Next Article in Journal
Formation of βTC3 and MIN6 Pseudoislets Changes the Expression Pattern of Gpr40, Gpr55, and Gpr119 Receptors and Improves Lysophosphatidylcholines-Potentiated Glucose-Stimulated Insulin Secretion
Next Article in Special Issue
Targeted Activation of T Cells with IL-2-Coupled Nanoparticles
Previous Article in Journal
Novel Insights into Beta 2 Adrenergic Receptor Function in the rd10 Model of Retinitis Pigmentosa
Previous Article in Special Issue
Cellular Uptake of siRNA-Loaded Nanocarriers to Knockdown PD-L1: Strategies to Improve T-cell Functions
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Nucleic Acid-Based Approaches for Tumor Therapy

1
Department of Chemistry and Pharmacy, Ludwig-Maximilians-University (LMU), 81377 Munich, Germany
2
Department of Dermatology, University Medical Center, 55131 Mainz, Germany
*
Authors to whom correspondence should be addressed.
Cells 2020, 9(9), 2061; https://doi.org/10.3390/cells9092061
Submission received: 3 August 2020 / Revised: 6 September 2020 / Accepted: 7 September 2020 / Published: 9 September 2020
(This article belongs to the Special Issue Nanoparticles in Cancer Immunotherapy)

Abstract

:
Within the last decade, the introduction of checkpoint inhibitors proposed to boost the patients’ anti-tumor immune response has proven the efficacy of immunotherapeutic approaches for tumor therapy. Furthermore, especially in the context of the development of biocompatible, cell type targeting nano-carriers, nucleic acid-based drugs aimed to initiate and to enhance anti-tumor responses have come of age. This review intends to provide a comprehensive overview of the current state of the therapeutic use of nucleic acids for cancer treatment on various levels, comprising (i) mRNA and DNA-based vaccines to be expressed by antigen presenting cells evoking sustained anti-tumor T cell responses, (ii) molecular adjuvants, (iii) strategies to inhibit/reprogram tumor-induced regulatory immune cells e.g., by RNA interference (RNAi), (iv) genetically tailored T cells and natural killer cells to directly recognize tumor antigens, and (v) killing of tumor cells, and reprograming of constituents of the tumor microenvironment by gene transfer and RNAi. Aside from further improvements of individual nucleic acid-based drugs, the major perspective for successful cancer therapy will be combination treatments employing conventional regimens as well as immunotherapeutics like checkpoint inhibitors and nucleic acid-based drugs, each acting on several levels to adequately counter-act tumor immune evasion.

1. Introduction

Cancer is a serious and life-threatening disease with increasing incidence in today’s world [1,2,3,4,5]. Depending on the tumor type, stage, and location, cancer therapy can be very challenging. Conventional treatments (surgery, chemotherapy, and irradiation) are often inefficient, resulting in recurrence and even death. The main reasons for therapy failure are chemoresistance as well as metastasis [6,7]. Moreover, the patients often suffer from severe side-effects [8]. In the last 20–30 years, however, cancer treatment regimens have changed remarkably, based on the gained knowledge about molecular biology as well as tumor pathobiology and pathophysiology [9,10,11]. As a consequence of a better understanding of the tumor as a heterogeneous tissue with different types of cells, new strategies for cancer therapy have been developed, which are also applicable in combination with classical therapies [12,13,14,15,16,17,18,19,20,21,22,23,24]. However, still only a limited number of patients respond to the already approved immunotherapies, and toxicity as well as induction of resistance towards treatment are often a problem [25,26,27,28,29]. Nanotechnology-based strategies, and in particular therapeutic nucleic acids, as well as combined immunotherapies may improve the therapeutic outcome in more patients for a broad range of tumors, even in late stage. In this regard, nucleic acid-based immunotherapeutic approaches have received growing interest [24,30,31].
This review aims to present a comprehensive overview of the current state of nucleic acid-based anti-tumor therapeutics, and associated optimization strategies. As depicted in Figure 1, such strategies aim (i) to deliver tumor-related antigen plus adjuvant to antigen presenting cells (APC) like dendritic cells (DC) that induce tumor-specific immune responses, (ii) to either deplete or reprogram tumor-induced/expanded immunoregulatory cell types, especially regulatory T cells (Treg) and myeloid-derived suppressor cells (MDSC), which collectively inhibit the induction of adaptive immune reactions in the periphery, (iii) to generate tumor-specific T cells and natural killer (NK) cells by genetic introduction of synthetic antigen receptors, termed CARs (chimeric antigen receptors), and (iv) at the tumor site itself to yield direct tumor cell killing, and to inhibit the tumor-promoting function of the tumor microenvironment (TEM). It is worth mentioning that the first clinical trial ever using in vivo gene transfer was conducted by Nabel et al. in 1993 with an intratumorally applied liposomal formulation of immunotherapeutic DNA encoding for HLA (human leukocyte antigen)-B7 [32].

2. Nucleic Acid-Based Strategies to Induce Adaptive Anti-Tumor Responses

In the last decades, the potential to exploit the patients´ immune system to induce and shape anti-tumor responses has gained increasing interest [33]. The induction of tumor antigen-specific adaptive immune responses requires co-delivery of the antigen and of an immunostimulatory compound to evoke activation of a professional antigen presenting cell (APC) [34]. In this regard, DC that are considered the most potent APC population at stimulated state are in the focus of interest [35]. In conventional vaccination approaches, the antigen is applied as a peptide/protein in combination with a structurally different adjuvant that specifically triggers a danger receptor expressed by DC (and other APC) [36]. According vaccination approaches need to overcome several obstacles like (i) unwanted uncoupling of antigen and adjuvant in vivo, which may contribute to unwanted immune reactions, (ii) binding/uptake of the vaccine by non-APC, including regulatory immune cells like tumor-associated macrophages (TAM) and tumor-induced myeloid-derived suppressor cells (MDSC), which may result in the induction of tumor immune tolerance, and (iii) limited presentation of the exogenous antigen via major histocompatibility complex class I (MHCI), yielding limited activation of CD8+ T cells, and thereby insufficient induction of cytotoxic tumor lymphocytes (CTL). As outlined in the following, nucleic acids encoding for antigens (plasmid DNA (pDNA) or mRNA) and nucleic acid-based adjuvants, especially when encapsulated in APC-targeting nanoparticles (NP), provide an interesting alternative to conventional vaccination approaches.
So far, nucleic acid-based vaccines have been delivered largely by intramuscular, intradermal, as well as subcutaneous injections, resulting in predominant transfection of myocytes [37] and keratinocytes [38], respectively. Whereas mRNA-based transgenes are expressed directly in the cytoplasm of the transfected cell [39], pDNA needs to translocate to the nucleus for transcription, followed by translation in the cytoplasm [40]. In case of intramuscular [41] as well as cutaneous [42] administration, directly transfected cells may express the antigen. Antigen may be transferred to regional APC by the release of exosomes [43] or apoptotic bodies [44]. In either case, antigen of exogenous origin is presented largely on MHCII, resulting in the activation of antigen-specific CD4+ T helper cells (Th) [45]. Only subpopulations of DC are characterized by so-called cross priming activity, which means that antigen is shuttled/processed in such a manner that MHCI is loaded, resulting in CD8+ T cell activation [46]. In case of direct APC transfection [47], the antigen is expressed and processed like an endogenous gene, resulting in parallel loading onto MHCI and MHCII molecules [48]. APC that are sufficiently stimulated by pathogen-derived molecular patterns (PAMP) or endogenous danger signals, mimicked by the adjuvant, upregulate expression of MHC molecules, of costimulators, and of soluble mediators (i.e., cytokines), and migrate into the secondary lymphoid organs (draining lymph nodes, spleen) to prime antigen-specific T cells [49]. Activated CD4+ T cells are required for full activation of CD8+ T cells to yield CTL [50], and to confer so-called B cell help [51]. Depending largely on the composition of cytokines released by activated APC, CD4+ T cells polarize into various types of Th [52]. In case of tumor responses, the induction of Th1 cells, depending largely on IL-12, is paramount for CTL activation [53].

2.1. Clinical Trials Using Nucleic Acid-Based Vaccines for Tumor Therapy

2.1.1. pDNA Vaccines

In an early clinical phase I trial, stage IV melanoma patients were intranodally infused with pDNA encoding for melanoma-associated tyrosinase every two weeks for a total of four times [54]. This trial confirmed tolerability of pDNA administration, and some activation of tyrosinase-specific T cells, but no clinical responses were observed. In subsequent clinical trials DC were differentiated in vitro from peripheral blood monocytes of patients using GM-CSF (granulocyte macrophage colony-stimulating factor) plus interleukin (IL)-4, pulsed with tumor lysate/proteins, matured, and reinfused [55]. In order to evaluate the suitability of nucleic acid-based vaccination, in a clinical phase I/II trial that enrolled stage IV melanoma patients, monocyte-derived DC were transfected in vitro with pDNA encoding melanoma-associated antigens melan A and gp100 using a cationic peptide for pDNA transfer, and chloroquine to promote endosomal escape, and were stimulated with TNF (tumor necrosis factor)-α and IL-1β [56]. Patients were vaccinated every three weeks for a total of three months. Whereas antigen-specific T cell responses were observed, the clinical response rate was only in the range of 10%, and not sustained. So far, similar results have been obtained in most clinical studies on APC-focused pDNA vaccination (tabulated in [57]).
Only a few clinical trials have demonstrated therapeutic efficacy of pDNA vaccination. In a clinical phase I/II study, patients with carcinoembryonic antigen (CEA)-positive tumors (in most cases colorectal cancer) were repetitively treated with a pDNA vaccine that encoded for a MHCI-restricted CEA-derived peptide fused to an immunostimulatory domain derived from tetanus toxin fragment C as an adjuvant by intramuscular injection for three months [58]. About half of the patients developed diarrhea due to a break in tolerance towards CEA, which is also expressed by colonic mucosa. The group of patients that developed autoimmunity showed a prolonged overall survival over the 16 months observation period.
Several reports have shown that combined treatment with a pDNA vaccine and a second drug exerted improved anti-tumor responses. In a clinical phase I trial, progression of metastatic prostate cancer was attenuated in more than half of the patients vaccinated for three months with a prostate acid phosphatase encoding pDNA plus recombinant GM-CSF as an adjuvant, co-applied intradermally, in combination with the programmed cell death protein (PD-)1 blocking antibody pembrolizumab [59]. This effect was not observed in case of sequential treatment with the antigen encoding vector/GM-CSF for three months followed by pembrolizumab application. In a phase IIB/III trial, treatment of non-small-cell lung cancer patients with a vaccinia virus encoding the tumor-associated antigen (TAA) Mucin-1, and IL-2 to stimulate T cells (TG4010) by repetitive subcutaneous injections yielded longer overall survival of patients upon co-treatment with first line chemotherapy (different drugs) as compared to patients that received chemotherapy only [60]. The efficacy of TG4010 in combination with checkpoint inhibitors is evaluated in ongoing phase II trials (NCT02823990, NCT03353675).
Due to the overall low efficacy of pDNA vaccination in clinical trials observed so far, pDNA vaccines need to be improved to yield stronger immunogenicity. In the following various parameters that are important for the optimization of the design of pDNA vaccines as well as their delivery are discussed.

2.1.2. mRNA Vaccines

Until a few years ago, mRNA-based anti-tumor vaccines were largely evaluated in clinical studies using patient-derived autologous DC electroporated in vitro with TAA-encoding mRNA either alone, in combination with adjuvant-encoding mRNA or followed by stimulation with soluble mediators, followed by intradermal administration. In most of these trials, adaptive antigen-specific immune responses were detectable, but only some reached clinical responses (the outcome of these clinical trials is listed in [61]).
In an early phase II clinical trial, acute myeloid leukemia patients were vaccinated by intradermal injection with autologous DC electroporated in vitro with mRNA, encoding Wilms´ tumor 1 (WT1) antigen in bi-weekly intervals for four cycles [62]. About a third of the patients displayed complete remission after more than a year after the first vaccination. Therapeutic efficacy of vaccination with WT1-mRNA transfected DC was increased by including the lysosomal targeting signal of lysosomal-associated membrane protein (LAMP) [63], which previously demonstrated to achieve improved loading of antigen onto MHCII [64]. Similar results were achieved in another clinical phase II trial on patients with acute myeloid leukemia (AML) using human telomerase reverse transcriptase (hTERT) encoding mRNA for ex vivo electroporation of DC, followed by intradermal application [65]. The hTERT expression unit was fused to a LAMP minigene. Transfected DC were applied weekly for six weeks, followed by bi-weekly application for another six rounds. Recurrence-free survival of accordingly treated patients was prolonged as compared to historical controls.
Therapeutic efficacy of ex vivo mRNA-vaccinated DC was also demonstrated for glioblastoma, applied after surgical removal of the major tumor mass, and in combination with more conventional treatment regimens. In a phase II clinical trial, autologous DC were electroporated ex vivo with mRNA derived from surgically removed glioblastoma, and were maturated with a cocktail of proinflammatory mediators prior to intradermal application [66]. DC were applied six weeks after surgery and combined radiotherapy/chemotherapy (temozolomide), twice in the first week, and once per month afterwards (up to 18 treatments). All patients received chemotherapy throughout the vaccination period. The group of DC-treated patients showed prolonged progression-free survival. Strongly improved progression-free survival of glioblastoma patients vaccinated in a similar setting was also observed in a phase I clinical study using an mRNA encoding cytomegalovirus (CMV) pp-65 for DC transfection and GM-CSF as an adjuvant [67]. CMV pp-65 was chosen based on the fact that glioblastoma cells expressed this protein, but no other brain cells [68].
In melanoma therapy, efficacy of mRNA vaccines was observed in a study that enrolled stage III/IV melanoma patients after resection of metastases [69]. Autologous DC were co-transfected ex vivo with a mixture of four to six melanoma-associated antigen-encoding mRNAs (MAGE-A1/A3/C2, Melan A, gp100, tyrosinase) plus a mixture of adjuvants (either the toll-like receptor (TLR) 3 ligand polyriboinosinic:polyribocytidylic acid (poly(I:C)) plus CD40 ligand-mRNA, or mRNA coding for CD40L, CD70, and a constitutively active TLR4 mutant (TriMix-mRNA)). Transfected DC were applied intradermally in a bi-weekly cycle up to 12 times, and interferon (IFN)-α 2b was administered concomitantly in most cases. Vaccinated patients showed an increased survival rate as compared to historical controls. In a follow-up study on stage III/IV melanoma patients, co-treatment of patients with DC co-electroporated with either of the melanoma antigen-mRNAs plus TriMix, and concomitant treatment with the checkpoint inhibitor ipilimumab (CTL-associated protein (CTLA-)4 blocking antibody), applied every three weeks for a total of four times yielded better long term survival rates than ipilimumab treatment alone [70].
Within the last few years also some clinical trials assessing the potency of systemically applied mRNA-based vaccines (e.g., NCT02410733; Lipo-MERIT) have been initiated, using lipoplexes to prevent mRNA degradation. The mRNA vaccine tested in the Lipo-MERIT study aims to directly target DC for melanoma therapy [71], and is comprised of several mRNAs that encode four different TAA (MAGE-A3, NY-ESO-1, TPTE, and tyrosinase,) to be presented via MHCI and MHCII, and induce IFN type I driven immune responses due to intrinsic stimulatory activity. In a preclinical setting, a liposomal formulation that specifically addressed DC was identified by testing the biodistribution and cell binding properties of a library of cationic liposomes consisting of DOTMA (1,2-di-O-octadecenyl-3-trimethylammonium propane) and DOPE (dioleoyl phosphatidylethanolamine), which differed in their size and zeta potential [72]. mRNA-loaded lipoplexes with a negative net charge and a diameter of around 300 nm almost exclusively accumulated in the spleen and were shown to address splenic and lymph node DC.

2.2. Optimization Strategies for Nucleic Acid-Based Vaccines

2.2.1. Antigen

For tumor therapy, nucleic acid-based vaccines need to encode tumor-specific immunogenic peptides, which allows to comprise antigen-encoding sequences of different proteins within one minigene aimed to activate a broader number of CD4+ and CD8+ T cells [73]. In general, TAA may either constitute tumor-specific shared or tumor-specific unique antigens [74]. Whereas shared TAAs are also presented by normal cell types, albeit at lower extent, unique tumor antigens, also called neo-antigens, are exclusively expressed by tumors [75]. Especially in older studies, sequences encoding shared TAAs have been used [76], but this may also result in autoimmune responses [77]. On the contrary, effector T cell responses towards neo-antigens, identified in a tumor-specific manner by mutagenome analysis, have been reported to be more potent [78,79]. Moreover, antigens with a prolonged half-life have been shown to induce stronger CTL responses, and thereby increased immunogenicity [80]. To improve the presentation of (tumor) antigens, epitope-specific changes have been shown to increase MHC affinity [81], including the use of xenogeneic antigens [82]. Loading of pDNA-encoded antigens onto MHCII was also demonstrated to be improved by inclusion of the coding sequence of the invariant chain [83]. mRNA-encoded antigens were shown to be presented at higher extent via MHCII when fused with the lysosomal targeting signal of LAMP [64].

2.2.2. Adjuvant

Conventional pDNA was reported to possess intrinsic immunostimulatory activity due to a CpG-rich motif located within the ampicillin-resistance gene that triggered TLR9 in endo/lysosomes [84]. Besides, pDNA was also shown to bind cytosolic DNA sensors that mediate activation of the stimulator of IFN genes (STING) signaling pathway [85]. Moreover, physical stress associated with vaccination may also exert adjuvant effects as observed for gene gun-mediated delivery of gold particle adsorbed pDNA into the skin [86].
However, nucleic acid-based vaccines normally contain an adjuvant, which is delivered as a separate unit, like the TLR3 agonist poly(I:C) [69] or CpG oligodeoxynucleotides (ODNs) that trigger TLR9 [87,88], or more conventional adjuvants like Alum [89]. Whereas these moieties trigger danger receptors, in several studies the efficacy of transgenes that encode constitutively active mutants of danger receptors like TLR4, and receptors with co-stimulatory activity like CD40L and CD70 [69] to confer APC activation has been evaluated. Additionally, minigenes encoding signaling adaptors and transcription factors have been assessed in this regard. For example, Shedlock and co-workers reported that co-transfection of an NF-κB p65 expression plasmid and of a HIV protein encoding pDNA by in vivo electroporation of mice yielded stronger T cell responses [90]. Likewise, human monocyte-derived DC co-transfected in vitro with an mRNA encoding for a constitutively active form of IKKβ (inhibitor of nuclear factor kappa B kinase subunit beta) showed elevated upregulation of surface activation markers and cytokines like IL-12, and conferred stronger activation of co-cultured CD8+ T cells [91] and NK cells [92]. Similarly, biolistic co-transfection of mice with an IRF-3 encoding pDNA enhanced T cell responses towards co-applied influenza antigen-encoding pDNA [93].
Further, the suitability of pDNA [49] or mRNA [94] encoding cytokines intended to activate APC and to modulate T cells (in a paracrine manner) has been evaluated. For example, Li and co-workers co-administered healthy volunteers a multigene HIV DNA vaccine plus an IL-12 encoding pDNA by intramuscular injection, which conferred increased Th1/CTL responses [95]. Bontkes et al. demonstrated that human DC co-transfected in vitro with a TAA, and IL-12 as well as IL-18 encoding mRNA induced increased activity of co-cultured CD8+ T cells and NK cells [94]. Similar findings were made in a preclinical mouse study upon intramuscular administration of a pDNA encoding mycobacteria antigen and IL-15, known to activate both APC as well as T cells and NK cells [96]. Further, administration of IL-2 and IL-7 pDNA expression constructs aimed to promote T cell activation and proliferation have been tested in preclinical studies [97].

2.2.3. Inhibition of Regulatory Proteins in APC

In other studies, the potential of small interfering RNA (siRNA) to inhibit the expression of endogenous inhibitory key factors in APC has been tested. For example, Luo and co-workers boosted anti-tumor responses using NPs that co-delivered the TLR3 ligand poly(I:C) and a siRNA specific for the transcription factor STAT (signal transducer and activators of transcription) 3 [98], which induces expression of anti-inflammatory factors like IL-10. Likewise, NPs delivering siRNA specific for the co-inhibitory receptor programmed cell death (PD) ligand 1 (PD-L1) have been evaluated in tumor studies [99]. More recently, also micro-RNA (miRNA) species, which constitute endogenously expressed small RNA species that inhibit gene expression (Figure 2), are considered interesting candidates to modulate the activation state of APC [100]. For example, delivery of a plasmid harboring multiple miRNA consensus bindings sites, termed miRNA sponge [101] and of anti-miRNA oligonucleotides [102], is intended to limit the inhibitory effect of miRNAs on activation-associated mRNA targets.

2.2.4. Structural Optimization of pDNA Vaccines

Expression Units

In most of the aforementioned studies pDNA and mRNA species encoding antigen and adjuvant were applied as separate plasmids (in trans). However, the approach to integrate several transcription units into the same pDNA or mRNA in cis has received growing interest [104]. In case of pDNA, according vectors may either contain separate expression units each driven by another promoter, or a single promoter that regulates expression of the antigen and of molecular adjuvants. In case of the latter, which is also possible in case of mRNA vaccines, the different expression units may be separated either by an internal ribosomal entry site that confers cap-independent translation [105,106] or virus-derived recognition sites [107], which in the derived long peptide are recognized by a ubiquitously expressed protease [108].

Size Reduction

A large part of pDNA is of prokaryotic origin and is required only for propagation in bacteria. It has been shown that after transfection prokaryotic parts are silenced by formation of heterochromatin, which may spread into the eukaryotic expression unit(s), and thereby limit transgene expression [109]. Therefore, the strategy to flank the expression cassette comprised of the promoter and the transgene-encoding part with phage recombinase-recognition sites has received growing interest. This configuration allows deletion of the prokaryotic part in the late phase of plasmid propagation by inducing phage recombinase. In several studies the derived mini-circle DNA (mcDNA) was reported to yield a higher transfection efficiency as well as a longer duration of gene expression as compared to the full length parental construct [110].

Nuclear Transfer

Moreover, in case of a pDNA vaccine its nuclear translocation is necessary for transcription of the encoded transgene(s), which constitutes a hurdle in mitotically inactive APC [111]. It was shown that transcription factors may bind recognition sites within the gene regulatory regions of the pDNA, and mediate nuclear import of the pDNA by their nuclear localization signal (NLS) [112]. Especially the simian virus (SV)40 enhancer sequence was demonstrated to harbor several of these transcription factor binding sites, and inclusion of this region directly upstream or downstream of the transgene expression unit conferred enhanced nuclear import and elevated transfection efficiencies [40]. In a more controlled manner, viral peptides (e.g., SV40 large T antigen) coupled to pDNA can facilitate its nuclear entry via their NLS [113].

