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WIREs Nanomed Nanobiotechnol
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Embracing nanomaterials' interactions with the innate immune system

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Abstract Immunotherapy has firmly established itself as a compelling avenue for treating disease. Although many clinically approved immunotherapeutics engage the adaptive immune system, therapeutically targeting the innate immune system remains much less explored. Nanomedicine offers a compelling opportunity for innate immune system engagement, as many nanomaterials inherently interact with myeloid cells (e.g., monocytes, macrophages, neutrophils, and dendritic cells) or can be functionalized to target their cell‐surface receptors. Here, we provide a perspective on exploiting nanomaterials for innate immune system regulation. We focus on specific nanomaterial design parameters, including size, form, rigidity, charge, and surface decoration. Furthermore, we examine the potential of high‐throughput screening and machine learning, while also providing recommendations for advancing the field. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease
(a) Schematic overview of cell types associated with the innate (top) and adaptive (bottom) branches of the immune system. The depicted residence organs serve as representative examples. (b) Nanocarriers can be loaded with drugs to enhance these compounds' intracellular delivery or surface‐functionalized with specific ligands to target cell (surface) receptors
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Factors influencing nanomaterial‐mediated activation of cell surface receptors. (a) The avidity between multivalent receptor–ligand scaffolds is often several orders of magnitude greater than the sum of the individual receptor–ligand affinities. (b) The linkers connecting a nanomaterial and its ligands should ideally be just long enough to activate and cluster multiple receptors. Further increasing linker lengths reduces the ligands' local concentration and thereby the nanoparticle's receptor avidity. (c) Elongated nanomaterials generally bind cell surface receptors more efficiently than spherical ones with identical ligand density. (d) Functionalizing nanomaterials with multiple types of ligands allows clustering different kinds of receptors. (e) Schematic depiction of a nanoparticle library comprised of PEG (blue), poly‐lactic acid (PLA, yellow), and cRGD (green). (f) In vitro uptake of the various polymeric nanoparticles in U87MG glioblastoma cells after 45 min incubation at 37°C, as determined by flow cytometry. (g) The hydrodynamic diameter of nanoparticles containing 2 or 5 kDa PEG chains as determined by dynamic light scattering. (h) Schematic depiction of the effect of PEG linker length on the nanomaterials' colloidal stability and receptor activation. Panels d–h were adapted with permission from Abstiens, Gregoritza, and Goepferich (2019)
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The effect of nanomaterial surface charge on in vitro and in vivo behavior. (a) Introducing surface modifications can alter nanomaterial surface charge. (b) Surface charge influences nanomaterial (spheres) colloidal stability and protein (blobs) adsorption. (c) Protein adsorption alters nanomaterials properties and thereby their cellular uptake. (d,e) Amici et al. incubated liposomes for 10 min at 37°C in blood‐derived from FVB/N mice before recovering the nanoparticles (in vitro sample). Alternatively, the liposomes were intravenously administered to FVB/N mice, allowed to circulate for 10 min, and subsequently recovered from the bloodstream (in vivo sample). (d) Dynamic light scattering revealed that protein adsorption increases the effective size and zeta‐potential of both in vitro incubated and in vivo circulated liposomes, as compared with their unused counterparts. However, differences in size and zeta‐potential were observed between the in vitro and in vivo used nanomaterials. (e) The number, molecular weight (Mw), and function of the types of proteins adsorbed after in vitro incubating or in vivo circulating the liposomes; as determined by tandem mass spectroscopy. Panels d and e were adapted with permission from Amici et al. (2017)
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The effect of nanomaterials' rigidity on their in vivo behavior. (a) Nanoparticles' rigidity largely depends on their bulk composition, but in some cases can be precisely controlled. (b) Flexible nanomaterials deform upon endocytosis, hindering the formation of actin filaments and impeding endocytosis (Anselmo & Mitragotri, 2017; Beningo & Wang, 2002). (c) In some instances, enhanced nanoparticle rigidity can inhibit fusion with the cell membrane and thereby reduce their uptake. Panel adapted with permission from Guo et al. (2018). (d) Flexible nanoparticles pass through membranes easier than rigid variants, reducing their clearance from the bloodstream. (e,f) Polymer brushed were synthesized in two different lengths and with either flexible or rigid cores (I = flexible 220 ± 70 nm, II = rigid 260 ± 50 nm, III = flexible 1150 ± 300 nm, and IV = rigid 1200 ± 200 nm). (e) Fluorophore‐labeled polymer brushes were incubated with RAW264.7 macrophages for 24 h and analyzed by fluorescence microscopy. Significantly more cell association was observed for both longer brushes, but the brushes' rigidity had no clear influence. (f) Radiolabeled polymer brushes were i.v. administrated to rats and their plasma concentration monitored. Results revealed that rigid variants clear notably faster than their flexible analogs. Panels e and f were adapted with permission from Müllner et al. (2015)
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The effect of nanomaterial size and form on in vivo behavior. (a) Transmission electron microscopy (TEM) micrographs of nanomaterials with various forms, scale bars represent 100 nm. (b) A small contact angle (θ) between nanomaterials and cells' surface impedes endocytosis. (c) The increased blood half‐life typically observed for elongated nanoparticles is presumed to originate from their tumbling in the bloodstream, promoting vessel wall adherence. (d) Schematic depiction of highly defined RNA nanosquares of different sizes and ex vivo fluorescence imaging of organs obtained from tumor‐bearing mice (subcutaneous xenografts established using KB cells) intravenously injected with these RNA nanosquares. All nanosquares were labeled with the fluorophore Alexa Fluor 647, Li = liver, Sp = spleen, Ki = kidney, Tu = tumor. Panel a was adapted with permission from Castagnola et al. (2017), panels b and c are based on Toy et al. (2013), panel d is adapted with permission from Jasinski et al. (2018)
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Schematic representation of nanomaterials commonly employed as nanocarriers or nanotherapeutics for (innate) nanoimmunotherapy (Almeida et al., 2014; H. Chen et al., 2020; Fadel & Fahmy, 2014; Hawkins et al., 2008; Herrera Estrada & Champion, 2015; Hess et al., 2017; Kean & Thanou, 2010; Lee et al., 2019; Mehnert & Mäder, 2012; Okholm & Kjems, 2017; Raut et al., 2018; Savage et al., 2013)
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Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease
Diagnostic Tools > In Vivo Nanodiagnostics and Imaging
Nanotechnology Approaches to Biology > Nanoscale Systems in Biology

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