via endosomal escape. *Nanomedicine.* 2017;12:1421-33.

205. Wei PS, Thota N, John G, Chang E, Lee S, Wang Y, et al. Enhancing RNA-lipid nanoparticle delivery: Organ- and cell-specificity and barcoding strategies. *J Control Release.* 2024;375:366-88.

206. Lobovkina T, Jacobson GB, Gonzalez-Gonzalez E, Hickerson RP, Leake D, Kaspar RL et al. In vivo sustained release of siRNA from solid lipid nanoparticles. *ACS Nano.* 2011 [cited 2025 Jul 25];5:9977-83. Available from: https://pubs.acs.org/doi/abs/doi:10.1021/nn203745n

207. Tadin-Strapps M, Peterson LB, Cumiskey AM, Rosa RL, Mendoza VH, Castro-Perez J et al. siRNA-induced liver ApoB knockdown lowers serum LDL-cholesterol in a mouse model with human-like serum lipids. *J Lipid Res.* 2011 [cited 2025 Jul 25];52:1084. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC3090230/

208. Habtemariam BA, Karsten V, Attarwala H, Goel V, Melch M, Clausen VA et al. Single-Dose Pharmacokinetics and Pharmacodynamics of Transthryretin Targeting N-acetylgalactosamine-Small Interfering Ribonucleic Acid Conjugate, Vutrisiran, in Healthy Subjects. *Clin Pharmacol Ther.* 2021 [cited 2021 Mar 22];109:372-82. Available from: https://onlinelibrary.wiley.com/doi/https://doi.org/10.1002/cpt.1974

209. Northfelt DW, Hamburg SI, Borad MJ, Seetharam M, Curtis KK, Lee P et al. A phase I dose-escalation study of TKM-080301, a RNAi therapeutic directed against polo-like kinase 1 (PLK1), in patients with advanced solid tumors: Expansion cohort evaluation of biopsy samples for evidence of pharmacodynamic effects of PLK1 inhibition. *J Clin Oncol.* 2013 [cited 2025 Jul 27];31:TPS2621-TPS2621. Available from: https://doi.org/10.1200/jco.2013.31.15_suppl.tps2621

210. Schultheis B, Strumberg D, Santel A, Vank C, Gebhardt F, Keil O et al. First-in-human phase I study of the liposomal RNA interference therapeutic Atu027 in patients with advanced solid tumors. *J Clin Oncol.* 2014 [cited 2025 Jul 27];32:4141-8. Available from: https://doi.org/10.1200/JCO.2013.55.0376

211. Tabernero J, Shapiro GI, LoRusso PM, Cervantes A, Schwartz GK, Weiss GJ et al. First-in-humans trial of an RNA interference therapeutic targeting VEGF and KSP in cancer patients with liver involvement. *Cancer Discov.* 2013 [cited 2025 Jul 27];3:406-17.

Available from: /cancerdiscovery/article/3/4/406/3986/First-in-Humans-Trial-of-an-RNA-Interference.

212. Bartlett DW, Davis ME. Insights into the kinetics of siRNA-mediated gene Silencing from live-cell and live-animal bioluminescent imaging. *Nucleic Acids Res.* 2006;34:322-33.

213. Brunner T, Cohen S, Monsonego A. Silencing of Proinflammatory genes targeted to peritoneal-residing macrophages using SiRNA encapsulated in biodegradable microspheres. *Biomaterials.* 2010;31:2627-36.

214. Zhou X, Li D, Xia S, Ma X, Li R, Mu Y, et al. RNA-based modulation of macrophage-mediated efferocytosis potentiates antitumor immunity in colorectal cancer. *J Control Release.* 2024;366:128-41.

215. Yong SB, Ramishetti S, Goldsmith M, Diesendruck Y, Hazan-Halevy I, Chatterjee S et al. Dual-Targeted lipid nanotherapeutic boost for Chemo-Immunotherapy of cancer. *Adv Mater.* 2022;34.