Transcriptional Regulation

Expression units of pDNA-based vaccines are often under transcriptional control of virus-derived promotors characterized by ubiquitous activity at high level, like the human intermediate/early CMV or the SV40 promoter [114]. Since viral promoters may be subjected to methylation-mediated inactivation, both eukaryotic promoters, like the human elongation factor (EF)1α or beta-actin gene promoter, as well as viral/eukaryotic hybrid (e.g., CMV/beta-actin) promoters have been introduced that allow long term transgene expression [115]. These types of promoters are still widely used in preclinical and clinical studies. On the contrary, the potential of promoters that restrict gene expression to DC to avoid unwanted vaccine expression by regulatory immune cells (e.g., TAM, MDSC) has been assessed in a limited number of preclinical studies only. The promoter of DC-STAMP (dendrocyte-expressed seven transmembrane proteins) is active in unstimulated human and mouse DC as well as in macrophages, and is downregulated upon stimulation [116]. Mice transduced with a lentivirus containing the DC-STAMP promoter displayed reporter activity in DC, monocytes, B cells, and NK cells [117]. Biolistic transfection of mice with a pDNA containing the promoter of the Langerhans cell (LC)-specifically active Dectin-2 gene resulted in LC-specific reporter activity [118], and when employed in a lentiviral vector conferred both DC- and macrophage-restricted reporter expression [119]. In several studies the promoters of the evolutionarily conserved human [120,121] and mouse [120,121] fascin-1 genes were demonstrated to restrict gene expression to maturing DC. Biolistic transfection of mice with fascin-1 promoter driven antigen encoding pDNA yielded largely DC-restricted transgene expression, and conferred Th1-polarized immune responses in models of allergy [122], and multiple sclerosis [123]. Furthermore, pDNA encoding for anti-inflammatory transforming growth factor (TGF)-β [123] and IDO [124] under transcriptional control of the fascin-1 promoter yielded tolerogenic effects.

2.2.5. NPs for APC-Focused Delivery of Nucleic Acids

Biocompatible NPs are highly interesting for cellular transfer of nucleic acids [125] in the context of nucleic acid-based tumor therapy [126], since they offer protection against extracellular degradation by DNases [127] and RNases [128] either by dense complexation [129] or encapsulation [130] of nucleic acids. Especially in case of systemic application, NPs may confer either due to their intrinsic properties passive [72] or upon conjunction with surface receptor targeting moieties active [46] targeting of APC populations.

NP Size and Surface Characteristics Affecting Biodistribution

With regard to the design of NPs it needs to be taken into account that DC as the often preferred target cell type internalize smaller particles (<200 nm) more efficiently [131], whereas monocytes/macrophages preferably ingest larger ones (<5 µm) by means of receptor-mediated endocytosis and phagocytosis [132]. Besides size, also the shape of the NP may affect the efficacy of uptake as evaluated for gold-based NPs, which were engulfed by macrophages more efficiently in case of spherical as compared to e.g., elongated shape [133]. Both the cellular internalization of transfection complexes and the endosomal release of NP-complexed nucleic acids, can be increased by cell penetrating peptides (CPP) that are attached either e.g., to the pDNA [134] or to the NP [135].
Concerning the biodistribution of nucleic acid/NP transfection complexes, it was shown that small particles are easily transported into the lymph node, whereas larger particles remain longer at the site of administration [136]. Further, the route of administration can also account for the fate of NP delivery systems. After subcutaneous injection small PEGylated liposomes were found in a larger amount in the lymph node than after intravenous or intraperitoneal application [137]. Concerning NP clearance from the body, NPs that are smaller than 8 nm are cleared renally [138], and the extent of renal clearance was shown to correlate with the extent of negative charge [139]. Biliary clearance was observed especially for particles over 200 nm, and for strongly charged particles [140].

NP Types Suitable for APC Transfection

By now, a large variety of materials and structures has been evaluated for transfer of nucleic acids into APC, comprising inorganic materials like solid core gold [141] and iron oxide-based [142], mesoporous silica [143], and graphene oxide [144] based NPs. The latter have repetitively shown to confer endosomal escape of nucleic acids [145,146]. Polymer-based NPs bind nucleic acids by electrostatic interactions [147]. PLG (poly-D,L-lactide-co-glycolide) [148], PLGA (poly-D,L-lactic-co-glycolic acid) [149], and polyethylenimine (PEI) [150] are among the most intensely studied polymer-based NPs for delivery of nucleic acids. Of these, PEI by acting as a ’proton sponge’ conferred the most pronounced endosomal release of nucleic acids [151], but at the same time also mediated strong cytotoxicity [152]. Chitosan is a natural polysaccharide-based polymer, which has been evaluated for pDNA transfer [153] and similar to PLGA [154] was demonstrated to exert immunostimulatory activity [155]. Protein-based NPs offer the advantage of high biocompatibility [156]. For example, gelatin B (negatively charged) combined with protamine sulfate (positively charged) conferred DNA transfection, and mediated pDNA release under acidic conditions as apparent in endolysosomes [157]. Using endogenous proteins as nano-carriers may reduce potential immune reactions in response to repetitive application. In this regard, serum albumin coated with chitosan conferred DNA transfection [158]. NPs, consisting of albumin conjugated with cationic ethylenediamine complexed Bcl-2 specific siRNA, intravenously injected into mice with established melanoma lung metastases successfully inhibited further tumor progression [159]. Cationic lipids complex negatively charged nucleic acids by electrostatic interactions, and by interaction with the negatively charged cell membrane confer internalization of lipoplexes [160]. DOTAP (N-[1-(2,3-dioleoyloxy)propyl]-N,N,N-trimethylammonium chloride) was the first lipid to be used for pDNA transfection [161], and is still used either as a single component for complexation of nucleic acids or in combinations with helper lipids. With regard to the latter, neutral helper lipids like cholesterol have been included resulting in much stronger transfection efficiency presumably due to elevated endosomal escape of passenger DNA [162]. Incorporation of coiled-coil lipopeptides into liposomes resulted in direct release of the payload into the cytosol [163].

Administration Routes

Direct transfection of APC in secondary lymphoid organs can be achieved by intravenous application [164], given that the nano-vaccine predominantly addresses APC by passive [72] or active [165] targeting. This would result in the induction of antigen-specific T effector cells, which can home to each tissue, and thereby also reach metastases irrespective of their location. However, as delineated in preclinical rodent biodistribution studies, systemically administered NPs of larger size (≥ 200 nm diameter) may accumulate e.g., in lung as reported e.g., for mesoporous silica particles [166] or chitosan NP [167]. Moreover, most NP formulations tested so far accumulate in the liver [168] as a consequence of the general clearance function of the liver [169], conferred by Kupffer cells (KC) as the major liver-resident macrophage population [170] and liver sinusoidal endothelial cells (LSEC) [171]. KC and LSEC are equipped with a number of danger receptors, including different C-type lectin receptors (CLR) as e.g., the mannose receptor CD206 [172,173], and scavenger receptors that broadly bind negatively charged ligands [174,175]. Besides, KC [176] and LSEC [177] express high affinity Fc receptors, and KC also express complement receptors [178]. Therefore, it is conceivable that NPs, depending on the characteristics of the protein corona formed in vivo [179], also including complement activation as shown for lectin-coated NP [180], may be internalized preferentially by KC and LSEC. The formation of a pronounced protein corona may be attenuated by PEGylation, shown to reduce unwanted binding to KC [181] and LSEC [182], and by conjugation with CD47, which serves as a ‘do not-eat-me’ ignal for macrophages as evaluated for liposomes [183]. Furthermore, targeting moieties on NP may engage according receptors on either non-parenchymal liver cell population. An example is mannose, which has frequently been used to address CD206-expressing APC of myeloid origin [184,185].
NP delivery via the skin constitutes an interesting alternative to systemic NP delivery for several reasons: (i) topical application circumvents unwanted liver accumulation, (ii) cutaneous DC, comprising Langerhans cells (LC) as the epidermal DC population, which form a dense network (200–1000 LC/mm2 [186]), and dermal DC are apparent at rather high numbers in skin, and (iii) targeting is not necessary since only DC, at activated state, are able to migrate to secondary lymphoid organs [187]. By now, several approaches for transfection of skin DC have been tested successfully in clinical trials concerning safety and tolerability and are used in preclinical studies to evaluate vaccines. These include conventional intradermal injection [188], biolistic transfection of nucleic acids pre-adsorbed onto particles applied by gene gun [189] and PMED (particle-mediated epidermal delivery) [190], patches with dissolvable microneedles [191,192], and tattooing devices [193]. All of these transdermal delivery methods can transfer NP-complexed nucleic acids [194]. In case of biolistic transfection the method-associated physical stress was sufficient to confer activation and consequently emigration of transfected DC [86]. Further, administration of an electrical pulse just after intradermal [195] and intramuscular [196] injection, was shown to induce local inflammation, which activated APC at the according site, and to enhance overall transfection rates [197]. Consequently, electroporation devices that are applied in the context of intradermal injection are currently tested in clinical phase I (e.g., NCT04336410) and phase II (NCT03180684) pDNA vaccination studies.
Other potential delivery routes for tumor vaccination comprise the respiratory system by applying nebulized pDNA or mRNA that largely transfect lung epithelia [198], which has predominantly been employed for treatment of lung diseases like cystic fibrosis [199], and oral vaccination approaches using attenuated bacteria (e.g., Salmonella typhimurium) for pDNA transfer to APC in Payer’s patches [200].

Targeting of APC

Passive targeting of DC and monocytes/macrophages in vivo may be a consequence of the protein corona formed in case of many types of NPs due to adsorption of serum factors, which may constitute genuine ligands for cell surface receptors [179]. The composition of the protein corona is determined by several factors including e.g., charge and hydrophobicity of the particle surface. Further, serum factors due to interaction with the particle surface may alter their state of conformation, and thereby are recognized as ‘new’ ligands e.g., by scavenger receptors [201]. Finally, NPs may be recognized as pathogen-like by the innate immune system, e.g., in case of lectin surfaces intended to ensure biocompatibility of the NP, which however was found to trigger the lectin-dependent complement pathway [202]. This in turn resulted in adsorption of active complement C3 on the particle surface, and subsequent recognition of immune cells via complement receptors [180]. Unwanted adsorption of serum factors may be limited by conjugation with polyethylene glycol (PEG) [203]. However, concerning the repetitive application of vaccines potential adverse reactions as e.g., the induction of PEG-specific antibodies [204] need to be taken into account.
Active targeting of transfection complexes to DC and monocytes/macrophages can be achieved by conjugation of NPs with derivatives of natural ligands and antibodies that specifically bind endocytic surface receptors like C-type lectin receptors, which are expressed in a largely cell type-specific manner [205]. For example, the mannose receptor CD206 is highly expressed by macrophages (M2-like > M1-like), and is apparent at some extent on conventional DC [206], whereas DC-SIGN is predominantly expressed by conventional DC populations, but only by a low fraction of macrophages [207]. In a preclinical study, intramuscular vaccination of mice with mannosylated cationic liposomes (distearoylphosphoethanolamine-polycarboxybetaine/DOTAP/cholesterol) that showed intrinsic DC stimulatory activity and complexed a HIV antigen-encoding pDNA improved HIV-specific T cell responses [208]. More recently, trimannosylated liposomes (1,2-bis(hexadecyl)glycerol/1,2-Dioleoyl-sn-glycero-3-phosphocholine/cholesterol) were shown to specifically address DC-SIGN, and to accumulate at highest extent in the spleen after intravenous application, addressing predominantly DC [165]. While these approaches aimed to directly transfect APC in vivo, in an alternative approach Wang and co-workers designed a pDNA that encoded a fusion protein consisting of a tumor antigen polypeptide and a single chain antibody fragment known to bind the murine DC-specific receptor CD11c [209]. Thereby, this pDNA was aimed to be expressed in non-APC, but the expressed fusion protein was meant to target DC. In a mouse breast cancer model intramuscular injection of this pDNA prevented tumor growth when applied protectively prior to subcutaneous tumor cell inoculation, and attenuated tumor progression in a therapeutic setting. As mentioned above, lipoplexes composed of DOTMA and DOPE loaded with mRNA with a negative net charge and a size of around 300 nm due to these characteristics predominantly targeted DC in secondary lymphoid organs [72].

3. Inhibition of Regulatory Immune Cells

The success of vaccination to induce a sustained antigen-specific anti-tumor response is limited by regulatory immune cells that are induced and expanded by tumors as part of their evasion strategy [210]. Both MDSC [211] and Treg [212] can attenuate the T cell stimulatory activity of APC, the activation of T cells as well as the anti-tumor function of Teff, and effector functions of NK cells. To counteract the suppressive effect of regulatory immune cells the suitability of RNAi has been delineated [213,214]. Further, nucleic acids with immunostimulatory function were reported to reprogram MDSC to exert anti-tumor activity [215].

3.1. Inhibition of Treg by RNA Interference

Under homeostatic conditions Treg ensure tolerance towards self-antigens to prohibit autoimmunity [216], and against harmless antigens to prevent allergies [217]. Besides, as a negative feedback mechanism Treg are expanded and are also induced de novo in the course of immune reactions in order to limit immune responses and thereby to minimize tissue damages. Under healthy conditions Treg occur only in small numbers [218]. Depending on the place of origin Treg can be differentiated in thymic Treg (tTreg), alternatively termed natural Treg, [219] and in Treg that are induced in the periphery (iTreg) [220]. During thymopoiesis thymocytes, which express a T cell receptor (TCR) with intermediate affinity for self-peptides, differentiate into immunosuppressive tTreg [221]. iTreg derive from CD4+/CD8+ T cells, whose TCR is not specific for self-antigens, but recognizes microbiota- and environmental antigens presented by DC in the periphery [222] in the context of low co-stimulation and/or Treg-promoting factors like retinoic acid, kynurenine, and TGF-β [223,224]. In mice, tTreg and some iTreg populations can be identified by constitutive expression of the IL-2 receptor CD25 and by co-expression of the transcription factor FoxP3 [225], whereas other iTreg populations are Foxp3-deficient, but may express anti-inflammatory mediators like IL-10 and TGF-β [226].
In cancer, constituents of the TME produce anti-inflammatory mediators, which promote Treg expansion/induction in the periphery [218], and release of chemokines as for example the C-C motif chemokine ligand (CCL) 22, to recruit Treg to the tumor [227]. Treg suppress anti-tumor responses on the level of APC activity, T cell activation, T effector cell functions, and the functions of NK cells by numerous mechanisms, as for example anti-inflammatory cytokines (e.g., IL-10, TGF-β), surface receptor interactions (e.g., negative cross-talk via CTLA-4), IL-2 depletion, and transfer of cyclic adenosine monophosphate (cAMP) [228].
There are different approaches to overcome the obstacle of Treg-mediated suppression of anti-tumor responses, including strategies to deplete Treg or to reduce their suppressive activity [229]. Concerning nucleic acid-based approaches to attenuate Treg induction, silencing of tumor-derived TGF-β in murine CT26 colon carcinoma cells by transfection with oligofectamine/TGF-β1 siRNA complexes suppressed Treg induction [230]. Most recently, Masjedi et al. reported that ex vivo silencing of the adenosine A2A receptor (A2AR) with an A2AR-specific siRNA complexed with PEG-chitosan-lactate (PCL) NPs inhibited the differentiation of CD4+CD25 T cells derived from 4T1 breast tumor-bearing Balb/C mice toward Treg [231]. Alternative approaches have aimed to minimize the suppressive capability of Treg. For example, in vitro transfection of murine Treg with a Foxp3-specific siRNA resulted in profound inhibition of their suppressive capacity [232]. Another treatment option is to interfere with the recruitment of Treg to the tumor site. Kang and co-workers have demonstrated that tumor infiltration with Treg in athymic nude mice, inoculated with human breast cancer cells, can be prohibited by tail vein injection of Treg transfected with a siRNA specific for CCL22 [233]. Besides the use of synthetic siRNA for RNA interference, in recent years miRNA (over)expression intended to alter the genetic program of Treg has gained increasing interest. In this regard, lentiviral transduction of Treg in vitro with miR-9 and miR-155 encoding vectors resulted in reduced expression of CTLA-4, which is a key factor for the immunosuppressive activity of Treg [234]. Additionally, Jonuleit et al. reported that in a mouse melanoma model systemic delivery of CTLA-4 specific siRNA by cationic lipid-assisted PEG–poly(lactic acid (PLA))-based NP resulted in reduced Treg numbers, and inhibited tumor growth [235]. Administration of miR-141 and miR-200a mimics in multiple sclerosis patients shifted the differentiation of naive T cells towards Th17, and at the same time inhibited Treg differentiation [236]. In a mouse model of epithelial ovarian cancer (EOC) in vitro transfection of CD4+ T cells with miRNA 29a-3p and miR-21-5p mimics, complexed with the commercially available X-tremeGENE siRNA transfection reagent, followed by adoptive transfer into tumor-burdened mice, tumor growth was attenuated [237]. This outcome was based on the inhibitory effects of both miRNA species on STAT3 expression, thereby favoring Th17 over Treg differentiation. In another study, transfection of Treg with miR-142-3p reduced the level of intracellular cAMP and adenylyl cyclase type 9 expression, which impaired their suppressive properties [238]. Treg-specific delivery of biologicals may be achieved by using IL-2-functionalized NPs as shown for hydroxyethyl starch nanocapsules that targeted Treg due to their constitutive high level expression of the IL-2 receptor CD25 [239].
Altogether, these studies demonstrate that nucleic acid-based strategies have a high potential to reduce overall Treg activity in cancer. However, it should be noted that Treg depletion may result in a compensatory induction of MDSC [240].

3.2. Strategies for MDSC Reprograming and Depletion

MDSC derive from myeloid precursor cells during myelopoiesis [241]. Immunomodulatory factors generated by tumors like some cytokines, chemokines, or colony-stimulating factors (CSF) are capable of stimulating expansion of MDSC on the expansion of monocytes, conventional DC, and neutrophils [242], while chronic inflammations can lead to extramedullary myelopoiesis [243]. The expansion and activation of generated MDSC requires concerted interaction of several signaling pathways, like the NF-κB, JAK-STAT, HIF-1α, C/EBPβ, and CHOP pathway. Based on the expression of plasma membrane markers, the amount of immune suppressive molecules as well as by functional analysis [244], MDSC can be allocated to CD11b+Ly6GLy6Chi monocytic (m)MDSC and to CD11b+Ly6G+Ly6Clow granulocytic (g)MDSC [245]. MDSC exert potent immune-suppressive activity against T cells [246] and NK cells [247]. Accordingly, MDSC contribute to control autoimmunity [248] and infections [249]. After activation, MDSC migrate to the site of inflammation or to the tumor site in response to a variety of chemokines [250]. There, MDSC generate an immune-suppressive milieu, which is enhanced by different cytokines [243]. The infiltration of mMDSC into a tumor leads to a distribution of tumor cells from the place of origin by induction of epithelial–mesenchymal transition (EMT), which generates a cancer stem cell (CSC) phenotype [251]. Tumor infiltration of gMDSC withdraws the CSC phenotype and leads to tumor cell proliferation and promotes metastasis. In secondary lymphoid organs MDSC suppress APC, the activation of tumor antigen-specific T cells, and T effector cells by several mechanisms in an analogous manner as described for Treg [252].
In some approaches siRNA and miRNA have been applied to attenuate MDSC generation and their suppressive activity. For example, Boldin et al. have shown that miR-146a inhibited the proliferation of MDSC by targeting tumor necrosis factor receptor-associated factor 6 (TRAF6) and IL-1 receptor-associated kinase 1 (IRAK1) [253]. Similarly, miR-424 was reported to interfere with MDSC differentiation [214]. In several mouse tumor models intravenous application of oligofectamine/miR-223 complexes inhibited tumor-conferred MDSC generation by targeting myocyte enhancer factor 2C (MEF2C) in bone marrow progenitor cells [254].
Moreover, some types of NPs as an intrinsic property have been reported to reprogram MDSC towards proinflammatory macrophages as shown e.g., for cationic dextran- and PEI-based NP [215] in vitro and for NP modified with a cationic polymer in vivo [255]. In addition, TLR agonists that address TLR7/8 (e.g., R848) and TLR9 (CpG ODN) were shown to exert similar effects both in vitro and in vivo [256], which may contribute to the overall immunostimulatory effect of these adjuvants.

3.3. Inhibition of Treg and MDSC by Tumor-Directed Approaches

Besides direct targeting of Treg and MDSC via RNA interference, the induction/expansion and tumor infiltration of either regulatory cell type may also be controlled indirectly by affecting tumor gene expression and as a secondary effect in the course of inducing anti-tumor responses. Stem cell factor (SCF; c-kit ligand) is generated by tumors and confers MDSC infiltration [257]. In a mouse MCA26 colon tumor model adenoviral transfer of SCF-specific siRNA resulted in reduced accumulation of MDSC at the tumor site [258]. Injection of a TNFAIP3-specific siRNA into E.G7 or B16-F10 melanoma induced apoptosis in MDSC via activation of the c-Jun N-terminal kinase (JNK) pathway [259]. Injection of vascular endothelial growth factor (VEGF)-specific siRNA, complexed with nanogels, into renal tumors significantly reduced MDSC numbers in that area [260]. Injection of a Newcastle Disease Virus Hemagglutinin–Neuraminidase encoding pDNA into the ear pinna of DA3 tumor bearing Balb/c mice promoted innate anti-tumor responses and reduced MDSC infiltration into the tumor site [261]. In humans suffering from pancreatic ductal adenocarcinoma (PDA), in many cases antibodies and T cells specific for α-enolase (ENO1) have been identified [262]. In a mouse model of autochthonous pancreatic cancer, injection/electroporation with a ENO1-encoding pDNA attenuated tumor growth and concomitantly also the expansion of Treg and MDSC [263].

4. Generation of T Cells and NK Cells Expressing CARs for Tumor Therapy

CARs are synthetic antigen receptors, which comprise an extracellular antibody domain, a transmembrane domain, and an intracellular signaling domain, and recognize e.g., tumor-associated antigens [264]. So-called CAR T cells (CAR-T) and CAR natural killer cells (CAR-NK) are generated by transfection of either cell type with a CAR-encoding pDNA, mRNA, or are transduced with a CAR-encoding viral vector [265]. Therefore, CAR expressing cells are able to recognize antigens under tumor-induced immune-suppressive conditions and can exert a proper immune response. For CAR synthesis, the variable domains of an antibodies’ light and heavy chain are fused, for example by short glycine-serine linkers, to yield a single chain fragment variable (scFv) [266]. The transmembrane domain is usually derived from CD28 or another membrane receptor [267]. In most cases CD3ζ, which is a component of the endogenous TCR, serves as the signaling domain for CAR-T [268]. For CAR-NK the transmembrane immune signaling adaptor chain is employed as the signaling domain [264]. The signaling domain is often combined with one or more co-stimulatory motifs [269] like CD28 [270], CD137, CD357, CD278, or CD134 [271] for CAR-T, and CD28, CD137 [272], CD278, CD134 [273], or Dap10 [270] in case of CAR-NK. The first generation of CARs contained only CD3 (ζ or γ chain) signaling motifs, which are able to activate murine CTL hybridoma cells, modified with chimeric genes for surface receptors, e.g., to trigger IL-2 secretion, but these may be inactivated by tumors [274]. The second generation of CARs was equipped in addition with a co-stimulatory domain, and the third generation possessed more than one co-stimulatory domain [275].
In an alternative approach, the signaling and the co-stimulatory domains are split between two different CARs, which is termed combinatorial targeting [264]. Until now, two CAR-T based immunotherapies have been approved by the United States Food and Drug Administration (FDA). Both are CD19-directed CAR-T immunotherapies, targeting the pan-B cell receptor CD19. They have shown significant results in the treatment of non-Hodgkin lymphoma (NHL), acute lymphoblastic leukemia (ALL), and chronic lymphocytic leukemia (CLL) [276]. Of these, treatment with tisagenlecleucel (T cells from the patients’ blood are lentivirally transduced with CD19-speciic CARs) yielded an overall remission rate of 81% after three months in patients suffering from relapsed or refractory ALL, but caused serious, mainly reversible toxic effects in children and young adults under 25 years [277]. In patients with NHL, axicabtagene ciloleucel (lentiviral transduction of patients’ blood T cells with CD19-specific CARs) resulted in an objective response rate of 82%, and a complete response in 54% of cases [278]. However, treatment with either CAR-T treatment can lead to serious and even life-threatening side effects, like the tumor lysis syndrome, a disease which can result from a tumor therapy, causing hyperuricemia, hyperkalemia, hyperphosphatemia, and hypocalcemia [279], and the cytokine release syndrome that is induced by a cytokine storm [280], leading to fever, hypotension, and respiratory insufficiency [281].
Another problem of CAR-Ts is the interaction of MDSC with CAR-Ts, which may lead to a reduction of CAR-T activation, to reduced proliferation after antigen stimulation, and lowered cytokine production [282]. MDSC in the liver for example suppress an anti-tumor response of CAR-Ts via binding of PD-L1 that engages PD-1 on T cells [283]. The expression of PD-L1 by MDSC in the liver is supported by GM-CSF and is largely regulated by the transcription factor STAT3. The negative effect of MDSC on CAR-T can be avoided by MDSC depletion, using therapeutic drugs like gemcitabine and 5-fluorouracil [284], neutralization of GM-CSF, e.g., by otilimab that is currently assessed in a clinical phase 3 study [285], and PD-L1 blockade, e.g., by checkpoint inhibitors like atezolizumab [286]. For example, Fultang and co-workers have recently shown that the activity of an anti-GD2-/mesothelin-/EGFRvIII-CAR-T was significantly enhanced when co-applied with the anti-MDSC drug gemtuzumab ozogamicin, an anti-CD33 antibody linked to cytostatic calicheamicin [287]. Altogether, due to the high potential of CARs for cancer treatment, improvement of CAR-based therapy is in the focus of research. For example, Wang et al. have recently generated CAR-T cells by electroporation-based transfection of T cells with non-viral mcDNA, which is considered much safer than virus-based chimeric antigen receptor-engineered CARs [288].

5. Manipulating the TME Using Therapeutic Nucleic Acids

The TME is a complex, very heterogeneous network of stromal and endothelial cells as well as recruited immune cells [289]. It is characterized by leaky blood vessels, a special tumor-specific extracellular matrix (ECM), immunomodulatory agents/cytokines, and growth factors [18,289,290,291]. The TME plays an important role during tumorigenesis as well as tumor progression and metastasis by supporting the tumor cells in evading the immune system [19,292] and by contributing to chemoresistance [293]. Different cell types like CAF [294], TAM (pro-tumoral phenotype) [295,296,297], MDSC, and Treg (see Section 3) [18] as well as tolerogenic DC [18,298] contribute to the establishment and maintenance of the immunosuppressive tumor surroundings. In addition, the TME inactivates effector functions of tumor-infiltrating lymphocytes (TIL) by various mechanisms, and thus undermines immunosurveillance [292,299,300].
Further characteristics of the tumor tissue comprise acidity (≈pH 6.5) due to the Warburg effect [301,302], hypoxia [303], expression of distinct matrix enzymes like matrix metalloproteases (MMPs) [304], and an elevated redox potential [305] as well as increased levels of reactive oxygen species (ROS) [306]. These properties display barriers in the delivery process of anti-tumor drugs, but can be also exploited for bio-responsive targeting of therapeutics to the tumor tissue [307]. By this, tumor selectivity and overall biocompatibility might be enhanced. Besides, passive targeting via the enhanced permeation and retention (EPR) effect [308], and more effective tumor addressing via tumor homing peptides and CPPs can increase accumulation of (nano) formulations within the tumor [309,310,311]. In addition, active targeting mediated by ligands such as peptides, vitamins, or antibodies is often utilized to direct a therapeutic selectively to the target site [312].
Immunotherapeutic approaches often aim to evoke a switch from immunosuppression to immune permission within the tumor tissue. By this, the tumor becomes immune-sensitive again, and then can be effectively combated by the innate and adaptive immune system. In the following, a selection of diverse strategies for TME manipulation is presented with a focus on nucleic acid-based approaches.

5.1. Modulation of Intratumoral Signaling by Nucleic Acids

In the immunosuppressive TME a disproportion exists between soluble mediators (cytokines and growth factors) exerting pro- and anti-inflammatory properties, thereby promoting tumor immune escape and tumorigenesis [313]. There are two options to counteract this imbalance, resulting in effective anti-tumor activity [313]. On the one hand, the immune system can be stimulated by overexpression of pro-inflammatory cytokines. On the other hand, immunosuppression can be reduced by inhibition/neutralization of anti-inflammatory signals.
Cytokines are key mediators in the communication of immune cells and are crucially involved in controlling the intensity of an immune response [314,315,316]. Thus, it is not surprising that cytokine therapy has been pursued as a cancer immunotherapeutic approach for more than 30 years now. However, in clinical studies, such cytokine therapies have not met the expectations based on the results of preclinical studies, especially when applied as monotherapies [313]. Only IFN-α [317] and IL-2 as high-dose therapy [318] have been approved for the systemic treatment of several cancers, based on moderate beneficial anti-tumor effects in clinical trials. Ongoing research is focused on increasing therapeutic efficacy and biocompatibility by developing recombinant cytokines with improved pharmacokinetics (e.g., PEGylated or fused with targeting antibodies), combinations with other immunotherapeutic approaches such as immune checkpoint inhibitors, and local or specifically targeted administration of (recombinant) cytokines [313]. Besides that, cytokine gene therapy (using gene encoding pDNA or viral vectors) and other nucleic acid-based approaches (like RNAi or genome editing) are promising concepts [24,313,316]. Table 1 summarizes such nucleic acid-based approaches evaluated in clinical trials. In the following, important signaling molecules and strategies (especially therapeutic nucleic acids) to modulate their levels within the tumor tissue are outlined.
IL-2 stimulates T-lymphocytes and NK cells, but also controls the duration and intensity of their activation, regulates immune homeostasis, and balances the Teff/Treg ratio [313,334]. Various autologous/syngeneic as well as allogeneic IL-2 gene-modified tumor cell vaccines have been investigated in preclinical and clinical studies for their potential in prophylactic and therapeutic application for the treatment of advanced and metastatic cancers like melanoma [319,320,321,322,335,336,337]. In vitro transduction of tumor cells with the IL-2 gene was achieved using viral vectors (e.g., retro-viral or adenoviral) [320,322,336] or by employment of advanced methods like the adenovirus-enhanced transferrinfection (AVET) system [319,335,337,338]. The toxicity profile of systemic IL-2 gene therapy can be improved by transcriptional targeting of IL-2 to the tumor to ensure specific expression of the IL-2 gene within the tumor [339,340,341].
TNF-α exhibits tumoricidal effects by inducing apoptosis and hemorrhagic necrosis of tumor cells [323]. GenVec’s TNFerade is a replication-deficient adenoviral vector encoding for TNF-α under the control of a radiation-inducible promotor [323,324], applied by intratumoral injection. Phase III clinical trials have been terminated in 2010, as a study in locally advanced pancreatic cancer failed to show a significantly improved outcome of combination therapy with TNFerade in comparison to standard therapy alone [342]. Reduced transgene expression may be caused by (pre-existing) immune responses against the adenoviral vector, mainly mediated by antibodies, limiting the option of repeated application [343]. Besides viral vectors, non-viral carrier systems for TNF-α delivery are subject of research as well. Kircheis et al. for example designed surface-shielded transferrin-PEI/DNA complexes for targeted TNF-α gene delivery after intravenous application in tumor-bearing mice [344]. Significant and selective TNF-α expression within the tumor without detectable serum levels could be demonstrated in three different tumor models. In a combination approach, Su et al. evaluated to which extent systemic TNF-α gene therapy synergized with liposomal doxorubicin (Doxil®) to enhance tumor endothelium permeability, and thus would promote accumulation of the chemotherapeutic drug within the tumor [345]. Synthetic polymers based on amino ethylene units [346,347] were used as pDNA carriers. The beneficial effect of TNF-α expression on concomitant Doxil® therapy was proven in all tested tumor models including metastases [345]. All in all, this combination approach offers great potential in treating metastases even with low doses of chemotherapeutic drugs. Quinn et al. achieved synergistic effects on tumor growth inhibition by combining systemic application of a previously evaluated RGD-targeted adeno-associated virus phage encoding for TNF-α [348,349] with hypo-fractionated radiation for the therapy of disseminated melanoma [350].
Another interesting candidate for cancer immunotherapy is IL-12 because of its ability to activate both the innate and the adaptive immune system [351]. In addition, IL-12 has anti-angiogenic properties by inducing IFN-γ, which in turn inhibits VEGF and MMPs [313,351,352,353,354]. In early clinical trials, however, the anti-tumor activity of systemically applied IL-12 was found to be only moderate, and was accompanied by severe side effects [351,355]. IFN-γ as induced by IL-12 is mainly responsible for the dose-related and schedule-dependent toxicity [353,356]. New strategies focus on targeted and local delivery of IL-12 to minimize systemic toxicity and to improve specific tumor targeting by conjugating IL-12 to tumor antigen-specific monoclonal antibodies (so-called immunocytokines) [357,358]. Moreover, various IL-12 gene therapy approaches ex vivo and in vivo are pursued [359,360]. Different delivery methods comprise viral vectors like adeno- or retroviral vectors [325,361,362,363,364,365,366], and non-viral techniques such as electroporation [367,368,369,370,371,372,373] or synthetic carrier systems like (lipo)polymer-DNA complexes and liposomes [374,375,376,377]. In order to increase the specificity of local IL-12 expression within the tumor, an IL-12 transgene with a ligand-inducible expression switch was designed [325,364]. Another way to locally control in situ expression of IL-12 is to engineer CAR- T cells, which release IL-12 in an inducible or constitutive manner [378]. Moreover, the IL-12 gene may be inserted in the genome of oncolytic viruses as an immune stimulatory component (see Section 5.3).
GM-CSF has been investigated as an adjuvant for different types of vaccines because of its stimulatory effect on myeloid cell types like conventional DC and macrophages [313]. Unfortunately, GM-CSF activates TAM and MDSC as well, thereby supporting tumor growth. These opposing effects are mainly responsible for its only moderate clinical efficacy [316]. Combination therapy is an option to overcome this issue; e.g., co-treatment with recombinant GM-CSF and immune checkpoint inhibitors led to prolonged survival of metastatic melanoma patients [379]. An example for a GM-CSF gene-based approach is the GVAX technology [326,327,328,329]. To this end, allogeneic pancreatic tumor cells have been transfected ex vivo with pDNA encoding GM-CSF. GVAX has been tested in combination with immune checkpoint inhibitors as well as with tumor vaccines. Moreover, oncolytic viruses often encode inter alia for GM-CSF (see Section 5.3). GM-CSF is also addressed in strategies to improve the efficacy and to lower the toxicity of CAR-T cell therapies. However, in contrast to the aforementioned GM-CSF therapy concepts, here GM-CSF is not substituted, but knocked out for example via CRISPR/Cas9 technology [380].
The CXCL12/CXCR4 (C-X-C motif chemokine 12/C-X-C motif chemokine receptor 4) axis plays a crucial role in tumorigenesis, metastasis, and chemoresistance [381,382], and therefore is an ideal target for cancer immunotherapy. However, the toxicity of systemic anti-CXCL12 therapy approaches using small CXCR4 inhibitors like AMD3100 [383] and monoclonal antibodies targeting CXCL12 [384] is a serious issue. Transient and locally restricted expression of antibody-like trap proteins that bind and neutralize CXCL12 constitutes an option to increase systemic tolerability [385,386]. For this purpose, NPs are used for target site-selective delivery of pCXCL12-trap encoding pDNA [18], such as lipid NPs/liposomes [385,386,387].
VEGF is crucial for neoangiogenesis, which is essential for tumor progression and metastasis [388]. Moreover, VEGF contributes to immunosuppression within the TME [389]. Accordingly, several anti-VEGF therapeutics have already been clinically approved, and many pre-/clinical trials are currently carried out evaluating the VEGF trap protein aflibercept [390,391] or monoclonal antibodies that target either VEGF itself (bevacizumab) [392,393] and its receptor VEGFR (ramucirumab) [394] in combination with classical chemotherapeutics or immune checkpoint inhibitors [389,395]. Another potent strategy is RNAi aimed to knock-down VEGF or VEGFR, which showed good anti-tumor results in many preclinical studies. In this regard, CPPs [396,397,398,399], polymers like PEI [400,401,402,403] or chitosan [404], cationic liposomes [405,406], gold [407], and graphene oxide NPs [408], often modified with shielding and targeting units, have been used as delivery systems.
TGF-β exhibits manifold functions regarding cell proliferation, differentiation, migration, and apoptosis [409,410,411]. In the context of cancer progression, an overexpression of TGF-β has been observed within the TME, promoting EMT, immunosuppression, and metastasis. However, these tumor-promoting effects of TGF-β occur only in late-stage tumors, while in early stages its anti-tumor activity is more pronounced. Thus, anti-TGF-β therapy approaches aim to treat advanced cancers. A lot of preclinical and clinical research has been performed in the field of nucleic acid-based strategies ranging from siRNA [412] over miRNA [413,414,415] to antisense oligonucleotides (ASO) [416,417,418,419,420,421]. Belagenpneumatucel-L is an anti-TGF-β allogeneic tumor cell vaccine, based on non-small cell lung cancer cells genetically engineered to express ASO directed against TGF-β [331,332,333]. In a phase III clinical trial, however, no significant increase in the mean overall survival was achieved compared to placebo treatment, but e.g., prior treatment with radiation therapy was found to have a positive effect on therapeutic outcome [333]. Therefore, further investigation in clinical trials is necessary.
In addition to the mediators discussed above, many others can be addressed in immunotherapeutic approaches as well [313,316]. For example, intramuscular IL-27 and intratumoral IFN-α gene delivery via viral vectors promoted Treg depletion in the TME [422,423,424]. This is favorable in view of the efficacy of cancer immunotherapy [425,426], suggesting that both approaches are valuable as adjuvant therapies. Moreover, IFN-α showed strong anti-proliferative, anti-angiogenic, and immunomodulatory activity [427,428]. An IFN-α encoding adenoviral vector (rAdIFNα2b/Syn3, Instiladrin®) has been investigated in advanced clinical trials for intravesical treatment of BCG (Bacillus Calmette–Guerin) unresponsive bladder cancer [330]. Results of a phase III clinical trial that has been completed in 2018 are still pending (NCT02773849).

5.2. Nucleic Acid-Mediated Immune Checkpoint Inhibition and T Cell Stimulation

Immune checkpoints regulate the intensity and the duration of immune responses [429,430]. By this, self-tolerance is preserved, and hence tissue damage is minimized. Tumors often abuse such pathways in order to create an immunosuppressive surrounding, e.g., by anergizing tumor-reactive Teff. Consequently, blockade of immune checkpoints presents a very promising method to restore immunity against the tumor and the TME. Among these CTLA-4 and PD-1 are the best characterized receptors [431,432]. Intensive research led to therapy concepts of immune checkpoint inhibition, which revolutionized treatment especially of advanced cancers [433]. Up to now, several antibodies addressing CTLA-4, PD-1, and its ligand PD-L1 have been implemented in cancer therapy regimens [25,26]. However, response rates are quite low, and relapse often occurs due to resistance development [434,435,436,437,438]. Moreover, immune checkpoint blockade is effective only if the number of tumor-reactive Teff is high enough at the beginning of treatment [434,439,440,441,442]. In this regard, the T cell number in a patient can be increased by ex vivo expansion of TIL that are subsequently reinfused, or by prior treatment with tumor vaccines [438]. Combinations of different immune checkpoint inhibitors as well as their combination with other (immuno)therapeutic approaches aim to overcome the resistance mechanisms [436,437,442].
Other major issues of checkpoint inhibitor therapy are immune-related adverse effects and toxicity [443,444]. Systemic toxicity can be reduced by targeted delivery of checkpoint inhibitors using NPs and by nucleic acid-based approaches [442]. Concerning the latter, mRNA encoding for an anti-CTLA-4 antibody [445], pDNA encoding for PD-L1 traps [386,446,447], siRNA specific for PD-L1 [448,449,450,451,452], and CRISPR/Cas9-mediated knock-out of the PD-1 gene in CAR-T cells [453,454] have been tested so far (Figure 3).
For example, Pruitt et al. electroporated DC ex vivo with mRNA encoding heavy and light chains of blocking antibodies specific for CTLA-4 and glucocorticoid-induced TNFR-related protein [445], which are expressed by Treg at high level [455]. Transfected DC were co-administrated with tumor antigen-transfected DC via subcutaneous injection into B16/F10.9 melanoma bearing C57BL/6 mice [445]. Based on the encouraging results, a phase I clinical trial for treatment of metastatic melanoma has been initiated (NCT01216436).
Transient local expression of PD-L1 trap was pursued by Huang and co-workers [447]. For this purpose, pDNA encoding for PD-L1 trap fusion protein was loaded into lipid-protamine-DNA NPs, consisting of a DNA-protamine core within pre-formed DOTAP-cholesterol liposomes. These were optionally equipped with 1,2-distearoylphosphatidylethanolamine (DSPE)-PEG or DSPE-PEG-AEAA for shielding and targeting. These nano formulations were applied intravenously in combination with intraperitoneally administered oxaliplatin, a chemotherapeutic drug inducing immunogenic cell death and thereby activating DC. By this approach, synergistic effects on tumor inhibition were achieved in a colorectal cancer mouse model.
A further combination approach was conducted by Zhou et al. by combined administration of doxorubicin and of PD-L1-specific siRNA delivered by stimuli-responsive NPs in a B16 melanoma tumor model [452]. These NPs were dually sensitive towards the extracellular slightly acidic pH of tumor cells (pH-triggered detachment of the PEG layer) and their elevated intracellular redox potential (reduction-sensitive polymer core of poly-L-lysine–lipoic acid). This combination therapy was superior to either monotherapy in terms of specificity, efficacy, and tolerability, proving once more the advantage of targeted combination therapies.

5.3. Multi-Faceted Combat of Cancer by Oncolytic Virotherapy

Oncolytic viruses may constitute the next breakthrough in cancer immunotherapy [456]. They comprise DNA and RNA viruses, which can be wild-type (e.g., coxsackie virus, reovirus) or genetically modified (e.g., herpes simplex virus (HSV), adenovirus, vaccinia virus) [457]. Oncolytic viruses selectively replicate in tumor tissue while destroying it [14,458,459,460]. Moreover, they exhibit an immunostimulatory function. Infection and lysis of tumor cells lead to the release of ROS and proinflammatory cytokines as well as danger-associated molecular patterns and intracellular tumor antigens, stimulating both the innate and the adaptive immune system [460]. By this, even immunological memory can be induced, resulting in long-lasting anti-tumor effects [14,461].
In 1991, Martuza et al. succeeded in producing the first genetically modified HSV-1 characterized by a mutation in the thymidine kinase (TK) gene to ensure selective replication only in tumor cells [462]. This pioneer work opened a new way for cancer treatment. The first clinical trial with an oncolytic virus started in mid-1990 [463], followed quickly by many others [464]. However, the clinical efficacy fell short of the expectations, but safety and synergism with standard cancer treatments could be demonstrated [464]. Subsequent generations of oncolytic viruses have been developed by genetic engineering to enhance selectivity and efficiency while maintaining or even improving safety [457,459,465,466] (Figure 4). Tumor selectivity can be enhanced at several levels (transduction, transcription, translation, post-translation) as well as via oncogenic targeting or insertion of miRNA targeting sequences [465,467]. Oncolytic and immunogenic efficacy can be increased by insertion of certain transgenes encoding (i) enzymes that convert pro-drugs to cytotoxic products (e.g., HSV-TK or cytosine deaminase), (ii) immunostimulatory cytokines (e.g., GM-CSF or IL-12), or (iii) TME/ECM-modifying peptides and enzymes (e.g., MMP-9 or the anti-angiogenic peptide angiostatin) [468]. Safety can be ensured by mutations in pathogenic and virulence genes as well as in genes required for viral replication in normal cells [457,468].
Nowadays, a large repertoire of oncolytic viruses is available and oncolytic virotherapy has been intensively investigated in numerous preclinical and clinical studies, also in combination with other cancer therapies like chemotherapy, radiation therapy, or other immunotherapies [456,457,458,459,460,469,470]. Table 2 displays approved oncolytic virotherapies and those that have been or are currently tested in clinical trials.
RIGVIR® was the first oncolytic virus being approved for therapy of melanoma in Latvia in 2004 [471]. This oncolytic virus, enteric cytopathogenic human orphan (ECHO)-7, is a wild-type virus. In 2005, the first genetically modified oncolytic virus (Oncorine®, a recombinant oncolytic adenovirus H101) was approved in China for the treatment of nasopharyngeal carcinoma [474,475]. Ten years later, T-Vec (talminogene laherparepvec) achieved approval by the FDA and the European Medicines Agency (EMA) for treatment of advanced melanoma [477,478]. This oncolytic virus is derived from HSV-1 and was genetically modified to mitigate pathogenicity as well as to increase tumor-selective replication and lysis [478]. In addition, T-Vec expresses GM-CSF to enhance anti-tumor immunity.
Saha et al. conducted a preclinical study with a triple-mutated third generation oncolytic HSV-1 vector (G47Δ-mIL12), in which the murine IL-12 gene was inserted [483]. This oncolytic virus was applied intratumorally, in combination with systemically applied immune checkpoint inhibitors. Only the triple combination of G47Δ-mIL12, anti-CTLA-4, and anti-PD-1 antibodies successfully cured glioblastoma in an immune-competent glioblastoma mouse model.
Other oncolytic DNA viruses that are frequently used are genetically engineered adenovirus and vaccinia viruses [484,485]. CG0070, an oncolytic adenovirus type 5 with an inserted GM-CSF gene, is currently investigated in advanced clinical trials for treatment of non-muscle invasive bladder cancer (BOND, NCT01438112; BOND2, NCT02365818) [456]. The BOND study (phase II/III clinical trial) demonstrated that intravesically applied CG0070 evoked a durable response in a subset of high-risk patients and was well tolerated [476]. An example for an oncolytic vaccinia virus in clinical studies is pexastimogene devacirepvec (Pexa-Vec, JX-594), which bears a mutation in the TK gene for cancer cell targeting and an inserted GM-CSF gene to enhance immune stimulation [456,482,486,487,488]. In a phase III clinical trial, Pexa-Vec is currently evaluated in combination with the multi tyrosine kinase inhibitor sorafenib in patients with advanced hepatocellular carcinoma without prior systemic therapy [482].
Reolysin® (pelareorep) is a wild-type oncolytic RNA virus (type 3 Dearing (T3D) strain reovirus) [457,489], which is extensively studied in clinical trials [456,472]. In phase II and III clinical trials, Reolysin® showed encouraging clinical efficacy, especially in combination with chemotherapeutics (e.g., carboplatin and paclitaxel) in patients with advanced malignancies [472,473].
Despite rapid progress in oncolytic virotherapy and encouraging results in clinical trials, there are still some obstacles [457]. One shortcoming is the small genomic capacity of some oncolytic viruses [460]. Moreover, deletion of pathogenic genes to reduce toxicity might also reduce oncolytic activity [490]. Efficacy may be enhanced for instance by insertion of transgenes or combination with other therapies. In case of the latter, optimal therapy regimens and schedules have to be evaluated in terms of dosage, application routes, and timing [457]. Therefore, further investigations in clinical trials are needed.