216. Xia S, Chen W, Xu Z, Gao Y, Chen J, Ding N et al. Targeting Dicer reprograms tumor-associated macrophages to promote antitumoral immunity in colorectal cancer liver metastasis. *J Nanobiotechnology.* 2025 [cited 2025 Jul 29];23:1-21. Available from: https://jnanobiotechnology.biomedcentral.com/articles/https://doi.org/10.1186/s12951-025-03518-4

217. Fattore L, Cafaro G, Di Martile M, Campani V, Sacconi A, Liguoro D et al. Oncosuppressive miRNAs loaded in lipid nanoparticles potentiate targeted therapies in BRAF-mutant melanoma by inhibiting core escape pathways of resistance. *OncoGene* 2022 424. 2022 [cited 2025 Jul 29];42:293-307. Available from: https://www.nature.com/articles/s41388-022-02547-9

218. Wu Y, Park J, Xu E, Kim D, Lee J, Oh YK. MicroRNA-induced reprogramming of tumor-associated macrophages for modulation of tumor immune microenvironment. *J Control Release.* 2025;381:113593.

219. Spiller KL, Koh TJ. Macrophage-based therapeutic strategies in regenerative medicine. *Adv Drug Deliv Rev.* 2017;122:74-83.

220. Bao X, Shi R, Zhao T, Wang Y, Anastasov N, Rosemann M, et al. Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels tumour heterogeneity plus M2-like tumour-associated macrophage infiltration and aggressiveness in TNBC. *Cancer Immunol Immunother.* 2021;70:189-202.

221. Yang S, Wang M, Hua Y, Li J, Zheng H, Cui M, et al. Advanced insights on tumor-associated macrophages revealed by single-cell RNA sequencing: the intratumor heterogeneity, functional phenotypes, and cellular interactions. *Cancer Lett.* 2024;584:21660.

222. Yang Q, Zhang H, Wei T, Lin A, Sun Y, Luo P, et al. Single-Cell RNA sequencing reveals the heterogeneity of Tumor-Associated macrophage in Non-Small cell lung cancer and differences between sexes. *Front Immunol.* 2021;12:1-18.

223. Müller S, Kohanbash G, Liu SJ, Alvarado B, Carrera D, Bhaduri A, et al. Single-cell profiling of human gliomas reveals macrophage ontogeny as a basis for regional differences in macrophage activation in the tumor microenvironment. *Genome Biol.* 2017;18:1-14.

224. Wang X, Xu Y, Sun Q, Zhou X, Ma W, Wu JB, et al. New insights from the single-cell level: tumor associated macrophages heterogeneity and personalized therapy. *Biomed Pharmacother.* 2022;153:113343.

225. Larroquette M, Guegan JP, Besse B, Cousin S, Brunet M, Le Moulec S et al. Spatial transcriptomics of macrophage infiltration in non-small cell lung cancer reveals determinants of sensitivity and resistance to anti-PD1/PD-L1 antibodies. *J Immunother Cancer.* 2022;10.

226. Feng Y, Wang S, Xie J, Ding B, Wang M, Zhang P, et al. Spatial transcriptomics reveals heterogeneity of macrophages in the tumor microenvironment of granulomatous slack skin. *J Pathol.* 2023;261:105-19.
227. Zheng X, Weigert A, Reu S, Guenther S, Mansouri S, Bassaly B, et al. Spatial density and distribution of tumor-associated macrophages predict survival in non-small cell lung carcinoma. Cancer Res. 2020;80:4414–25.

228. Xia Y, Rao L, Yao H, Wang Z, Ning P, Chen X. Engineering macrophages for cancer immunotherapy and drug delivery. Adv Mater. 2020;32:1–20.

229. Dilliard SA, Cheng Q, Siegwart DJ. On the mechanism of tissue-specific mRNA delivery by selective organ targeting nanoparticles. Proc Natl Acad Sci U S A. 2021;118.

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