5.4. Nucleic Acid-Based TLR Agonists to Boost Anti-Tumor Immune Response

PAMPs and other danger signals are recognized by the innate immune system via pattern recognition receptors such as TLRs [491,492]. Subsequently, pro-inflammatory pathways and the innate immune system are activated to eradicate pathogens. The anti-tumor immune response can be augmented by mimicking PAMPs. Monophosphoryl lipid A, a modified lipopolysaccharide derivative that triggers TLR4, is used as the adjuvant component in the prophylactic cervix cancer vaccine Cervarix® [493]. The successful application of this TLR ligand also reinforced further research in immunostimulatory nucleic acids like double-stranded RNA (dsRNA) or single-stranded DNA (ssDNA) for cancer immunotherapy.
Poly(I:C) is an artificial dsRNA analog that acts as a potent TLR3 agonist [491,494]. Besides enhancement of the anti-tumor immune response, mainly by induction of IFN type I and chemokines especially in immune cells, poly(I:C) also directly induces apoptosis in cancer cells [495,496,497]. However, early clinical trials conducted in the 1970s using poly(I:C) for cancer treatment did not prove any clinical benefit [491,498,499,500], most likely because of its fast degradation prior to cellular uptake [501,502]. Consequently, a stabilized version of poly(I:C), polyriboinosinic:polyribocytidylic acid-polylysine carboxymethylcellulose (poly-ICLC, Hiltonol®), has been developed [502,503]. However, toxicity was a big issue in early rounds of clinical testing, which could be reduced by administration of lower intravenous doses and by local application [491]. Nowadays, poly-ICLC is intensively evaluated in phase I and II clinical trials, especially in combination with cancer vaccines and radiotherapy [491,492,495,504,505]. Another concept to increase the stability and to improve the toxicity profile of TLR3 agonists is the employment of particulate formulations [506]. Shir et al. designed poly(I:C) polyplexes using a polymer conjugate consisting of branched PEI, PEG, EGF for EGFR-targeting, and lytic melittin for improved endosomal escape [507,508]. Complete tumor elimination could be achieved via intratumoral application in three different tumor mouse models (glioblastoma, breast cancer, adenocarcinoma) [507], and in a disseminated EGFR overexpressing tumor mouse model [508]. In the latter study, polyplexes were administered intravenously, followed by intraperitoneal injection of peripheral blood mononuclear cells into tumor bearing immune-deficient SCID mice. Tumor-targeted poly(I:C) mediated induction of chemokines and inflammatory cytokines selectively within the tumor tissue. This led to tumor homing of the injected immune cells as well as a strong anti-tumor and bystander killing effect. The latter might be advantageous in view of the heterogeneous tumor tissue. In this study, complete curation was achieved without adverse side effects [508]. Schaffert et al. optimized the nano-carrier by using linear instead of branched PEI [509]. The improved carrier was effective even without the lytic melittin unit. In a follow-up study, GE11 peptide was used for EGFR targeting [510]. In contrast to EGF, GE11 does not activate EGFR, and thus mitogenic activity of the tumor cells should be much lower. This could be an advantage in terms of clinical use. Other types of poly(I:C) polyplexes were formulated by Lächelt et al. [511] using sequence-defined oligo(ethanamino)amides modified with PEG and the anti-folate drug methotrexate (MTX) with varying degrees of polyglutamylation. MTX exhibits dual function by serving as ligand targeting the folate receptor and by exerting cytotoxic effects in the cytosol. The extent of polyplex uptake as well as MTX and poly(I:C) toxicities correlated with increasing amounts of glutamic acid. A synergism of the combined cytotoxic agents was observed.
CpG ODNs are another class of TLR agonists that imitate bacterial/viral genomic sequences, and are recognized by TLR9 trough their unmethylated cytosine-guanine dinucleotide motif [87,512,513,514]. TLR9 signaling results in the secretion of pro-inflammatory cytokines and the activation of APC and CTL. To improve the in vivo stability of CpG ODNs in most cases the phosphodiester backbone is replaced (at least in part) by a nuclease-resistant phosphorothioate backbone [513,515]. Encouraging results in preclinical studies led to a series of clinical trials in the mid-2000s, testing CpG ODNs alone, in combination with cancer vaccines, or with chemo- and radiotherapy [18,514,515]. However, the clinical outcome fell far short of the hopes and expectations, especially in case of CpG ODN monotherapies, but safety and good tolerability were proven. Subsequent studies showed that TLR9 signaling was negatively influenced at several levels by the immunosuppressive TME [514]. Consequently, CpG ODNs in combination with immune checkpoint inhibitors are currently evaluated in phase I and II clinical trials for treatment of advanced solid tumors like metastatic melanoma [514]. Another dual immunotherapy strategy are conjugates of CpG ODN and either STAT3 siRNA or a STAT3 decoy ODN, respectively [514,516], as STAT3 is an oncogenic transcription factor that interferes with TLR9 signaling. Furthermore, NPs that deliver CpG ODN are under intensive investigation in several preclinical and also some clinical studies [513]. The goal of all these NP-based approaches is to enhance the therapeutic efficacy of CpG ODNs by increasing their stability and protection against nucleases as well as to improve the uptake of CpG ODNs by target cells. In addition, NPs allow to use phosphodiesters instead of the commonly used phosphorothioate backbone [513]. This may improve safety, as phosphorothioates are known to cause various adverse effects, especially in case of systemic application at higher doses [513,514]. By now, several types of NPs have been evaluated for CpG ODN delivery [18,513]. Preclinical studies are conducted inter alia with polymeric NPs formed with polymers like poly(lactic-co-glycolic acid) or PEI [517,518], liposomal formulations [519,520,521], carbon nanotubes [522,523], gold [524,525], and silica mesoporous NPs [526], as well as DNA-based carriers [527,528]. Near-infrared light responsive nanomaterials like copper sulfide, graphene oxide, or gold nanorods can be used for photothermal enhancing of CpG ODN immunogenicity [529,530,531]. Besides these preclinical studies, CpG ODN-loaded virus-like particles are already investigated in a phase I/II clinical trial [532]. Furthermore, CpG ODNs can also be conjugated with antigen (peptide/protein) or human immunodeficiency virus-derived Tat-peptide [533,534]. Self-assembled CpG ODNs like MGN1703 are another example, already tested in phase I and II clinical trials, for treatment of e.g., metastatic colorectal carcinomas [535,536,537].

5.5. Tumor Suppression by RNA Interference

The discovery of RNAi in 1998 [538] led to a better understanding of gene regulation mechanisms [103]. RNAi in humans and animals is mediated by miRNA [539] (Figure 2). miRNAs influence many cellular functions like proliferation, differentiation, apoptosis, oncogenesis, and drug sensitivity [540,541,542,543]. Dysregulated miRNA expression is associated with the development and progress of various diseases [539,543,544]. Calin et al. were the first to report involvement of miRNA in cancer progression [545]. miRNAs can be used as diagnostic and prognostic biomarkers [546]. For cancer therapy, oncogenic miRNAs can be blocked by antisense molecules (antagomirs), while attenuated levels of tumor suppressor miRNAs can be substituted by pre-miRNAs or miRNA mimics [539,543,547,548].
The major challenge in clinical translation of miRNA therapeutics is to ensure their efficient, specific, and safe delivery to the tumor [539,543,546,549]. Chemical modifications can increase resistance of RNA to enzymatic degradation by nucleases. Examples for such structural alterations are modifications of the ribose 2′-OH group, the use of phosphorothioate instead of phosphodiester bonds, peptide nucleic acids, locked nucleic acids as well as conjugation with other moieties (e.g., cholesterol, antibodies, or membrane translocation peptides) [103,539,550,551,552].
For example, Cheng et al. conjugated peptide nucleic acid-based anti-miR-155 to a pH-sensitive membrane translocation peptide via a disulfide link [103,552]. In the acidic tumor tissue, the conformational change in this peptide promoted internalization of the antagomir, which was released intracellularly upon disulfide cleavage due to increased glutathione levels. In a lymphoma model, cell targeting, a significant inhibition of lymphoma proliferation as well as a good tolerability were demonstrated. It is also worth noting that the neutral charge of the peptide nucleic acid was decisive for success.
Viral as well as non-viral delivery systems such as liposomal or polymeric NPs are under investigation to prevent degradation of miRNA and to promote their targeted delivery [539,546,551]. Loss of miR-200c expression is known to promote tumorigenic processes like tumor cell proliferation, EMT, migration, and chemoresistance [539,553,554,555,556,557,558]. Müller et al. tested a cationic oligo(ethanamino)amide structure with T-shape topology, terminal cysteines, and a dioleyl motif, post-functionalized with PEG-GE11 for shielding and EGFR targeting for delivery of a mimic of the tumor suppressor miR-200c [559]. In two different human tumor cell lines, these EGFR-targeting miRNA polyplexes conferred selective, enhanced delivery of miRNA-200c, leading to various anti-tumor effects, including decreased tumor cell proliferation and migration, and enhanced sensitivity towards doxorubicin.
Altogether, miRNA therapeutics hold great potential for efficient and safe cancer treatment, especially as multi-functional nano formulations, paving the way towards clinical translation. A liposomal formulation of miR-34a mimic (MRX34) for treatment of patients with advanced solid tumors was the first miRNA therapeutic entering phase I clinical studies in 2013, but was accompanied by severe immune-mediated adverse effects (NCT01829971) [560,561]. Nevertheless, the observed dose-dependent modulation of relevant target gene expression provided a proof-of-concept for miRNA-based cancer therapy [561]. This raises hope that miRNA therapeutics will make the leap towards clinical application. Therefore, further optimization of cargo and delivery systems to improve clinical efficacy and toxicity profiles is necessary.

6. Conclusions

Until a few years ago, nucleic acid-based immunotherapeutics have proven successful in preclinical studies, but largely fell short of expectations when evaluated for therapeutic efficacy in clinical trials [57,61]. One major limit has been the lack of appropriate delivery systems required to prevent degradation of pDNA/mRNA, and to enable cell type-specific delivery [125,126]. Insofar, it is not surprising that by now virus-based gene therapies including oncolytic viruses [471,474,475,477,478], and cell-based immunotherapeutics, namely CAR-T cell therapies [28,277,562,563,564], demonstrated more successful for tumor therapy, and have been approved for clinical treatment. However, in the last years, the development of biocompatible, cell targeting NPs, especially of liposomal carriers [565], has strongly improved the efficacy of e.g., mRNA-based anti-tumor vaccines [71,72]. Additionally, in case of CAR-T as an ex vivo gene therapy approach non-viral delivery is currently tested [566]. These developments, in combination with structural improvements in particular of gene encoding pDNA [567], and the proper choice of individual tumor-specific neoantigens for individualized vaccination [79], are important factors to overcome the low therapeutic efficacy of most nucleic acid immunotherapeutics tested so far. Furthermore, as numerous clinical trials have repetitively shown, nucleic acid-based therapeutics were more efficient when co-applied with agents that act on other levels like immune checkpoint inhibitors [70,79] or chemotherapeutics [474], and radiotherapy [568]. Moreover, first preclinical studies have shown that also different kinds of nucleic acids that act on distinct levels of cancer treatment may be combined to yield synergistic effects. For example, co-administration of the adjuvant poly(I:C) enhanced the anti-tumor efficacy of CAR-T cells [569]. Similarly, co-application of an oncolytic adenovirus and of CAR-T cells improved anti-tumor responses as compared to monotherapy [570].
Altogether, ongoing developments indicate that nucleic acid-based therapeutics will become essential tools for successful tumor therapy as part of combination therapies, comprising the induction of tumor antigen-specific immune reactions [79], the enhancement of anti-tumor responses [514], the inhibition or reprograming of regulatory immune cells [256], the generation of tumor killing immune cells (CAR) [284], and direct killing of tumor cells [482]. The versatility of nucleic acids as a therapeutic mean is underscored by the fact that these can exert either of the aforementioned functions by serving as gene expression units in pDNA/mRNA vaccines, conferring RNAi (siRNA, miRNA), and adjuvant activity (e.g., CpG ODN), and can be easily produced under GMP conditions [571]. Therefore, it is conceivable that in the future nucleic acid-based therapeutics that act on different levels of cancer treatment will be part of combination therapies involving either also conventional therapeutics or distinct types of nucleic acids.

Author Contributions

Each author has substantially contributed to drafting this review. S.H., E.W. and M.B. conceptualized the review topic. S.H., F.J.F., E.W., and M.B. wrote the manuscript draft and S.H., E.W., and M.B. revised it. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Deutsche Forschungsgemeinschaft (SFB1066, project B05).

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

A2AR: adenosine A2A receptor; ALL: acute lymphoblastic leukemia; AML: acute myeloid leukemia; APC: antigen presenting cell; ASO: antisense oligonucleotide; AVET: adenovirus-enhanced transferrinfection; CAR: chimeric antigen receptor; BCG: Bacillus Calmette–Guerin; CAF: cancer-associated fibroblast; cAMP: cyclic adenosine monophosphate; CCL: C-C motif chemokine ligand; CLL: chronic lymphocytic leukemia; CLR: C-type lectin receptor; CPP: cell penetrating peptide; CEA: carcinoembryonic antigen; CSC: cancer stem cell; CTL: cytotoxic T lymphocyte; CTLA-4: CTL-associated protein 4; CXCL12: C-X-C motif chemokine 12; CXCR4: C-X-C motif chemokine receptor 4; DC: dendritic cell; DOPE: dioleoyl phosphatidylethanolamine; DOTAP: N-[1-(2,3-dioleoyloxy)propyl]-N,N,N-trimethylammonium chloride; DOTMA: 1,2-di-O-octadecenyl-3-trimethylammonium propane; DSPE: distearoylphosphatidylethanolamine; dsRNA: double-stranded RNA; ECHO-7: enteric cytopathogenic human orphan 7; ECM: extracellular matrix; EGFR: epidermal growth factor receptor; EMA: European Medicines Agency; EMT: epithelial–mesenchymal transition; ENO1: α-enolase; EPR: enhanced permeation and retention; FDA: united states food and drug administration; GM-CSF: granulocyte macrophage colony-stimulating factor; HD: hexanediol diacrylate; HSV: herpes simplex virus; IFN-α: interferon alpha; IL: interleukin; IRAK1: IL-1 receptor-associated kinase; JNK: c-Jun N-terminal kinase; KC: Kupffer cell; mcDNA: mini-circle DNA; LAMP: lysosomal-associated membrane protein; LSEC: liver sinusoidal endothelial cell; MHC: major histocompatibility complex; MDSC: myeloid-derived suppressor cell; MMP: matrix metalloprotease; MTX: methotrexate; NK: natural killer cell; NLS: nuclear localization signal; NP: nanoparticle; NHL: non-Hodgkin lymphoma; ODN: oligodeoxynucleotides; OEI: oligoethylenimine; PD-1: programmed cell death protein 1; PD-L1: PD ligand 1; PEG: polyethylene glycol; PEI: polyethylenimine; Pexa-Vec: pexastimogene devacirepvec; PLGA: poly-D,L-lactic-co-glycolic acid; Poly(I:C): polyriboinosinic:polyribocytidylic acid; poly-ICLC: polyriboinosinic:polyribocytidylic acid-polylysine carboxymethylcellulose; RNAi: RNA interference; ROS: reactive oxygen species; SCF: stem cell factor; scFv: single chain fragment variable; ssDNA: single-stranded DNA; STAT: signal transducer and activator of transcription; STING: stimulator of IFN genes; SV40: simian virus 40; T-Vec: talminogene laherparepvec; T3D: type 3 Dearing; TAA: tumor-associated antigen; TAM: tumor-associated macrophage; TCR: T cell receptor; Teff: effector T cell; TGF-β: transforming growth factor beta; Th: T helper cell; TIL: tumor-infiltrating lymphocyte; TK: thymidine kinase; TLR: toll-like receptor; TNF-α: tumor necrosis factor alpha; TRAF6: tumor necrosis factor receptor-associated factor 6; Treg: regulatory T cell; iTreg: induced Treg; tTreg: thymic Treg; VEGF: vascular endothelial growth factor; VEGFR: VEGF receptor; WT1: Wilms’ tumor 1.

References

  1. Siegel, R.L.; Miller, K.D.; Jemal, A. Cancer statistics, 2019. CA Cancer J. Clin. 2019, 69, 7–34. [Google Scholar] [CrossRef] [Green Version]
  2. Think globally about cancer. Nat. Med. 2019, 25, 351. [CrossRef] [PubMed] [Green Version]
  3. Ferlay, J.; Colombet, M.; Soerjomataram, I.; Mathers, C.; Parkin, D.M.; Piñeros, M.; Znaor, A.; Bray, F. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int. J. Cancer 2019, 144, 1941–1953. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Ferlay, J.; Colombet, M.; Soerjomataram, I.; Dyba, T.; Randi, G.; Bettio, M.; Gavin, A.; Visser, O.; Bray, F. Cancer incidence and mortality patterns in Europe: Estimates for 40 countries and 25 major cancers in 2018. Eur. J. Cancer 2018, 103, 356–387. [Google Scholar] [CrossRef]
  5. Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Zheng, H.C. The molecular mechanisms of chemoresistance in cancers. Oncotarget 2017, 8, 59950–59964. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Liu, Q.; Zhang, H.; Jiang, X.; Qian, C.; Liu, Z.; Luo, D. Factors involved in cancer metastasis: A better understanding to “seed and soil” hypothesis. Mol. Cancer 2017, 16, 176. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Schirrmacher, V. From chemotherapy to biological therapy: A review of novel concepts to reduce the side effects of systemic cancer treatment (Review). Int. J. Oncol. 2019, 54, 407–419. [Google Scholar] [CrossRef]
  9. Rosenberg, S.A. A New Era for Cancer Immunotherapy Based on the Genes that Encode Cancer Antigens. Immunity 1999, 10, 281–287. [Google Scholar] [CrossRef] [Green Version]
  10. Zugazagoitia, J.; Guedes, C.; Ponce, S.; Ferrer, I.; Molina-Pinelo, S.; Paz-Ares, L. Current Challenges in Cancer Treatment. Clin. Ther. 2016, 38, 1551–1566. [Google Scholar] [CrossRef] [Green Version]
  11. Tariman, J.D. Changes in Cancer Treatment: Mabs, Mibs, Mids, Nabs, and Nibs. Nurs. Clin. North Am. 2017, 52, 65–81. [Google Scholar] [CrossRef] [PubMed]
  12. Farkona, S.; Diamandis, E.P.; Blasutig, I.M. Cancer immunotherapy: The beginning of the end of cancer? BMC Med. 2016, 14, 73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Saleh, T.; Shojaosadati, S.A. Multifunctional nanoparticles for cancer immunotherapy. Hum. Vaccin. Immunother. 2016, 12, 1863–1875. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Sami, H.; Ogris, M. Biopharmaceuticals and gene vectors opening new avenues in cancer immune therapy. Ther. Deliv. 2016, 7, 419–422. [Google Scholar] [CrossRef] [Green Version]
  15. Emens, L.A.; Ascierto, P.A.; Darcy, P.K.; Demaria, S.; Eggermont, A.M.M.; Redmond, W.L.; Seliger, B.; Marincola, F.M. Cancer immunotherapy: Opportunities and challenges in the rapidly evolving clinical landscape. Eur. J. Cancer 2017, 81, 116–129. [Google Scholar] [CrossRef]
  16. Rangel-Sosa, M.M.; Aguilar-Córdova, E.; Rojas-Martínez, A. Immunotherapy and gene therapy as novel treatments for cancer. Colomb. Med. (Cali) 2017, 48, 138–147. [Google Scholar] [CrossRef] [Green Version]
  17. Song, W.; Musetti, S.N.; Huang, L. Nanomaterials for cancer immunotherapy. Biomaterials 2017, 148, 16–30. [Google Scholar] [CrossRef]
  18. Musetti, S.; Huang, L. Nanoparticle-Mediated Remodeling of the Tumor Microenvironment to Enhance Immunotherapy. ACS Nano 2018, 12, 11740–11755. [Google Scholar] [CrossRef]
  19. Sau, S.; Alsaab, H.O.; Bhise, K.; Alzhrani, R.; Nabil, G.; Iyer, A.K. Multifunctional nanoparticles for cancer immunotherapy: A groundbreaking approach for reprogramming malfunctioned tumor environment. J. Controlled Release 2018, 274, 24–34. [Google Scholar] [CrossRef]
  20. Bai, Y.; Wang, Y.; Zhang, X.; Fu, J.; Xing, X.; Wang, C.; Gao, L.; Liu, Y.; Shi, L. Potential applications of nanoparticles for tumor microenvironment remodeling to ameliorate cancer immunotherapy. Int. J. Pharm. 2019, 570, 118636. [Google Scholar] [CrossRef]
  21. Luo, Q.; Zhang, L.; Luo, C.; Jiang, M. Emerging strategies in cancer therapy combining chemotherapy with immunotherapy. Cancer Lett. 2019, 454, 191–203. [Google Scholar] [CrossRef] [PubMed]
  22. Salvioni, L.; Rizzuto, A.M.; Bertolini, A.J.; Pandolfi, L.; Colombo, M.; Prosperi, D. Thirty Years of Cancer Nanomedicine: Success, Frustration, and Hope. Cancers 2019, 11, 1855. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Shi, Y.; Lammers, T. Combining Nanomedicine and Immunotherapy. Acc. Chem. Res. 2019, 52, 1543–1554. [Google Scholar] [CrossRef] [PubMed]
  24. Sun, W.; Shi, Q.; Zhang, H.; Yang, K.; Ke, Y.; Wang, Y.; Qiao, L. Advances in the techniques and methodologies of cancer gene therapy. Discov. Med. 2019, 27, 45–55. [Google Scholar] [PubMed]
  25. Hargadon, K.M.; Johnson, C.E.; Williams, C.J. Immune checkpoint blockade therapy for cancer: An overview of FDA-approved immune checkpoint inhibitors. Int. Immunopharmacol. 2018, 62, 29–39. [Google Scholar] [CrossRef]
  26. Wilky, B.A. Immune checkpoint inhibitors: The linchpins of modern immunotherapy. Immunol. Rev. 2019, 290, 6–23. [Google Scholar] [CrossRef]
  27. Chen, Q.; Wang, C.; Chen, G.; Hu, Q.; Gu, Z. Delivery Strategies for Immune Checkpoint Blockade. Adv. Healthc. Mater. 2018, 7, e1800424. [Google Scholar] [CrossRef]
  28. Sermer, D.; Brentjens, R. CAR T-cell therapy: Full speed ahead. Hematol. Oncol. 2019, 37, 95–100. [Google Scholar] [CrossRef] [Green Version]
  29. Shah, N.N.; Fry, T.J. Mechanisms of resistance to CAR T cell therapy. Nat. Rev. Clin. Oncol. 2019, 16, 372–385. [Google Scholar] [CrossRef]
  30. Ginn, S.L.; Amaya, A.K.; Alexander, I.E.; Edelstein, M.; Abedi, M.R. Gene therapy clinical trials worldwide to 2017: An update. J. Gene Med. 2018, 20, e3015. [Google Scholar] [CrossRef]
  31. Hobernik, D.; Bros, M. DNA Vaccines—How Far From Clinical Use? Int. J. Mol. Sci. 2018, 19, 3605. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Nabel, G.J.; Nabel, E.G.; Yang, Z.Y.; Fox, B.A.; Plautz, G.E.; Gao, X.; Huang, L.; Shu, S.; Gordon, D.; Chang, A.E. Direct gene transfer with DNA-liposome complexes in melanoma: Expression, biologic activity, and lack of toxicity in humans. Proc. Natl. Acad. Sci. 1993, 90, 11307. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Goldberg, M.S. Improving cancer immunotherapy through nanotechnology. Nat. Rev. Cancer 2019, 19, 587–602. [Google Scholar] [CrossRef]
  34. Shae, D.; Baljon, J.J.; Wehbe, M.; Becker, K.W.; Sheehy, T.L.; Wilson, J.T. At the bench: Engineering the next generation of cancer vaccines. J. Leukoc. Biol. 2019. [Google Scholar] [CrossRef] [PubMed]
  35. Sadeghzadeh, M.; Bornehdeli, S.; Mohahammadrezakhani, H.; Abolghasemi, M.; Poursaei, E.; Asadi, M.; Zafari, V.; Aghebati-Maleki, L.; Shanehbandi, D. Dendritic cell therapy in cancer treatment; The state-of-the-art. Life Sci. 2020, 254, 117580. [Google Scholar] [CrossRef] [PubMed]
  36. Bastola, R.; Noh, G.; Keum, T.; Bashyal, S.; Seo, J.E.; Choi, J.; Oh, Y.; Cho, Y.; Lee, S. Vaccine adjuvants: Smart components to boost the immune system. Arch. Pharm. Res. 2017, 40, 1238–1248. [Google Scholar] [CrossRef]
  37. Marino, M.; Scuderi, F.; Provenzano, C.; Bartoccioni, E. Skeletal muscle cells: From local inflammatory response to active immunity. Gene ther. 2011, 18, 109–116. [Google Scholar] [CrossRef] [Green Version]
  38. Hengge, U.R.; Chan, E.F.; Foster, R.A.; Walker, P.S.; Vogel, J.C. Cytokine gene expression in epidermis with biological effects following injection of naked DNA. Nat. Genet. 1995, 10, 161–166. [Google Scholar] [CrossRef]
  39. Oh, S.; Kessler, J.A. Design, Assembly, Production, and Transfection of Synthetic Modified mRNA. Methods 2018, 133, 29–43. [Google Scholar] [CrossRef]
  40. Bai, H.; Lester, G.M.S.; Petishnok, L.C.; Dean, D.A. Cytoplasmic transport and nuclear import of plasmid DNA. Biosci. Rep. 2017, 37. [Google Scholar] [CrossRef]
  41. Lazzaro, S.; Giovani, C.; Mangiavacchi, S.; Magini, D.; Maione, D.; Baudner, B.; Geall, A.J.; De Gregorio, E.; D’Oro, U.; Buonsanti, C. CD8 T-cell priming upon mRNA vaccination is restricted to bone-marrow-derived antigen-presenting cells and may involve antigen transfer from myocytes. Immunology 2015, 146, 312–326. [Google Scholar] [CrossRef] [PubMed]
  42. Sudowe, S.; Dominitzki, S.; Montermann, E.; Bros, M.; Grabbe, S.; Reske-Kunz, A.B. Uptake and presentation of exogenous antigen and presentation of endogenously produced antigen by skin dendritic cells represent equivalent pathways for the priming of cellular immune responses following biolistic DNA immunization. Immunology 2009, 128, e193–e205. [Google Scholar] [CrossRef] [PubMed]
  43. Li, Q.; Wang, H.; Peng, H.; Huyan, T.; Cacalano, N.A. Exosomes: Versatile Nano Mediators of Immune Regulation. Cancers 2019, 11, 1557. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Chen, Z.; Larregina, A.T.; Morelli, A.E. Impact of extracellular vesicles on innate immunity. Curr. Opin. Organ. Transplant. 2019, 24, 670–678. [Google Scholar] [CrossRef]
  45. Den Haan, J.M.; Arens, R.; van Zelm, M.C. The activation of the adaptive immune system: Cross-talk between antigen-presenting cells, T cells and B cells. Immunol. Lett. 2014, 162, 103–112. [Google Scholar] [CrossRef]
  46. Macri, C.; Dumont, C.; Johnston, A.P.; Mintern, J.D. Targeting dendritic cells: A promising strategy to improve vaccine effectiveness. Clin. Transl. Immunol. 2016, 5, e66. [Google Scholar] [CrossRef] [Green Version]
  47. Porgador, A.; Irvine, K.R.; Iwasaki, A.; Barber, B.H.; Restifo, N.P.; Germain, R.N. Predominant role for directly transfected dendritic cells in antigen presentation to CD8+ T cells after gene gun immunization. J. Exp. Med. 1998, 188, 1075–1082. [Google Scholar] [CrossRef]
  48. Coban, C.; Kobiyama, K.; Jounai, N.; Tozuka, M.; Ishii, K.J. DNA vaccines: A simple DNA sensing matter? Hum. Vaccin. Immunother. 2013, 9, 2216–2221. [Google Scholar] [CrossRef] [Green Version]
  49. Joffre, O.; Nolte, M.A.; Sporri, R.; Reis e Sousa, C. Inflammatory signals in dendritic cell activation and the induction of adaptive immunity. Immunol. Rev. 2009, 227, 234–247. [Google Scholar] [CrossRef]
  50. Maecker, H.T.; Umetsu, D.T.; DeKruyff, R.H.; Levy, S. Cytotoxic T cell responses to DNA vaccination: Dependence on antigen presentation via class II MHC. J. Immunol. (Baltimore, Md.: 1950) 1998, 161, 6532–6536. [Google Scholar]
  51. Aloulou, M.; Fazilleau, N. Regulation of B cell responses by distinct populations of CD4 T cells. Biomed. J. 2019, 42, 243–251. [Google Scholar] [CrossRef]
  52. Fu, S.H.; Chien, M.W.; Hsu, C.Y.; Liu, Y.W.; Sytwu, H.K. Interplay between Cytokine Circuitry and Transcriptional Regulation Shaping Helper T Cell Pathogenicity and Plasticity in Inflammatory Bowel Disease. Int. J. Mol. Sci. 2020, 21, 3379. [Google Scholar] [CrossRef] [PubMed]
  53. Farhood, B.; Najafi, M.; Mortezaee, K. CD8(+) cytotoxic T lymphocytes in cancer immunotherapy: A review. J. Cell. Physiol. 2019, 234, 8509–8521. [Google Scholar] [CrossRef]
  54. Tagawa, S.T.; Lee, P.; Snively, J.; Boswell, W.; Ounpraseuth, S.; Lee, S.; Hickingbottom, B.; Smith, J.; Johnson, D.; Weber, J.S. Phase I study of intranodal delivery of a plasmid DNA vaccine for patients with Stage IV melanoma. Cancer 2003, 98, 144–154. [Google Scholar] [CrossRef]
  55. Proudfoot, O.; Apostolopoulos, V.; Pietersz, G.A. Receptor-mediated delivery of antigens to dendritic cells: Anticancer applications. Mol. Pharm. 2007, 4, 58–72. [Google Scholar] [CrossRef] [PubMed]
  56. Steele, J.C.; Rao, A.; Marsden, J.R.; Armstrong, C.J.; Berhane, S.; Billingham, L.J.; Graham, N.; Roberts, C.; Ryan, G.; Uppal, H.; et al. Phase I/II trial of a dendritic cell vaccine transfected with DNA encoding melan A and gp100 for patients with metastatic melanoma. Gene Ther. 2011, 18, 584–593. [Google Scholar] [CrossRef] [Green Version]
  57. Lopes, A.; Vandermeulen, G.; Préat, V. Cancer DNA vaccines: Current preclinical and clinical developments and future perspectives. J.Exp. Clin. Cancer Res. 2019, 38, 146. [Google Scholar] [CrossRef]
  58. McCann, K.J.; Mander, A.; Cazaly, A.; Chudley, L.; Stasakova, J.; Thirdborough, S.; King, A.; Lloyd-Evans, P.; Buxton, E.; Edwards, C.; et al. Targeting Carcinoembryonic Antigen with DNA Vaccination: On-Target Adverse Events Link with Immunologic and Clinical Outcomes. Clin. Cancer Res. 2016, 22, 4827–4836. [Google Scholar] [CrossRef] [Green Version]
  59. McNeel, D.G.; Eickhoff, J.C.; Wargowski, E.; Zahm, C.; Staab, M.J.; Straus, J.; Liu, G. Concurrent, but not sequential, PD-1 blockade with a DNA vaccine elicits anti-tumor responses in patients with metastatic, castration-resistant prostate cancer. Oncotarget 2018, 9, 25586–25596. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  60. Tosch, C.; Bastien, B.; Barraud, L.; Grellier, B.; Nourtier, V.; Gantzer, M.; Limacher, J.M.; Quemeneur, E.; Bendjama, K.; Préville, X. Viral based vaccine TG4010 induces broadening of specific immune response and improves outcome in advanced NSCLC. J. Immunother. Cancer 2017, 5, 70. [Google Scholar] [CrossRef]
  61. Dörrie, J.; Schaft, N.; Schuler, G.; Schuler-Thurner, B. Therapeutic Cancer Vaccination with Ex Vivo RNA-Transfected Dendritic Cells-An Update. Pharmaceutics 2020, 12, 92. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Van Tendeloo, V.F.; Van de Velde, A.; Van Driessche, A.; Cools, N.; Anguille, S.; Ladell, K.; Gostick, E.; Vermeulen, K.; Pieters, K.; Nijs, G.; et al. Induction of complete and molecular remissions in acute myeloid leukemia by Wilms’ tumor 1 antigen-targeted dendritic cell vaccination. Proc. Natl. Acad. Sci. USA 2010, 107, 13824–13829. [Google Scholar] [CrossRef] [Green Version]
  63. Anguille, S.; Van de Velde, A.L.; Smits, E.L.; Van Tendeloo, V.F.; Juliusson, G.; Cools, N.; Nijs, G.; Stein, B.; Lion, E.; Van Driessche, A.; et al. Dendritic cell vaccination as postremission treatment to prevent or delay relapse in acute myeloid leukemia. Blood 2017, 130, 1713–1721. [Google Scholar] [CrossRef] [Green Version]
  64. Su, Z.; Vieweg, J.; Weizer, A.Z.; Dahm, P.; Yancey, D.; Turaga, V.; Higgins, J.; Boczkowski, D.; Gilboa, E.; Dannull, J. Enhanced induction of telomerase-specific CD4(+) T cells using dendritic cells transfected with RNA encoding a chimeric gene product. Cancer Res. 2002, 62, 5041–5048. [Google Scholar] [PubMed]
  65. Khoury, H.J.; Collins, R.H., Jr.; Blum, W.; Stiff, P.S.; Elias, L.; Lebkowski, J.S.; Reddy, A.; Nishimoto, K.P.; Sen, D.; Wirth, E.D., III; et al. Immune responses and long-term disease recurrence status after telomerase-based dendritic cell immunotherapy in patients with acute myeloid leukemia. Cancer 2017, 123, 3061–3072. [Google Scholar] [CrossRef] [Green Version]
  66. Vik-Mo, E.O.; Nyakas, M.; Mikkelsen, B.V.; Moe, M.C.; Due-Tønnesen, P.; Suso, E.M.; Sæbøe-Larssen, S.; Sandberg, C.; Brinchmann, J.E.; Helseth, E.; et al. Therapeutic vaccination against autologous cancer stem cells with mRNA-transfected dendritic cells in patients with glioblastoma. Cancer Immunol. Immunother. 2013, 62, 1499–1509. [Google Scholar] [CrossRef] [Green Version]
  67. Batich, K.A.; Reap, E.A.; Archer, G.E.; Sanchez-Perez, L.; Nair, S.K.; Schmittling, R.J.; Norberg, P.; Xie, W.; Herndon, J.E., II; Healy, P.; et al. Long-term Survival in Glioblastoma with Cytomegalovirus pp65-Targeted Vaccination. Clin. Cancer Res. 2017, 23, 1898–1909. [Google Scholar] [CrossRef] [Green Version]
  68. Rahman, M.; Dastmalchi, F.; Karachi, A.; Mitchell, D. The role of CMV in glioblastoma and implications for immunotherapeutic strategies. Oncoimmunology 2019, 8, e1514921. [Google Scholar] [CrossRef] [PubMed]
  69. Wilgenhof, S.; Corthals, J.; Van Nuffel, A.M.; Benteyn, D.; Heirman, C.; Bonehill, A.; Thielemans, K.; Neyns, B. Long-term clinical outcome of melanoma patients treated with messenger RNA-electroporated dendritic cell therapy following complete resection of metastases. Cancer Immunol. Immunother. 2015, 64, 381–388. [Google Scholar] [CrossRef]
  70. Wilgenhof, S.; Corthals, J.; Heirman, C.; van Baren, N.; Lucas, S.; Kvistborg, P.; Thielemans, K.; Neyns, B. Phase II Study of Autologous Monocyte-Derived mRNA Electroporated Dendritic Cells (TriMixDC-MEL) Plus Ipilimumab in Patients With Pretreated Advanced Melanoma. J. Clin. Oncol. 2016, 34, 1330–1338. [Google Scholar] [CrossRef] [PubMed]
  71. Grabbe, S.; Haas, H.; Diken, M.; Kranz, L.M.; Langguth, P.; Sahin, U. Translating nanoparticulate-personalized cancer vaccines into clinical applications: Case study with RNA-lipoplexes for the treatment of melanoma. Nanomedicine (London, England) 2016, 11, 2723–2734. [Google Scholar] [CrossRef] [PubMed]
  72. Kranz, L.M.; Diken, M.; Haas, H.; Kreiter, S.; Loquai, C.; Reuter, K.C.; Meng, M.; Fritz, D.; Vascotto, F.; Hefesha, H.; et al. Systemic RNA delivery to dendritic cells exploits antiviral defence for cancer immunotherapy. Nature 2016, 534, 396–401. [Google Scholar] [CrossRef] [PubMed]
  73. Nazarkina Zh, K.; Khar’kova, M.V.; Antonets, D.V.; Morozkin, E.S.; Bazhan, S.I.; Karpenko, L.I.; Vlasov, V.V.; Ilyichev, A.A.; Laktionov, P.P. Design of Polyepitope DNA Vaccine against Breast Carcinoma Cells and Analysis of Its Expression in Dendritic Cells. Bull. Exp. Biol. Med. 2016, 160, 486–490. [Google Scholar] [CrossRef] [PubMed]
  74. Hirayama, M.; Nishimura, Y. The present status and future prospects of peptide-based cancer vaccines. Int. Immunol. 2016, 28, 319–328. [Google Scholar] [CrossRef] [PubMed]
  75. Brennick, C.A.; George, M.M.; Corwin, W.L.; Srivastava, P.K.; Ebrahimi-Nik, H. Neoepitopes as cancer immunotherapy targets: Key challenges and opportunities. Immunotherapy 2017, 9, 361–371. [Google Scholar] [CrossRef] [Green Version]
  76. Kiyotani, K.; Chan, H.T.; Nakamura, Y. Immunopharmacogenomics towards personalized cancer immunotherapy targeting neoantigens. Cancer Sci. 2018, 109, 542–549. [Google Scholar] [CrossRef] [Green Version]
  77. Sultan, H.; Trillo-Tinoco, J.; Rodriguez, P.; Celis, E. Effective antitumor peptide vaccines can induce severe autoimmune pathology. Oncotarget 2017, 8, 70317–70331. [Google Scholar] [CrossRef] [Green Version]
  78. Lu, Y.C.; Yao, X.; Crystal, J.S.; Li, Y.F.; El-Gamil, M.; Gross, C.; Davis, L.; Dudley, M.E.; Yang, J.C.; Samuels, Y.; et al. Efficient identification of mutated cancer antigens recognized by T cells associated with durable tumor regressions. Clin. Cancer Res. 2014, 20, 3401–3410. [Google Scholar] [CrossRef] [Green Version]
  79. Sahin, U.; Derhovanessian, E.; Miller, M.; Kloke, B.P.; Simon, P.; Löwer, M.; Bukur, V.; Tadmor, A.D.; Luxemburger, U.; Schrörs, B.; et al. Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature 2017, 547, 222–226. [Google Scholar] [CrossRef]
  80. Bins, A.D.; Wolkers, M.C.; van den Boom, M.D.; Haanen, J.B.; Schumacher, T.N. In vivo antigen stability affects DNA vaccine immunogenicity. J. Immunol. (Baltimore, Md.: 1950) 2007, 179, 2126–2133. [Google Scholar] [CrossRef] [PubMed]
  81. Hoppes, R.; Oostvogels, R.; Luimstra, J.J.; Wals, K.; Toebes, M.; Bies, L.; Ekkebus, R.; Rijal, P.; Celie, P.H.; Huang, J.H.; et al. Altered peptide ligands revisited: Vaccine design through chemically modified HLA-A2-restricted T cell epitopes. J. Immunol. 2014, 193, 4803–4813. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  82. Seledtsova, G.V.; Shishkov, A.A.; Kaschenko, E.A.; Goncharov, A.G.; Gazatova, N.D.; Seledtsov, V.I. Xenogeneic cell-based vaccine therapy for stage III melanoma: Safety, immune-mediated responses and survival benefits. Eur. J. Dermatol. 2016, 26, 138–143. [Google Scholar] [CrossRef]
  83. Sponaas, A.; Carstens, C.; Koch, N. C-terminal extension of the MHC class II-associated invariant chain by an antigenic sequence triggers activation of naive T cells. Gene Ther. 1999, 6, 1826–1834. [Google Scholar] [CrossRef] [PubMed]
  84. Tudor, D.; Dubuquoy, C.; Gaboriau, V.; Lefevre, F.; Charley, B.; Riffault, S. TLR9 pathway is involved in adjuvant effects of plasmid DNA-based vaccines. Vaccine 2005, 23, 1258–1264. [Google Scholar] [CrossRef] [PubMed]
  85. Suschak, J.J.; Wang, S.; Fitzgerald, K.A.; Lu, S. A cGAS-Independent STING/IRF7 Pathway Mediates the Immunogenicity of DNA Vaccines. J. Immunol. 2016, 196, 310–316. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  86. Larregina, A.T.; Watkins, S.C.; Erdos, G.; Spencer, L.A.; Storkus, W.J.; Beer Stolz, D.; Falo, L.D., Jr. Direct transfection and activation of human cutaneous dendritic cells. Gene Ther. 2001, 8, 608–617. [Google Scholar] [CrossRef] [Green Version]
  87. Hemmi, H.; Takeuchi, O.; Kawai, T.; Kaisho, T.; Sato, S.; Sanjo, H.; Matsumoto, M.; Hoshino, K.; Wagner, H.; Takeda, K.; et al. A Toll-like receptor recognizes bacterial DNA. Nature 2000, 408, 740–745. [Google Scholar] [CrossRef]
  88. Scheiermann, J.; Klinman, D.M. Clinical evaluation of CpG oligonucleotides as adjuvants for vaccines targeting infectious diseases and cancer. Vaccine 2014, 32, 6377–6389. [Google Scholar] [CrossRef] [Green Version]
  89. Garg, R.; Kaur, M.; Saxena, A.; Prasad, R.; Bhatnagar, R. Alum adjuvanted rabies DNA vaccine confers 80% protection against lethal 50 LD50 rabies challenge virus standard strain. Mol. Immunol. 2017, 85, 166–173. [Google Scholar] [CrossRef]
  90. Shedlock, D.J.; Tingey, C.; Mahadevan, L.; Hutnick, N.; Reuschel, E.L.; Kudchodkar, S.; Flingai, S.; Yan, J.; Kim, J.J.; Ugen, K.E.; et al. Co-Administration of Molecular Adjuvants Expressing NF-Kappa B Subunit p65/RelA or Type-1 Transactivator T-bet Enhance Antigen Specific DNA Vaccine-Induced Immunity. Vaccines 2014, 2, 196–215. [Google Scholar] [CrossRef]
  91. Pfeiffer, I.A.; Hoyer, S.; Gerer, K.F.; Voll, R.E.; Knippertz, I.; Gückel, E.; Schuler, G.; Schaft, N.; Dörrie, J. Triggering of NF-κB in cytokine-matured human DCs generates superior DCs for T-cell priming in cancer immunotherapy. Eur. J. Immunol. 2014, 44, 3413–3428. [Google Scholar] [CrossRef] [PubMed]
  92. Bosch, N.C.; Voll, R.E.; Voskens, C.J.; Gross, S.; Seliger, B.; Schuler, G.; Schaft, N.; Dörrie, J. NF-κB activation triggers NK-cell stimulation by monocyte-derived dendritic cells. Ther. Adv. Med. Oncol. 2019, 11, 1758835919891622. [Google Scholar] [CrossRef] [PubMed]
  93. Sasaki, S.; Amara, R.R.; Yeow, W.S.; Pitha, P.M.; Robinson, H.L. Regulation of DNA-raised immune responses by cotransfected interferon regulatory factors. J. Virol. 2002, 76, 6652–6659. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  94. Bontkes, H.J.; Kramer, D.; Ruizendaal, J.J.; Meijer, C.J.; Hooijberg, E. Tumor associated antigen and interleukin-12 mRNA transfected dendritic cells enhance effector function of natural killer cells and antigen specific T-cells. Clin. Immunol. 2008, 127, 375–384. [Google Scholar] [CrossRef] [PubMed]
  95. Li, S.S.; Kochar, N.K.; Elizaga, M.; Hay, C.M.; Wilson, G.J.; Cohen, K.W.; De Rosa, S.C.; Xu, R.; Ota-Setlik, A.; Morris, D.; et al. DNA Priming Increases Frequency of T-Cell Responses to a Vesicular Stomatitis Virus HIV Vaccine with Specific Enhancement of CD8(+) T-Cell Responses by Interleukin-12 Plasmid DNA. Clin. Vaccine Immunol. 2017, 24. [Google Scholar] [CrossRef] [Green Version]
  96. Sun, L.; Yuan, Q.; Xu, T.; Yao, L.; Feng, J.; Ma, J.; Wang, L.; Lv, C.; Wang, D. Novel adjuvant for immunization against tuberculosis: DNA vaccine expressing Mycobacterium tuberculosis antigen 85A and interleukin-15 fusion product elicits strong immune responses in mice. Biotechnol. Lett. 2017, 39, 1159–1166. [Google Scholar] [CrossRef]
  97. Zhang, Y.; Liang, S.; Li, X.; Wang, L.; Zhang, J.; Xu, J.; Huo, S.; Cao, X.; Zhong, Z.; Zhong, F. Mutual enhancement of IL-2 and IL-7 on DNA vaccine immunogenicity mainly involves regulations on their receptor expression and receptor-expressing lymphocyte generation. Vaccine 2015, 33, 3480–3487. [Google Scholar] [CrossRef]
  98. Luo, Z.; Wang, C.; Yi, H.; Li, P.; Pan, H.; Liu, L.; Cai, L.; Ma, Y. Nanovaccine loaded with poly I:C and STAT3 siRNA robustly elicits anti-tumor immune responses through modulating tumor-associated dendritic cells in vivo. Biomaterials 2015, 38, 50–60. [Google Scholar] [CrossRef]
  99. Luo, X.; Peng, X.; Hou, J.; Wu, S.; Shen, J.; Wang, L. Folic acid-functionalized polyethylenimine superparamagnetic iron oxide nanoparticles as theranostic agents for magnetic resonance imaging and PD-L1 siRNA delivery for gastric cancer. Int. J. Nanomed. 2017, 12, 5331–5343. [Google Scholar] [CrossRef] [Green Version]
  100. Self-Fordham, J.B.; Naqvi, A.R.; Uttamani, J.R.; Kulkarni, V.; Nares, S. MicroRNA: Dynamic Regulators of Macrophage Polarization and Plasticity. Front. Immunol. 2017, 8, 1062. [Google Scholar] [CrossRef] [Green Version]
  101. Migault, M.; Donnou-Fournet, E.; Galibert, M.D.; Gilot, D. Definition and identification of small RNA sponges: Focus on miRNA sequestration. Methods 2017, 117, 35–47. [Google Scholar] [CrossRef] [PubMed]
  102. Lima, J.F.; Cerqueira, L.; Figueiredo, C.; Oliveira, C.; Azevedo, N.F. Anti-miRNA oligonucleotides: A comprehensive guide for design. RNA Biol. 2018, 15, 338–352. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  103. Wagner, E. Tumor-targeted Delivery of Anti-microRNA for Cancer Therapy: pHLIP is Key. Angew. Chem. Int. Ed. Engl. 2015, 54, 5824–5826. [Google Scholar] [CrossRef] [PubMed]
  104. Vargas, J.E.; Salton, G.; Sodre de Castro Laino, A.; Pires, T.D.; Bonamino, M.; Lenz, G.; Delgado-Canedo, A. pLR: A lentiviral backbone series to stable transduction of bicistronic genes and exchange of promoters. Plasmid 2012, 68, 179–185. [Google Scholar] [CrossRef] [PubMed]
  105. Terenin, I.M.; Smirnova, V.V.; Andreev, D.E.; Dmitriev, S.E.; Shatsky, I.N. A researcher’s guide to the galaxy of IRESs. Cell. Mol. Life Sci. 2017, 74, 1431–1455. [Google Scholar] [CrossRef] [PubMed]
  106. Ko, H.L.; Park, H.J.; Kim, J.; Kim, H.; Youn, H.; Nam, J.H. Development of an RNA Expression Platform Controlled by Viral Internal Ribosome Entry Sites. J. Microbiol. Biotechnol. 2019, 29, 127–140. [Google Scholar] [CrossRef] [Green Version]
  107. Chng, J.; Wang, T.; Nian, R.; Lau, A.; Hoi, K.M.; Ho, S.C.; Gagnon, P.; Bi, X.; Yang, Y. Cleavage efficient 2A peptides for high level monoclonal antibody expression in CHO cells. mAbs 2015, 7, 403–412. [Google Scholar] [CrossRef] [Green Version]
  108. Kim, J.H.; Lee, S.R.; Li, L.H.; Park, H.J.; Park, J.H.; Lee, K.Y.; Kim, M.K.; Shin, B.A.; Choi, S.Y. High cleavage efficiency of a 2A peptide derived from porcine teschovirus-1 in human cell lines, zebrafish and mice. PloS ONE 2011, 6, e18556. [Google Scholar] [CrossRef] [Green Version]
  109. Gracey Maniar, L.E.; Maniar, J.M.; Chen, Z.Y.; Lu, J.; Fire, A.Z.; Kay, M.A. Minicircle DNA vectors achieve sustained expression reflected by active chromatin and transcriptional level. Mol. Ther. 2013, 21, 131–138. [Google Scholar] [CrossRef] [Green Version]
  110. Stenler, S.; Blomberg, P.; Smith, C.I. Safety and efficacy of DNA vaccines: Plasmids vs. minicircles. Hum. Vaccin. Immunother. 2014, 10, 1306–1308. [Google Scholar] [CrossRef] [Green Version]
  111. Lechardeur, D.; Lukacs, G.L. Nucleocytoplasmic transport of plasmid DNA: A perilous journey from the cytoplasm to the nucleus. Hum. Gene Ther. 2006, 17, 882–889. [Google Scholar] [CrossRef] [PubMed]
  112. Dean, D.A.; Dean, B.S.; Muller, S.; Smith, L.C. Sequence requirements for plasmid nuclear import. Exp. Cell. Res. 1999, 253, 713–722. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Kanazawa, T.; Yamazaki, M.; Fukuda, T.; Takashima, Y.; Okada, H. Versatile nuclear localization signal-based oligopeptide as a gene vector. Biol. Pharm. Bull. 2015, 38, 559–565. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  114. Grubor-Bauk, B.; Yu, W.; Wijesundara, D.; Gummow, J.; Garrod, T.; Brennan, A.J.; Voskoboinik, I.; Gowans, E.J. Intradermal delivery of DNA encoding HCV NS3 and perforin elicits robust cell-mediated immunity in mice and pigs. Gene Ther. 2016, 23, 26–37. [Google Scholar] [CrossRef] [PubMed]
  115. Krinner, S.; Heitzer, A.; Asbach, B.; Wagner, R. Interplay of Promoter Usage and Intragenic CpG Content: Impact on GFP Reporter Gene Expression. Hum. Gene Ther. 2015, 26, 826–840. [Google Scholar] [CrossRef]
  116. Yagi, M.; Miyamoto, T.; Toyama, Y.; Suda, T. Role of DC-STAMP in cellular fusion of osteoclasts and macrophage giant cells. J. Bone Miner. Metab. 2006, 24, 355–358. [Google Scholar] [CrossRef]
  117. Dresch, C.; Edelmann, S.L.; Marconi, P.; Brocker, T. Lentiviral-mediated transcriptional targeting of dendritic cells for induction of T cell tolerance in vivo. J. Immunol. 2008, 181, 4495–4506. [Google Scholar] [CrossRef] [Green Version]
  118. Bonkobara, M.; Zukas, P.K.; Shikano, S.; Nakamura, S.; Cruz, P.D., Jr.; Ariizumi, K. Epidermal Langerhans cell-targeted gene expression by a dectin-2 promoter. J. Immunol. 2001, 167, 6893–6900. [Google Scholar] [CrossRef]
  119. Lopes, A.; Vanvarenberg, K.; Preat, V.; Vandermeulen, G. Codon-Optimized P1A-Encoding DNA Vaccine: Toward a Therapeutic Vaccination against P815 Mastocytoma. Mol. Ther. Nucleic Acids 2017, 8, 404–415. [Google Scholar] [CrossRef] [Green Version]
  120. Ross, R.; Sudowe, S.; Beisner, J.; Ross, X.L.; Ludwig-Portugall, I.; Steitz, J.; Tuting, T.; Knop, J.; Reske-Kunz, A.B. Transcriptional targeting of dendritic cells for gene therapy using the promoter of the cytoskeletal protein fascin. Gene Ther. 2003, 10, 1035–1040. [Google Scholar] [CrossRef] [Green Version]
  121. Bros, M.; Ross, X.L.; Pautz, A.; Reske-Kunz, A.B.; Ross, R. The human fascin gene promoter is highly active in mature dendritic cells due to a stage-specific enhancer. J. Immunol. 2003, 171, 1825–1834. [Google Scholar] [CrossRef] [PubMed]
  122. Raker, V.; Maxeiner, J.; Reske-Kunz, A.B.; Sudowe, S. Efficiency of biolistic DNA vaccination in experimental type I allergy. In Biolistic DNA Delivery: Methods in Molecular Biology; Sudowe, S., Reske-Kunz, A., Eds.; Humana Press: Totowa, NJ, USA, 2013; pp. 357–370. [Google Scholar] [CrossRef]
  123. Castor, T.; Yogev, N.; Blank, T.; Barwig, C.; Prinz, M.; Waisman, A.; Bros, M.; Reske-Kunz, A.B. Inhibition of experimental autoimmune encephalomyelitis by tolerance-promoting DNA vaccination focused to dendritic cells. PloS ONE 2018, 13, e0191927. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  124. Sudowe, S.; Höhn, Y.; Renzing, A.; Maxeiner, J.; Montermann, E.; Habermeier, A.; Closs, E.; Bros, M.; Reske-Kunz, A.B. Inhibition of antigen-specific immune responses by co-application of an indoleamine 2,3-dioxygenase (IDO)-encoding vector requires antigen transgene expression focused on dendritic cells. Amino Acids 2020, 52, 411–424. [Google Scholar] [CrossRef] [Green Version]
  125. Angell, C.; Xie, S.; Zhang, L.; Chen, Y. DNA Nanotechnology for Precise Control over Drug Delivery and Gene Therapy. Small (Weinheim an der Bergstrasse, Germany) 2016, 12, 1117–1132. [Google Scholar] [CrossRef]
  126. Das, S.K.; Menezes, M.E.; Bhatia, S.; Wang, X.Y.; Emdad, L.; Sarkar, D.; Fisher, P.B. Gene Therapies for Cancer: Strategies, Challenges and Successes. J. Cell. Physiol. 2015, 230, 259–271. [Google Scholar] [CrossRef] [Green Version]
  127. Cai, P.; Zhang, X.; Wang, M.; Wu, Y.L.; Chen, X. Combinatorial Nano-Bio Interfaces. ACS Nano 2018. [Google Scholar] [CrossRef] [PubMed]
  128. Houseley, J.; Tollervey, D. The many pathways of RNA degradation. Cell 2009, 136, 763–776. [Google Scholar] [CrossRef] [Green Version]
  129. Li, B.; Zhang, X.; Dong, Y. Nanoscale platforms for messenger RNA delivery. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 2019, 11, e1530. [Google Scholar] [CrossRef]
  130. Midoux, P.; Pichon, C. Lipid-based mRNA vaccine delivery systems. Expert. Rev. Vaccines 2015, 14, 221–234. [Google Scholar] [CrossRef] [Green Version]
  131. Foged, C.; Brodin, B.; Frokjaer, S.; Sundblad, A. Particle size and surface charge affect particle uptake by human dendritic cells in an in vitro model. Int. J. Pharm. 2005, 298, 315–322. [Google Scholar] [CrossRef]
  132. Xiang, S.D.; Scholzen, A.; Minigo, G.; David, C.; Apostolopoulos, V.; Mottram, P.L.; Plebanski, M. Pathogen recognition and development of particulate vaccines: Does size matter? Methods 2006, 40, 1–9. [Google Scholar] [CrossRef] [PubMed]
  133. Niikura, K.; Matsunaga, T.; Suzuki, T.; Kobayashi, S.; Yamaguchi, H.; Orba, Y.; Kawaguchi, A.; Hasegawa, H.; Kajino, K.; Ninomiya, T.; et al. Gold nanoparticles as a vaccine platform: Influence of size and shape on immunological responses in vitro and in vivo. ACS Nano 2013, 7, 3926–3938. [Google Scholar] [CrossRef] [PubMed]
  134. Radis-Baptista, G.; Campelo, I.S.; Morlighem, J.R.L.; Melo, L.M.; Freitas, V.J.F. Cell-penetrating peptides (CPPs): From delivery of nucleic acids and antigens to transduction of engineered nucleases for application in transgenesis. J. Biotechnol. 2017, 252, 15–26. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  135. Falanga, A.; Galdiero, S. Peptide chemistry encounters nanomedicine: Recent applications and upcoming scenarios in cancer. Future. Med. Chem. 2018, 10, 1877–1880. [Google Scholar] [CrossRef] [Green Version]
  136. Dane, K.Y.; Nembrini, C.; Tomei, A.A.; Eby, J.K.; O’Neil, C.P.; Velluto, D.; Swartz, M.A.; Inverardi, L.; Hubbell, J.A. Nano-sized drug-loaded micelles deliver payload to lymph node immune cells and prolong allograft survival. J. Controlled Release 2011, 156, 154–160. [Google Scholar] [CrossRef]
  137. Allen, T.M.; Hansen, C.B.; Guo, L.S. Subcutaneous administration of liposomes: A comparison with the intravenous and intraperitoneal routes of injection. Biochim. Biophys. Acta 1993, 1150, 9–16. [Google Scholar] [CrossRef]
  138. Longmire, M.; Choyke, P.L.; Kobayashi, H. Clearance properties of nano-sized particles and molecules as imaging agents: Considerations and caveats. Nanomedicine (London, England) 2008, 3, 703–717. [Google Scholar] [CrossRef] [Green Version]
  139. Hu, J.; Sheng, Y.; Shi, J.; Yu, B.; Yu, Z.; Liao, G. Long circulating polymeric nanoparticles for gene/drug delivery. Curr. Drug Metab. 2018, 19, 723–738. [Google Scholar] [CrossRef]
  140. He, C.; Hu, Y.; Yin, L.; Tang, C.; Yin, C. Effects of particle size and surface charge on cellular uptake and biodistribution of polymeric nanoparticles. Biomaterials 2010, 31, 3657–3666. [Google Scholar] [CrossRef]
  141. Fogli, S.; Montis, C.; Paccosi, S.; Silvano, A.; Michelucci, E.; Berti, D.; Bosi, A.; Parenti, A.; Romagnoli, P. Inorganic nanoparticles as potential regulators of immune response in dendritic cells. Nanomedicine (London, England) 2017, 12, 1647–1660. [Google Scholar] [CrossRef]
  142. Svoboda, O.; Fohlerova, Z.; Baiazitova, L.; Mlynek, P.; Samouylov, K.; Provaznik, I.; Hubalek, J. Transfection by Polyethyleneimine-Coated Magnetic Nanoparticles: Fine-Tuning the Condition for Electrophysiological Experiments. J. Biomed. Nanotechnol. 2018, 14, 1505–1514. [Google Scholar] [CrossRef] [PubMed]
  143. Xiong, L.; Qiao, S.Z. A mesoporous organosilica nano-bowl with high DNA loading capacity - a potential gene delivery carrier. Nanoscale 2016, 8, 17446–17450. [Google Scholar] [CrossRef] [PubMed]
  144. Singh, D.P.; Herrera, C.E.; Singh, B.; Singh, S.; Singh, R.K.; Kumar, R. Graphene oxide: An efficient material and recent approach for biotechnological and biomedical applications. Mater. Sci. Eng. C Mater. Biol. App. 2018, 86, 173–197. [Google Scholar] [CrossRef] [PubMed]
  145. Kim, H.; Kim, J.; Lee, M.; Choi, H.C.; Kim, W.J. Stimuli-Regulated Enzymatically Degradable Smart Graphene-Oxide-Polymer Nanocarrier Facilitating Photothermal Gene Delivery. Adv. Healthc. Mater. 2016, 5, 1918–1930. [Google Scholar] [CrossRef] [PubMed]
  146. Yue, H.; Zhou, X.; Cheng, M.; Xing, D. Graphene oxide-mediated Cas9/sgRNA delivery for efficient genome editing. Nanoscale 2018, 10, 1063–1071. [Google Scholar] [CrossRef]
  147. Quader, S.; Kataoka, K. Nanomaterial-Enabled Cancer Therapy. Mol. Ther. 2017, 25, 1501–1513. [Google Scholar] [CrossRef] [Green Version]
  148. Jang, H.J.; Jeong, E.J.; Lee, K.Y. Carbon Dioxide-Generating PLG Nanoparticles for Controlled Anti-Cancer Drug Delivery. Pharm. Res. 2018, 35, 59. [Google Scholar] [CrossRef]
  149. Li, Z.; Xiong, F.; He, J.; Dai, X.; Wang, G. Surface-functionalized, pH-responsive poly(lactic-co-glycolic acid)-based microparticles for intranasal vaccine delivery: Effect of surface modification with chitosan and mannan. Eur. J. Pharm. Biopharm. 2016, 109, 24–34. [Google Scholar] [CrossRef]
  150. Itaka, K.; Harada, A.; Yamasaki, Y.; Nakamura, K.; Kawaguchi, H.; Kataoka, K. In situ single cell observation by fluorescence resonance energy transfer reveals fast intra-cytoplasmic delivery and easy release of plasmid DNA complexed with linear polyethylenimine. J. Gene Med. 2004, 6, 76–84. [Google Scholar] [CrossRef]
  151. Zhu, J.; Qiao, M.; Wang, Q.; Ye, Y.; Ba, S.; Ma, J.; Hu, H.; Zhao, X.; Chen, D. Dual-responsive polyplexes with enhanced disassembly and endosomal escape for efficient delivery of siRNA. Biomaterials 2018, 162, 47–59. [Google Scholar] [CrossRef]
  152. Hao, F.; Li, Y.; Zhu, J.; Sun, J.; Marshall, B.; Lee, R.J.; Teng, L.; Yang, Z.; Xie, J. Polyethylenimine-based Formulations for Delivery of Oligonucleotides. Curr. Med. Chem. 2019, 26, 2264–2284. [Google Scholar] [CrossRef] [PubMed]
  153. Erbacher, P.; Zou, S.; Bettinger, T.; Steffan, A.M.; Remy, J.S. Chitosan-based vector/DNA complexes for gene delivery: Biophysical characteristics and transfection ability. Pharm. Res. 1998, 15, 1332–1339. [Google Scholar] [CrossRef] [PubMed]
  154. Liu, Q.; Chen, X.; Jia, J.; Zhang, W.; Yang, T.; Wang, L.; Ma, G. pH-Responsive Poly(D,L-lactic-co-glycolic acid) Nanoparticles with Rapid Antigen Release Behavior Promote Immune Response. ACS Nano 2015, 9, 4925–4938. [Google Scholar] [CrossRef] [PubMed]
  155. Slutter, B.; Plapied, L.; Fievez, V.; Sande, M.A.; des Rieux, A.; Schneider, Y.J.; Van Riet, E.; Jiskoot, W.; Preat, V. Mechanistic study of the adjuvant effect of biodegradable nanoparticles in mucosal vaccination. J. Controlled Release 2009, 138, 113–121. [Google Scholar] [CrossRef]
  156. Lohcharoenkal, W.; Wang, L.; Chen, Y.C.; Rojanasakul, Y. Protein nanoparticles as drug delivery carriers for cancer therapy. BioMed Res. Int. 2014, 2014, 180549. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  157. Moran, M.C.; Rosell, N.; Ruano, G.; Busquets, M.A.; Vinardell, M.P. Gelatin-based nanoparticles as DNA delivery systems: Synthesis, physicochemical and biocompatible characterization. Colloids Surf. B. 2015, 134, 156–168. [Google Scholar] [CrossRef] [PubMed]
  158. Kumari, M.; Liu, C.H.; Wu, W.C. Efficient gene delivery by oligochitosan conjugated serum albumin: Facile synthesis, polyplex stability, and transfection. Carbohydr. Polym. 2018, 183, 37–49. [Google Scholar] [CrossRef]
  159. Han, J.; Wang, Q.; Zhang, Z.; Gong, T.; Sun, X. Cationic bovine serum albumin based self-assembled nanoparticles as siRNA delivery vector for treating lung metastatic cancer. Small (Weinheim an der Bergstrasse, Germany) 2014, 10, 524–535. [Google Scholar] [CrossRef]
  160. Rezaee, M.; Oskuee, R.K.; Nassirli, H.; Malaekeh-Nikouei, B. Progress in the development of lipopolyplexes as efficient non-viral gene delivery systems. J. Controlled Release 2016, 236, 1–14. [Google Scholar] [CrossRef]
  161. Felgner, P.L.; Gadek, T.R.; Holm, M.; Roman, R.; Chan, H.W.; Wenz, M.; Northrop, J.P.; Ringold, G.M.; Danielsen, M. Lipofection: A highly efficient, lipid-mediated DNA-transfection procedure. Proc. Natl. Acad. Sci. USA 1987, 84, 7413–7417. [Google Scholar] [CrossRef] [Green Version]
  162. Mevel, M.; Haudebourg, T.; Colombani, T.; Peuziat, P.; Dallet, L.; Chatin, B.; Lambert, O.; Berchel, M.; Montier, T.; Jaffres, P.A.; et al. Important role of phosphoramido linkage in imidazole-based dioleyl helper lipids for liposome stability and primary cell transfection. J. Gene Med. 2016, 18, 3–15. [Google Scholar] [CrossRef] [PubMed]
  163. Yang, J.; Bahreman, A.; Daudey, G.; Bussmann, J.; Olsthoorn, R.C.; Kros, A. Drug Delivery via Cell Membrane Fusion Using Lipopeptide Modified Liposomes. ACS Cent. Sci. 2016, 2, 621–630. [Google Scholar] [CrossRef] [PubMed]
  164. Glass, J.J.; Kent, S.J.; De Rose, R. Enhancing dendritic cell activation and HIV vaccine effectiveness through nanoparticle vaccination. Expert Rev. Vaccines 2016, 15, 719–729. [Google Scholar] [CrossRef] [PubMed]
  165. Wagener, K.; Bros, M.; Krumb, M.; Langhanki, J.; Pektor, S.; Worm, M.; Schinnerer, M.; Montermann, E.; Miederer, M.; Frey, H.; et al. Targeting of Immune Cells with Trimannosylated Liposomes. Adv. Ther. 2020, 3, 1900185. [Google Scholar] [CrossRef] [Green Version]
  166. Lindén, M. Biodistribution and Excretion of Intravenously Injected Mesoporous Silica Nanoparticles: Implications for Drug Delivery Efficiency and Safety. Enzymes 2018, 43, 155–180. [Google Scholar] [CrossRef]
  167. Guo, X.; Zhuang, Q.; Ji, T.; Zhang, Y.; Li, C.; Wang, Y.; Li, H.; Jia, H.; Liu, Y.; Du, L. Multi-functionalized chitosan nanoparticles for enhanced chemotherapy in lung cancer. Carbohydr. Polym. 2018, 195, 311–320. [Google Scholar] [CrossRef]
  168. Meng, H.; Leong, W.; Leong, K.W.; Chen, C.; Zhao, Y. Walking the line: The fate of nanomaterials at biological barriers. Biomaterials 2018, 174, 41–53. [Google Scholar] [CrossRef]
  169. Zhang, Y.N.; Poon, W.; Tavares, A.J.; McGilvray, I.D.; Chan, W.C.W. Nanoparticle-liver interactions: Cellular uptake and hepatobiliary elimination. J. Controlled Release 2016, 240, 332–348. [Google Scholar] [CrossRef]
  170. Li, P.; He, K.; Li, J.; Liu, Z.; Gong, J. The role of Kupffer cells in hepatic diseases. Mol. immunol. 2017, 85, 222–229. [Google Scholar] [CrossRef]
  171. Sago, C.D.; Krupczak, B.R.; Lokugamage, M.P.; Gan, Z.; Dahlman, J.E. Cell Subtypes Within the Liver Microenvironment Differentially Interact with Lipid Nanoparticles. Cell. Mol. Bioeng. 2019, 12, 389–397. [Google Scholar] [CrossRef]
  172. Pustylnikov, S.; Sagar, D.; Jain, P.; Khan, Z.K. Targeting the C-type lectins-mediated host-pathogen interactions with dextran. J. Pharm. Sci. 2014, 17, 371–392. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  173. Elvevold, K.; Simon-Santamaria, J.; Hasvold, H.; McCourt, P.; Smedsrød, B.; Sørensen, K.K. Liver sinusoidal endothelial cells depend on mannose receptor-mediated recruitment of lysosomal enzymes for normal degradation capacity. Hepatology 2008, 48, 2007–2015. [Google Scholar] [CrossRef] [PubMed]
  174. Hughes, D.A.; Fraser, I.P.; Gordon, S. Murine macrophage scavenger receptor: In vivo expression and function as receptor for macrophage adhesion in lymphoid and non-lymphoid organs. Eur. J. Immunol. 1995, 25, 466–473. [Google Scholar] [CrossRef] [PubMed]
  175. Poisson, J.; Lemoinne, S.; Boulanger, C.; Durand, F.; Moreau, R.; Valla, D.; Rautou, P.E. Liver sinusoidal endothelial cells: Physiology and role in liver diseases. J. Hepatol. 2017, 66, 212–227. [Google Scholar] [CrossRef] [Green Version]
  176. Gül, N.; Babes, L.; Siegmund, K.; Korthouwer, R.; Bögels, M.; Braster, R.; Vidarsson, G.; ten Hagen, T.L.; Kubes, P.; van Egmond, M. Macrophages eliminate circulating tumor cells after monoclonal antibody therapy. J. Clin. Invest. 2014, 124, 812–823. [Google Scholar] [CrossRef]
  177. Ganesan, L.P.; Kim, J.; Wu, Y.; Mohanty, S.; Phillips, G.S.; Birmingham, D.J.; Robinson, J.M.; Anderson, C.L. FcγRIIb on liver sinusoidal endothelium clears small immune complexes. J. Immunol. 2012, 189, 4981–4988. [Google Scholar] [CrossRef] [Green Version]
  178. Hinglais, N.; Kazatchkine, M.D.; Mandet, C.; Appay, M.D.; Bariety, J. Human liver Kupffer cells express CR1, CR3, and CR4 complement receptor antigens. An immunohistochemical study. Lab. Invest. 1989, 61, 509–514. [Google Scholar]
  179. Bros, M.; Nuhn, L.; Simon, J.; Moll, L.; Mailander, V.; Landfester, K.; Grabbe, S. The Protein Corona as a Confounding Variable of Nanoparticle-Mediated Targeted Vaccine Delivery. Front. Immunol. 2018, 9, 1760. [Google Scholar] [CrossRef]
  180. Shen, L.; Tenzer, S.; Storck, W.; Hobernik, D.; Raker, V.K.; Fischer, K.; Decker, S.; Dzionek, A.; Krauthauser, S.; Diken, M.; et al. Protein corona-mediated targeting of nanocarriers to B cells allows redirection of allergic immune responses. J. Allergy Clin. Immunol. 2018. [Google Scholar] [CrossRef] [Green Version]
  181. Sun, X.; Wang, G.; Zhang, H.; Hu, S.; Liu, X.; Tang, J.; Shen, Y. The Blood Clearance Kinetics and Pathway of Polymeric Micelles in Cancer Drug Delivery. ACS Nano 2018, 12, 6179–6192. [Google Scholar] [CrossRef]
  182. Zhou, H.; Fan, Z.; Li, P.Y.; Deng, J.; Arhontoulis, D.C.; Li, C.Y.; Bowne, W.B.; Cheng, H. Dense and Dynamic Polyethylene Glycol Shells Cloak Nanoparticles from Uptake by Liver Endothelial Cells for Long Blood Circulation. ACS Nano 2018, 12, 10130–10141. [Google Scholar] [CrossRef] [PubMed]
  183. Hayat, S.M.G.; Jaafari, M.R.; Hatamipour, M.; Penson, P.E.; Sahebkar, A. Liposome Circulation Time is Prolonged by CD47 Coating. Protein Pept. Lett. 2020. [Google Scholar] [CrossRef] [PubMed]
  184. Gulla, S.K.; Rao, B.R.; Moku, G.; Jinka, S.; Nimmu, N.V.; Khalid, S.; Patra, C.R.; Chaudhuri, A. In vivo targeting of DNA vaccines to dendritic cells using functionalized gold nanoparticles. Biomater. Sci. 2019, 7, 773–788. [Google Scholar] [CrossRef] [PubMed]
  185. Wi, T.I.; Byeon, Y.; Won, J.E.; Lee, J.M.; Kang, T.H.; Lee, J.W.; Lee, Y.J.; Sood, A.K.; Han, H.D.; Park, Y.M. Selective Tumor-Specific Antigen Delivery to Dendritic Cells Using Mannose-Labeled Poly(d, l-lactide-co-glycolide) Nanoparticles for Cancer Immunotherapy. J. Biomed. Nanotechnol. 2020, 16, 201–211. [Google Scholar] [CrossRef] [PubMed]
  186. Chen, H.; Yuan, J.; Wang, Y.; Silvers, W.K. Distribution of ATPase-positive Langerhans cells in normal adult human skin. Br. J. Dermatol. 1985, 113, 707–711. [Google Scholar] [CrossRef]
  187. Russo, E.; Nitschke, M.; Halin, C. Dendritic cell interactions with lymphatic endothelium. Lymphatic Research and Biology 2013, 11, 172–182. [Google Scholar] [CrossRef]
  188. Fernando, G.J.; Zhang, J.; Ng, H.I.; Haigh, O.L.; Yukiko, S.R.; Kendall, M.A. Influenza nucleoprotein DNA vaccination by a skin targeted, dry coated, densely packed microprojection array (Nanopatch) induces potent antibody and CD8(+) T cell responses. J. Controlled Release 2016, 237, 35–41. [Google Scholar] [CrossRef] [Green Version]
  189. Lambracht-Washington, D.; Fu, M.; Frost, P.; Rosenberg, R.N. Evaluation of a DNA Aβ42 vaccine in adult rhesus monkeys (Macaca mulatta): Antibody kinetics and immune profile after intradermal immunization with full-length DNA Aβ42 trimer. Alzheimers Res. Ther. 2017, 9, 30. [Google Scholar] [CrossRef] [Green Version]
  190. Alvarez, R.D.; Huh, W.K.; Bae, S.; Lamb, L.S., Jr.; Conner, M.G.; Boyer, J.; Wang, C.; Hung, C.F.; Sauter, E.; Paradis, M.; et al. A pilot study of pNGVL4a-CRT/E7(detox) for the treatment of patients with HPV16+ cervical intraepithelial neoplasia 2/3 (CIN2/3). Gynecol. Oncol. 2016, 140, 245–252. [Google Scholar] [CrossRef] [Green Version]
  191. Duong, H.T.T.; Yin, Y.; Thambi, T.; Nguyen, T.L.; Giang Phan, V.H.; Lee, M.S.; Lee, J.E.; Kim, J.; Jeong, J.H.; Lee, D.S. Smart vaccine delivery based on microneedle arrays decorated with ultra-pH-responsive copolymers for cancer immunotherapy. Biomaterials 2018, 185, 13–24. [Google Scholar] [CrossRef]
  192. Cole, G.; Ali, A.A.; McErlean, E.; Mulholland, E.J.; Short, A.; McCrudden, C.M.; McCaffrey, J.; Robson, T.; Kett, V.L.; Coulter, J.A.; et al. DNA vaccination via RALA nanoparticles in a microneedle delivery system induces a potent immune response against the endogenous prostate cancer stem cell antigen. Acta Biomater. 2019, 96, 480–490. [Google Scholar] [CrossRef] [PubMed]
  193. Samuels, S.; Marijne Heeren, A.; Zijlmans, H.; Welters, M.J.P.; van den Berg, J.H.; Philips, D.; Kvistborg, P.; Ehsan, I.; Scholl, S.M.E.; Nuijen, B.; et al. HPV16 E7 DNA tattooing: Safety, immunogenicity, and clinical response in patients with HPV-positive vulvar intraepithelial neoplasia. Cancer Immunol. Immunother. 2017, 66, 1163–1173. [Google Scholar] [CrossRef] [PubMed]
  194. Bernelin-Cottet, C.; Urien, C.; McCaffrey, J.; Collins, D.; Donadei, A.; McDaid, D.; Jakob, V.; Barnier-Quer, C.; Collin, N.; Bouguyon, E.; et al. Electroporation of a nanoparticle-associated DNA vaccine induces higher inflammation and immunity compared to its delivery with microneedle patches in pigs. J. Controlled Release 2019, 308, 14–28. [Google Scholar] [CrossRef] [PubMed]
  195. Schultheis, K.; Smith, T.R.F.; Kiosses, W.B.; Kraynyak, K.A.; Wong, A.; Oh, J.; Broderick, K.E. Delineating the Cellular Mechanisms Associated with Skin Electroporation. Hum. Gene. Ther. Methods 2018, 29, 177–188. [Google Scholar] [CrossRef] [PubMed]
  196. Lamolinara, A.; Stramucci, L.; Hysi, A.; Iezzi, M.; Marchini, C.; Mariotti, M.; Amici, A.; Curcio, C. Intradermal DNA Electroporation Induces Cellular and Humoral Immune Response and Confers Protection against HER2/neu Tumor. J. Immunol. Res. 2015, 2015, 159145. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  197. Lee, S.H.; Danishmalik, S.N.; Sin, J.I. DNA vaccines, electroporation and their applications in cancer treatment. Hum. Vaccin. Immunother. 2015, 11, 1889–1900. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  198. Katz, M.G.; Fargnoli, A.S.; Gubara, S.M.; Fish, K.; Weber, T.; Bridges, C.R.; Hajjar, R.J.; Ishikawa, K. Targeted Gene Delivery through the Respiratory System: Rationale for Intratracheal Gene Transfer. J. Cardiovasc. Dev. Dis. 2019, 6, 8. [Google Scholar] [CrossRef] [Green Version]
  199. Davies, L.A.; Nunez-Alonso, G.A.; McLachlan, G.; Hyde, S.C.; Gill, D.R. Aerosol delivery of DNA/liposomes to the lung for cystic fibrosis gene therapy. Human Gene Ther. Clinical Develop. 2014, 25, 97–107. [Google Scholar] [CrossRef]
  200. Zheng, Z.; Diaz-Arevalo, D.; Guan, H.; Zeng, M. Noninvasive vaccination against infectious diseases. Hum. Vaccin. Immunother. 2018, 14, 1717–1733. [Google Scholar] [CrossRef]
  201. Mortimer, G.M.; Butcher, N.J.; Musumeci, A.W.; Deng, Z.J.; Martin, D.J.; Minchin, R.F. Cryptic epitopes of albumin determine mononuclear phagocyte system clearance of nanomaterials. ACS Nano 2014, 8, 3357–3366. [Google Scholar] [CrossRef]
  202. Huang, G.; Huang, H. Application of dextran as nanoscale drug carriers. Nanomedicine (London, England) 2018, 13, 3149–3158. [Google Scholar] [CrossRef] [PubMed]
  203. Khalil, I.A.; Harashima, H. An efficient PEGylated gene delivery system with improved targeting: Synergism between octaarginine and a fusogenic peptide. Int. J. Pharm. 2018, 538, 179–187. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  204. Zhang, P.; Sun, F.; Liu, S.; Jiang, S. Anti-PEG antibodies in the clinic: Current issues and beyond PEGylation. J. Controlled Release 2016, 244, 184–193. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  205. Frenz, T.; Grabski, E.; Duran, V.; Hozsa, C.; Stepczynska, A.; Furch, M.; Gieseler, R.K.; Kalinke, U. Antigen presenting cell-selective drug delivery by glycan-decorated nanocarriers. Eur. J. Pharm. Biopharm. 2015, 95, 13–17. [Google Scholar] [CrossRef]
  206. Burgdorf, S.; Lukacs-Kornek, V.; Kurts, C. The mannose receptor mediates uptake of soluble but not of cell-associated antigen for cross-presentation. J. Immunol. 2006, 176, 6770–6776. [Google Scholar] [CrossRef] [Green Version]
  207. Appelmelk, B.J.; van Die, I.; van Vliet, S.J.; Vandenbroucke-Grauls, C.M.; Geijtenbeek, T.B.; van Kooyk, Y. Cutting edge: Carbohydrate profiling identifies new pathogens that interact with dendritic cell-specific ICAM-3-grabbing nonintegrin on dendritic cells. J. Immunol. 2003, 170, 1635–1639. [Google Scholar] [CrossRef] [Green Version]
  208. Qiao, C.; Liu, J.; Yang, J.; Li, Y.; Weng, J.; Shao, Y.; Zhang, X. Enhanced non-inflammasome mediated immune responses by mannosylated zwitterionic-based cationic liposomes for HIV DNA vaccines. Biomaterials 2016, 85, 1–17. [Google Scholar] [CrossRef]
  209. Wang, Q.; Cao, W.; Yang, Z.G.; Zhao, G.F. DC targeting DNA vaccines induce protective and therapeutic antitumor immunity in mice. Int. J. Clin. Exp. Med. 2015, 8, 17565–17577. [Google Scholar]
  210. Shimizu, K.; Iyoda, T.; Okada, M.; Yamasaki, S.; Fujii, S.I. Immune suppression and reversal of the suppressive tumor microenvironment. Int. Immunol. 2018, 30, 445–454. [Google Scholar] [CrossRef]
  211. Weber, R.; Fleming, V.; Hu, X.; Nagibin, V.; Groth, C.; Altevogt, P.; Utikal, J.; Umansky, V. Myeloid-Derived Suppressor Cells Hinder the Anti-Cancer Activity of Immune Checkpoint Inhibitors. Front. Immunol. 2018, 9, 1310. [Google Scholar] [CrossRef] [Green Version]
  212. Ahrends, T.; Borst, J. The opposing roles of CD4(+) T cells in anti-tumour immunity. Immunology 2018. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  213. Hippen, K.L.; Loschi, M.; Nicholls, J.; MacDonald, K.P.A.; Blazar, B.R. Effects of MicroRNA on Regulatory T Cells and Implications for Adoptive Cellular Therapy to Ameliorate Graft-versus-Host Disease. Front. Immunol. 2018, 9, 57. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  214. Zhang, C.; Wang, S.; Liu, Y.; Yang, C. Epigenetics in myeloid derived suppressor cells: A sheathed sword towards cancer. Oncotarget 2016, 7, 57452–57463. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  215. He, W.; Liang, P.; Guo, G.; Huang, Z.; Niu, Y.; Dong, L.; Wang, C.; Zhang, J. Re-polarizing Myeloid-derived Suppressor Cells (MDSCs) with Cationic Polymers for Cancer Immunotherapy. Sci. Rep. 2016, 6, 24506. [Google Scholar] [CrossRef]
  216. Li, W.; Deng, C.; Yang, H.; Wang, G. The Regulatory T Cell in Active Systemic Lupus Erythematosus Patients: A Systemic Review and Meta-Analysis. Front. Immunol. 2019, 10, 159. [Google Scholar] [CrossRef] [Green Version]
  217. Bacher, P.; Scheffold, A. Antigen-specific regulatory T-cell responses against aeroantigens and their role in allergy. Mucosal Immunol. 2018, 11, 1537–1550. [Google Scholar] [CrossRef] [Green Version]
  218. Najafi, M.; Farhood, B.; Mortezaee, K. Contribution of regulatory T cells to cancer: A review. J. Cell. Physiol. 2019, 234, 7983–7993. [Google Scholar] [CrossRef]
  219. Attias, M.; Al-Aubodah, T.; Piccirillo, C.A. Mechanisms of human FoxP3(+) T(reg) cell development and function in health and disease. Clin. Exp. Immunol. 2019, 197, 36–51. [Google Scholar] [CrossRef] [Green Version]
  220. Yang, S.; Xie, C.; Chen, Y.; Wang, J.; Chen, X.; Lu, Z.; June, R.R.; Zheng, S.G. Differential roles of TNFα-TNFR1 and TNFα-TNFR2 in the differentiation and function of CD4(+)Foxp3(+) induced Treg cells in vitro and in vivo periphery in autoimmune diseases. Cell Death Dis. 2019, 10, 27. [Google Scholar] [CrossRef]
  221. Oh, J.; Wang, W.; Thomas, R.; Su, D.M. Capacity of tTreg generation is not impaired in the atrophied thymus. PLoS Biol. 2017, 15, e2003352. [Google Scholar] [CrossRef]
  222. Zhong, H.; Liu, Y.; Xu, Z.; Liang, P.; Yang, H.; Zhang, X.; Zhao, J.; Chen, J.; Fu, S.; Tang, Y.; et al. TGF-β-Induced CD8(+)CD103(+) Regulatory T Cells Show Potent Therapeutic Effect on Chronic Graft-versus-Host Disease Lupus by Suppressing B Cells. Front. Immunol. 2018, 9, 35. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  223. Devi, K.S.; Anandasabapathy, N. The origin of DCs and capacity for immunologic tolerance in central and peripheral tissues. Semin. Immunopathol. 2017, 39, 137–152. [Google Scholar] [CrossRef] [PubMed]
  224. Takenaka, M.C.; Quintana, F.J. Tolerogenic dendritic cells. Semin. Immunopathol. 2017, 39, 113–120. [Google Scholar] [CrossRef] [PubMed]
  225. Hall, B.M.; Robinson, C.M.; Plain, K.M.; Verma, N.D.; Tran, G.T.; Nomura, M.; Carter, N.; Boyd, R.; Hodgkinson, S.J. Changes in Reactivity In Vitro of CD4(+)CD25(+) and CD4(+)CD25(-) T Cell Subsets in Transplant Tolerance. Front. Immunol. 2017, 8, 994. [Google Scholar] [CrossRef] [Green Version]
  226. Sun, X.; He, S.; Lv, C.; Sun, X.; Wang, J.; Zheng, W.; Wang, D. Analysis of murine and human Treg subsets in inflammatory bowel disease. Mol. Med. Rep. 2017, 16, 2893–2898. [Google Scholar] [CrossRef]
  227. Huang, Y.H.; Chang, C.Y.; Kuo, Y.Z.; Fang, W.Y.; Kao, H.Y.; Tsai, S.T.; Wu, L.W. Cancer-associated fibroblast-derived interleukin-1β activates protumor C-C motif chemokine ligand 22 signaling in head and neck cancer. Cancer Sci. 2019, 110, 2783–2793. [Google Scholar] [CrossRef] [Green Version]
  228. Siede, J.; Fröhlich, A.; Datsi, A.; Hegazy, A.N.; Varga, D.V.; Holecska, V.; Saito, H.; Nakae, S.; Löhning, M. IL-33 Receptor-Expressing Regulatory T Cells Are Highly Activated, Th2 Biased and Suppress CD4 T Cell Proliferation through IL-10 and TGFβ Release. PloS ONE 2016, 11, e0161507. [Google Scholar] [CrossRef]
  229. Tanaka, A.; Sakaguchi, S. Targeting Treg cells in cancer immunotherapy. Eur. J. Immunol. 2019, 49, 1140–1146. [Google Scholar] [CrossRef] [Green Version]
  230. Conroy, H.; Galvin, K.C.; Higgins, S.C.; Mills, K.H. Gene silencing of TGF-β1 enhances antitumor immunity induced with a dendritic cell vaccine by reducing tumor-associated regulatory T cells. Cancer Immunol. Immunother. 2012, 61, 425–431. [Google Scholar] [CrossRef]
  231. Masjedi, A.; Ahmadi, A.; Ghani, S.; Malakotikhah, F.; Nabi Afjadi, M.; Irandoust, M.; Karoon Kiani, F.; Heydarzadeh Asl, S.; Atyabi, F.; Hassannia, H.; et al. Silencing adenosine A2a receptor enhances dendritic cell-based cancer immunotherapy. Nanomedicine 2020, 29, 102240. [Google Scholar] [CrossRef]
  232. Zhang, H.H.; Fei, R.; Xie, X.W.; Wang, L.; Luo, H.; Wang, X.Y.; Wei, L.; Chen, H.S. Specific suppression in regulatory T cells by Foxp3 siRNA contributes to enhance the in vitro anti-tumor immune response in hepatocellular carcinoma patients. Beijing Da Xue Xue Bao Yi Xue Ban 2009, 41, 313–318. [Google Scholar] [PubMed]
  233. Kang, S.; Xie, J.; Ma, S.; Liao, W.; Zhang, J.; Luo, R. Targeted knock down of CCL22 and CCL17 by siRNA during DC differentiation and maturation affects the recruitment of T subsets. Immunobiology 2010, 215, 153–162. [Google Scholar] [CrossRef] [PubMed]
  234. Jebbawi, F.; Fayyad-Kazan, H.; Merimi, M.; Lewalle, P.; Verougstraete, J.C.; Leo, O.; Romero, P.; Burny, A.; Badran, B.; Martiat, P.; et al. A microRNA profile of human CD8(+) regulatory T cells and characterization of the effects of microRNAs on Treg cell-associated genes. J. Transl. Med. 2014, 12, 218. [Google Scholar] [CrossRef] [PubMed]
  235. Jonuleit, H.; Bopp, T.; Becker, C. Treg cells as potential cellular targets for functionalized nanoparticles in cancer therapy. Nanomedicine (London, England) 2016, 11, 2699–2709. [Google Scholar] [CrossRef] [PubMed]
  236. Naghavian, R.; Ghaedi, K.; Kiani-Esfahani, A.; Ganjalikhani-Hakemi, M.; Etemadifar, M.; Nasr-Esfahani, M.H. miR-141 and miR-200a, Revelation of New Possible Players in Modulation of Th17/Treg Differentiation and Pathogenesis of Multiple Sclerosis. PloS ONE 2015, 10, e0124555. [Google Scholar] [CrossRef]
  237. Zhou, J.; Li, X.; Wu, X.; Zhang, T.; Zhu, Q.; Wang, X.; Wang, H.; Wang, K.; Lin, Y.; Wang, X. Exosomes Released from Tumor-Associated Macrophages Transfer miRNAs That Induce a Treg/Th17 Cell Imbalance in Epithelial Ovarian Cancer. Cancer Immunol. Res. 2018, 6, 1578–1592. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  238. Klein, M.; Bopp, T. Cyclic AMP Represents a Crucial Component of Treg Cell-Mediated Immune Regulation. Front. Immunol. 2016, 7, 315. [Google Scholar] [CrossRef] [Green Version]
  239. Frick, S.U.; Domogalla, M.P.; Baier, G.; Wurm, F.R.; Mailänder, V.; Landfester, K.; Steinbrink, K. Interleukin-2 Functionalized Nanocapsules for T Cell-Based Immunotherapy. ACS Nano 2016, 10, 9216–9226. [Google Scholar] [CrossRef]
  240. Woller, N.; Knocke, S.; Mundt, B.; Gürlevik, E.; Strüver, N.; Kloos, A.; Boozari, B.; Schache, P.; Manns, M.P.; Malek, N.P.; et al. Virus-induced tumor inflammation facilitates effective DC cancer immunotherapy in a Treg-dependent manner in mice. J. Clin. Invest. 2011, 121, 2570–2582. [Google Scholar] [CrossRef]
  241. Al Sayed, M.F.; Amrein, M.A.; Bührer, E.D.; Huguenin, A.L.; Radpour, R.; Riether, C.; Ochsenbein, A.F. T-cell-Secreted TNFα Induces Emergency Myelopoiesis and Myeloid-Derived Suppressor Cell Differentiation in Cancer. Cancer Res. 2019, 79, 346–359. [Google Scholar] [CrossRef] [Green Version]
  242. Keskinov, A.A.; Shurin, M.R. Myeloid regulatory cells in tumor spreading and metastasis. Immunobiology 2015, 220, 236–242. [Google Scholar] [CrossRef]
  243. Salminen, A.; Kauppinen, A.; Kaarniranta, K. AMPK activation inhibits the functions of myeloid-derived suppressor cells (MDSC): Impact on cancer and aging. J. Mol. Med. (Berl.) 2019, 97, 1049–1064. [Google Scholar] [CrossRef] [Green Version]
  244. Bruger, A.M.; Dorhoi, A.; Esendagli, G.; Barczyk-Kahlert, K.; van der Bruggen, P.; Lipoldova, M.; Perecko, T.; Santibanez, J.; Saraiva, M.; Van Ginderachter, J.A.; et al. How to measure the immunosuppressive activity of MDSC: Assays, problems and potential solutions. Cancer Immunol. Immunother. 2019, 68, 631–644. [Google Scholar] [CrossRef]
  245. Zeng, Y.; Hahn, S.; Stokes, J.; Hoffman, E.A.; Schmelz, M.; Proytcheva, M.; Chernoff, J.; Katsanis, E. Pak2 regulates myeloid-derived suppressor cell development in mice. Blood Adv. 2017, 1, 1923–1933. [Google Scholar] [CrossRef] [Green Version]
  246. Fleet, J.C.; Burcham, G.N.; Calvert, R.D.; Elzey, B.D.; Ratliff, T.L. 1α, 25 Dihydroxyvitamin D (1,25(OH)(2)D) inhibits the T cell suppressive function of myeloid derived suppressor cells (MDSC). J. Steroid Biochem. Mol. Biol. 2020, 198, 105557. [Google Scholar] [CrossRef] [PubMed]
  247. Finn, O.J.; Ochoa, A.C. Editorial: Myeloid Derived Suppressor Cells as Disease Modulators. Front. Immunol. 2020, 11, 90. [Google Scholar] [CrossRef] [PubMed]
  248. Boros, P.; Ochando, J.; Zeher, M. Myeloid derived suppressor cells and autoimmunity. Hum. Immunol. 2016, 77, 631–636. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  249. Medina, E.; Hartl, D. Myeloid-Derived Suppressor Cells in Infection: A General Overview. J. Innate Immun. 2018, 10, 407–413. [Google Scholar] [CrossRef] [PubMed]
  250. Li, B.H.; Garstka, M.A.; Li, Z.F. Chemokines and their receptors promoting the recruitment of myeloid-derived suppressor cells into the tumor. Mol. Immunol. 2020, 117, 201–215. [Google Scholar] [CrossRef] [PubMed]
  251. Ouzounova, M.; Lee, E.; Piranlioglu, R.; El Andaloussi, A.; Kolhe, R.; Demirci, M.F.; Marasco, D.; Asm, I.; Chadli, A.; Hassan, K.A.; et al. Monocytic and granulocytic myeloid derived suppressor cells differentially regulate spatiotemporal tumour plasticity during metastatic cascade. Nat. Commun. 2017, 8, 14979. [Google Scholar] [CrossRef]
  252. Veglia, F.; Perego, M.; Gabrilovich, D. Myeloid-derived suppressor cells coming of age. Nat. Immunol. 2018, 19, 108–119. [Google Scholar] [CrossRef] [PubMed]
  253. Boldin, M.P.; Taganov, K.D.; Rao, D.S.; Yang, L.; Zhao, J.L.; Kalwani, M.; Garcia-Flores, Y.; Luong, M.; Devrekanli, A.; Xu, J.; et al. miR-146a is a significant brake on autoimmunity, myeloproliferation, and cancer in mice. J. Exp. Med. 2011, 208, 1189–1201. [Google Scholar] [CrossRef] [PubMed]
  254. Liu, Q.; Zhang, M.; Jiang, X.; Zhang, Z.; Dai, L.; Min, S.; Wu, X.; He, Q.; Liu, J.; Zhang, Y.; et al. miR-223 suppresses differentiation of tumor-induced CD11b+ Gr1+ myeloid-derived suppressor cells from bone marrow cells. Int. J. Cancer 2011, 129, 2662–2673. [Google Scholar] [CrossRef] [PubMed]
  255. Wu, C.; Muroski, M.E.; Miska, J.; Lee-Chang, C.; Shen, Y.; Rashidi, A.; Zhang, P.; Xiao, T.; Han, Y.; Lopez-Rosas, A.; et al. Repolarization of myeloid derived suppressor cells via magnetic nanoparticles to promote radiotherapy for glioma treatment. Nanomedicine 2019, 16, 126–137. [Google Scholar] [CrossRef] [PubMed]
  256. Shirota, H.; Tross, D.; Klinman, D.M. CpG Oligonucleotides as Cancer Vaccine Adjuvants. Vaccines 2015, 3, 390–407. [Google Scholar] [CrossRef] [Green Version]
  257. Lee, W.C.; Hsu, P.Y.; Hsu, H.Y. Stem cell factor produced by tumor cells expands myeloid-derived suppressor cells in mice. Sci. Rep. 2020, 10, 11257. [Google Scholar] [CrossRef]
  258. Kao, J.; Ko, E.C.; Eisenstein, S.; Sikora, A.G.; Fu, S.; Chen, S.H. Targeting immune suppressing myeloid-derived suppressor cells in oncology. Crit. Rev. Oncol. Hematol. 2011, 77, 12–19. [Google Scholar] [CrossRef] [Green Version]
  259. Shao, B.; Wei, X.; Luo, M.; Yu, J.; Tong, A.; Ma, X.; Ye, T.; Deng, H.; Sang, Y.; Liang, X.; et al. Inhibition of A20 expression in tumor microenvironment exerts anti-tumor effect through inducing myeloid-derived suppressor cells apoptosis. Sci. Rep. 2015, 5, 16437. [Google Scholar] [CrossRef] [Green Version]
  260. Fujii, H.; Shin-Ya, M.; Takeda, S.; Hashimoto, Y.; Mukai, S.A.; Sawada, S.; Adachi, T.; Akiyoshi, K.; Miki, T.; Mazda, O. Cycloamylose-nanogel drug delivery system-mediated intratumor silencing of the vascular endothelial growth factor regulates neovascularization in tumor microenvironment. Cancer Sci. 2014, 105, 1616–1625. [Google Scholar] [CrossRef] [Green Version]
  261. Ni, J.; Galani, I.E.; Cerwenka, A.; Schirrmacher, V.; Fournier, P. Antitumor vaccination by Newcastle Disease Virus Hemagglutinin-Neuraminidase plasmid DNA application: Changes in tumor microenvironment and activation of innate anti-tumor immunity. Vaccine 2011, 29, 1185–1193. [Google Scholar] [CrossRef]
  262. Principe, M.; Ceruti, P.; Shih, N.Y.; Chattaragada, M.S.; Rolla, S.; Conti, L.; Bestagno, M.; Zentilin, L.; Yang, S.H.; Migliorini, P.; et al. Targeting of surface alpha-enolase inhibits the invasiveness of pancreatic cancer cells. Oncotarget 2015, 6, 11098–11113. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  263. Cappello, P.; Rolla, S.; Chiarle, R.; Principe, M.; Cavallo, F.; Perconti, G.; Feo, S.; Giovarelli, M.; Novelli, F. Vaccination with ENO1 DNA prolongs survival of genetically engineered mice with pancreatic cancer. Gastroenterology 2013, 144, 1098–1106. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  264. Arndt, C.; Bachmann, M.; Bergmann, R.; Berndt, N.; Feldmann, A.; Koristka, S. Theranostic CAR T cell targeting: A brief review. J. Labelled Comp. Radiopharm. 2019, 62, 533–540. [Google Scholar] [CrossRef]
  265. Newick, K.; O’Brien, S.; Sun, J.; Kapoor, V.; Maceyko, S.; Lo, A.; Puré, E.; Moon, E.; Albelda, S.M. Augmentation of CAR T-cell Trafficking and Antitumor Efficacy by Blocking Protein Kinase A Localization. Cancer Immunol. Res. 2016, 4, 541–551. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  266. Darowski, D.; Jost, C.; Stubenrauch, K.; Wessels, U.; Benz, J.; Ehler, A.; Freimoser-Grundschober, A.; Brünker, P.; Mössner, E.; Umaña, P.; et al. P329G-CAR-J: A novel Jurkat-NFAT-based CAR-T reporter system recognizing the P329G Fc mutation. Protein Eng. Des. Sel. 2019, 32, 207–218. [Google Scholar] [CrossRef] [PubMed]
  267. Chung, S.H.; Hughes, G.; Koffman, B.; Turtle, C.J.; Maloney, D.G.; Acharya, U.H. Not so crystal clear: Observations from a case of crystalline arthritis with cytokine release syndrome (CRS) after chimeric antigen receptor (CAR)-T cell therapy. Bone Marrow Transplant. 2019, 54, 632–634. [Google Scholar] [CrossRef]
  268. Rohrs, J.A.; Siegler, E.L.; Wang, P.; Finley, S.D. ERK Activation in CAR T Cells Is Amplified by CD28-Mediated Increase in CD3ζ Phosphorylation. iScience 2020, 23, 101023. [Google Scholar] [CrossRef]
  269. Kintz, H.; Nylen, E.; Barber, A. Inclusion of Dap10 or 4–1BB costimulation domains in the chPD1 receptor enhances anti-tumor efficacy of T cells in murine models of lymphoma and melanoma. Cell Immunol. 2020, 351, 104069. [Google Scholar] [CrossRef]
  270. Li, Y.; Hermanson, D.L.; Moriarity, B.S.; Kaufman, D.S. Human iPSC-Derived Natural Killer Cells Engineered with Chimeric Antigen Receptors Enhance Anti-tumor Activity. Cell Stem Cell 2018, 23, 181–192. [Google Scholar] [CrossRef] [Green Version]
  271. Strohl, W.R.; Naso, M. Bispecific T-Cell Redirection versus Chimeric Antigen Receptor (CAR)-T Cells as Approaches to Kill Cancer Cells. Antibodies 2019, 8, 41. [Google Scholar] [CrossRef] [Green Version]
  272. Oelsner, S.; Friede, M.E.; Zhang, C.; Wagner, J.; Badura, S.; Bader, P.; Ullrich, E.; Ottmann, O.G.; Klingemann, H.; Tonn, T.; et al. Continuously expanding CAR NK-92 cells display selective cytotoxicity against B-cell leukemia and lymphoma. Cytotherapy 2017, 19, 235–249. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  273. Hu, W.; Wang, G.; Huang, D.; Sui, M.; Xu, Y. Cancer Immunotherapy Based on Natural Killer Cells: Current Progress and New Opportunities. Front. Immunol. 2019, 10, 1205. [Google Scholar] [CrossRef] [PubMed]
  274. Oberschmidt, O.; Kloess, S.; Koehl, U. Redirected Primary Human Chimeric Antigen Receptor Natural Killer Cells As an “Off-the-Shelf Immunotherapy” for Improvement in Cancer Treatment. Front. Immunol. 2017, 8, 654. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  275. Sievers, N.M.; Dörrie, J.; Schaft, N. CARs: Beyond T Cells and T Cell-Derived Signaling Domains. Int. J. Mol. Sci. 2020, 21, 3525. [Google Scholar] [CrossRef]
  276. Hirayama, A.V.; Turtle, C.J. Toxicities of CD19 CAR-T cell immunotherapy. Am. J. Hematol. 2019, 94, S42–S49. [Google Scholar] [CrossRef] [Green Version]
  277. Maude, S.L.; Laetsch, T.W.; Buechner, J.; Rives, S.; Boyer, M.; Bittencourt, H.; Bader, P.; Verneris, M.R.; Stefanski, H.E.; Myers, G.D.; et al. Tisagenlecleucel in Children and Young Adults with B-Cell Lymphoblastic Leukemia. N. Engl. J. Med. 2018, 378, 439–448. [Google Scholar] [CrossRef]
  278. Locke, F.L.; Neelapu, S.S.; Bartlett, N.L.; Siddiqi, T.; Chavez, J.C.; Hosing, C.M.; Ghobadi, A.; Budde, L.E.; Bot, A.; Rossi, J.M.; et al. Phase 1 Results of ZUMA-1: A Multicenter Study of KTE-C19 Anti-CD19 CAR T Cell Therapy in Refractory Aggressive Lymphoma. Mol. Ther. 2017, 25, 285–295. [Google Scholar] [CrossRef] [Green Version]
  279. Belay, Y.; Yirdaw, K.; Enawgaw, B. Tumor Lysis Syndrome in Patients with Hematological Malignancies. J. Oncol. 2017, 2017, 9684909. [Google Scholar] [CrossRef]
  280. Shimabukuro-Vornhagen, A.; Gödel, P.; Subklewe, M.; Stemmler, H.J.; Schlößer, H.A.; Schlaak, M.; Kochanek, M.; Böll, B.; von Bergwelt-Baildon, M.S. Cytokine release syndrome. J. Immunother. Cancer 2018, 6, 56. [Google Scholar] [CrossRef] [Green Version]
  281. Giavridis, T.; van der Stegen, S.J.C.; Eyquem, J.; Hamieh, M.; Piersigilli, A.; Sadelain, M. CAR T cell-induced cytokine release syndrome is mediated by macrophages and abated by IL-1 blockade. Nat. Med. 2018, 24, 731–738. [Google Scholar] [CrossRef]
  282. Cervantes, E.V.; Boucher, J.C.; Lee, S.B.; Spitler, K.; Reid, K.; Davila, M.L. MDSC Suppression of CAR T Cells Can be Reduced By Targeted Signaling Disruption. Blood 2019, 134, 4438. [Google Scholar] [CrossRef]
  283. Burga, R.A.; Thorn, M.; Point, G.R.; Guha, P.; Nguyen, C.T.; Licata, L.A.; DeMatteo, R.P.; Ayala, A.; Joseph Espat, N.; Junghans, R.P.; et al. Liver myeloid-derived suppressor cells expand in response to liver metastases in mice and inhibit the anti-tumor efficacy of anti-CEA CAR-T. Cancer Immunol. Immunother. 2015, 64, 817–829. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  284. Wang, Z.; Liu, Y.; Zhang, Y.; Shang, Y.; Gao, Q. MDSC-decreasing chemotherapy increases the efficacy of cytokine-induced killer cell immunotherapy in metastatic renal cell carcinoma and pancreatic cancer. Oncotarget 2016, 7, 4760–4769. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  285. Crotti, C.; Agape, E.; Becciolini, A.; Biggioggero, M.; Favalli, E.G. Targeting Granulocyte-Monocyte Colony-Stimulating Factor Signaling in Rheumatoid Arthritis: Future Prospects. Drugs 2019, 79, 1741–1755. [Google Scholar] [CrossRef]
  286. Alsaab, H.O.; Sau, S.; Alzhrani, R.; Tatiparti, K.; Bhise, K.; Kashaw, S.K.; Iyer, A.K. PD-1 and PD-L1 Checkpoint Signaling Inhibition for Cancer Immunotherapy: Mechanism, Combinations, and Clinical Outcome. Front. Pharmacol. 2017, 8, 561. [Google Scholar] [CrossRef]
  287. Fultang, L.; Panetti, S.; Ng, M.; Collins, P.; Graef, S.; Rizkalla, N.; Booth, S.; Lenton, R.; Noyvert, B.; Shannon-Lowe, C.; et al. MDSC targeting with Gemtuzumab ozogamicin restores T cell immunity and immunotherapy against cancers. EBioMedicine 2019, 47, 235–246. [Google Scholar] [CrossRef] [Green Version]
  288. Wang, H.; Ye, X.; Ju, Y.; Cai, Z.; Wang, X.; Du, P.; Zhang, M.; Li, Y.; Cai, J. Minicircle DNA-Mediated CAR T Cells Targeting CD44 Suppressed Hepatocellular Carcinoma Both in vitro and in vivo. Onco Targets Ther. 2020, 13, 3703–3716. [Google Scholar] [CrossRef]
  289. Wu, T.; Dai, Y. Tumor microenvironment and therapeutic response. Cancer Lett. 2017, 387, 61–68. [Google Scholar] [CrossRef]
  290. Hanahan, D.; Coussens, L.M. Accessories to the crime: Functions of cells recruited to the tumor microenvironment. Cancer Cell 2012, 21, 309–322. [Google Scholar] [CrossRef] [Green Version]
  291. Chen, D.S.; Mellman, I. Elements of cancer immunity and the cancer-immune set point. Nature 2017, 541, 321–330. [Google Scholar] [CrossRef]
  292. Beatty, G.L.; Gladney, W.L. Immune Escape Mechanisms as a Guide for Cancer Immunotherapy. Clin. Cancer Res. 2015, 21, 687. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  293. Östman, A. The tumor microenvironment controls drug sensitivity. Nat. Med. 2012, 18, 1332–1334. [Google Scholar] [CrossRef] [PubMed]
  294. Chen, X.; Song, E. Turning foes to friends: Targeting cancer-associated fibroblasts. Nat. Rev. Drug Discov. 2019, 18, 99–115. [Google Scholar] [CrossRef]
  295. Qian, B.-Z.; Pollard, J.W. Macrophage Diversity Enhances Tumor Progression and Metastasis. Cell 2010, 141, 39–51. [Google Scholar] [CrossRef] [Green Version]
  296. Pathria, P.; Louis, T.L.; Varner, J.A. Targeting Tumor-Associated Macrophages in Cancer. Trends Immunol. 2019, 40, 310–327. [Google Scholar] [CrossRef] [PubMed]
  297. Prenen, H.; Mazzone, M. Tumor-associated macrophages: A short compendium. Cell. Mol. Life Sci. 2019, 76, 1447–1458. [Google Scholar] [CrossRef]
  298. Swiecki, M.; Colonna, M. The multifaceted biology of plasmacytoid dendritic cells. Nat. Rev. Immunol. 2015, 15, 471–485. [Google Scholar] [CrossRef]
  299. Anderson, K.G.; Stromnes, I.M.; Greenberg, P.D. Obstacles Posed by the Tumor Microenvironment to T cell Activity: A Case for Synergistic Therapies. Cancer Cell 2017, 31, 311–325. [Google Scholar] [CrossRef] [Green Version]
  300. Badalamenti, G.; Fanale, D.; Incorvaia, L.; Barraco, N.; Listì, A.; Maragliano, R.; Vincenzi, B.; Calò, V.; Iovanna, J.L.; Bazan, V.; et al. Role of tumor-infiltrating lymphocytes in patients with solid tumors: Can a drop dig a stone? Cell Immunol. 2019, 343, 103753. [Google Scholar] [CrossRef]
  301. Warburg, O. The Metabolism of Carcinoma Cells. J. Cancer Res. 1925, 9, 148. [Google Scholar] [CrossRef] [Green Version]
  302. Ferreira, L.M.R. Cancer metabolism: The Warburg effect today. Exp. Mol. Pathol. 2010, 89, 372–380. [Google Scholar] [CrossRef] [PubMed]
  303. Wilson, W.R.; Hay, M.P. Targeting hypoxia in cancer therapy. Nat. Rev. Cancer 2011, 11, 393–410. [Google Scholar] [CrossRef] [PubMed]
  304. Gialeli, C.; Theocharis, A.D.; Karamanos, N.K. Roles of matrix metalloproteinases in cancer progression and their pharmacological targeting. FEBS J. 2011, 278, 16–27. [Google Scholar] [CrossRef] [PubMed]
  305. Kuppusamy, P.; Li, H.; Ilangovan, G.; Cardounel, A.J.; Zweier, J.L.; Yamada, K.; Krishna, M.C.; Mitchell, J.B. Noninvasive Imaging of Tumor Redox Status and Its Modification by Tissue Glutathione Levels. Cancer Res. 2002, 62, 307. [Google Scholar] [PubMed]
  306. Reuter, S.; Gupta, S.C.; Chaturvedi, M.M.; Aggarwal, B.B. Oxidative stress, inflammation, and cancer: How are they linked? Free Radic. Biol. Med. 2010, 49, 1603–1616. [Google Scholar] [CrossRef] [Green Version]
  307. Hager, S.; Wagner, E. Bioresponsive polyplexes - chemically programmed for nucleic acid delivery. Expert Opin. Drug Deliv. 2018, 15, 1067–1083. [Google Scholar] [CrossRef]
  308. Maeda, H. Toward a full understanding of the EPR effect in primary and metastatic tumors as well as issues related to its heterogeneity. Adv. Drug Deliv. Rev. 2015, 91, 3–6. [Google Scholar] [CrossRef]
  309. Ruoslahti, E. Peptides as targeting elements and tissue penetration devices for nanoparticles. Adv. Mater. 2012, 24, 3747–3756. [Google Scholar] [CrossRef]
  310. Ruoslahti, E. Tumor penetrating peptides for improved drug delivery. Adv. Drug Deliv. Rev. 2017, 110–111, 3–12. [Google Scholar] [CrossRef] [Green Version]
  311. Ramsey, J.D.; Flynn, N.H. Cell-penetrating peptides transport therapeutics into cells. Pharmacol. Ther. 2015, 154, 78–86. [Google Scholar] [CrossRef] [Green Version]
  312. Lächelt, U.; Wagner, E. Nucleic Acid Therapeutics Using Polyplexes: A Journey of 50 Years (and Beyond). Chem. Rev. 2015, 115, 11043–11078. [Google Scholar] [CrossRef] [PubMed]
  313. Berraondo, P.; Sanmamed, M.F.; Ochoa, M.C.; Etxeberria, I.; Aznar, M.A.; Pérez-Gracia, J.L.; Rodríguez-Ruiz, M.E.; Ponz-Sarvise, M.; Castañón, E.; Melero, I. Cytokines in clinical cancer immunotherapy. Br. J. Cancer 2019, 120, 6–15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  314. Cao, L.; Kulmburg, P.; Veelken, H.; Mackensen, A.; Mézes, B.; Lindemann, A.; Mertelsmann, R.; Rosenthal, F.M. Cytokine gene transfer in cancer therapy. Stem Cells 1998, 16, 251–260. [Google Scholar] [CrossRef] [PubMed]
  315. Parmiani, G.; Rivoltini, L.; Andreola, G.; Carrabba, M. Cytokines in cancer therapy. Immunol. Lett. 2000, 74, 41–44. [Google Scholar] [CrossRef]
  316. Conlon, K.C.; Miljkovic, M.D.; Waldmann, T.A. Cytokines in the Treatment of Cancer. J. Interferon Cytokine Res. 2019, 39, 6–21. [Google Scholar] [CrossRef]
  317. Golomb, H.M.; Jacobs, A.; Fefer, A.; Ozer, H.; Thompson, J.; Portlock, C.; Ratain, M.; Golde, D.; Vardiman, J.; Burke, J.S. Alpha-2 interferon therapy of hairy-cell leukemia: A multicenter study of 64 patients. J. Clin. Oncol. 1986, 4, 900–905. [Google Scholar] [CrossRef]
  318. Antony, G.K.; Dudek, A.Z. Interleukin 2 in Cancer Therapy. Curr. Med. Chem. 2010, 17, 3297–3302. [Google Scholar] [CrossRef]
  319. Schreiber, S.; Kämpgen, E.; Wagner, E.; Pirkhammer, D.; Trcka, J.; Korschan, H.; Lindemann, A.; Dorffner, R.; Kittler, H.; Kasteliz, F.; et al. Immunotherapy of metastatic malignant melanoma by a vaccine consisting of autologous interleukin 2-transfected cancer cells: Outcome of a phase I study. Hum. Gene Ther. 1999, 10, 983–993. [Google Scholar] [CrossRef]
  320. Gansbacher, B.; Houghton, A.; Livingston, P.; Minasian, L.; Rosenthal, F.; Gilboa, E.; Oettgen, H.; Steffens, T.; Yang, S.Y.; Wong, G. A Pilot Study of Immunization with HLA-A2 Matched Allogeneic Melanoma Cells That Secrete Interleukin-2 in Patients with Metastatic Melanoma. Hum. Gene Ther. 1992, 3, 677–690. [Google Scholar] [CrossRef]
  321. Osanto, S.; Brouwenstÿn, N.; Vaessen, N.; Figdor, C.G.; Melief, C.J.; Schrier, P.I. Immunization with interleukin-2 transfected melanoma cells. A phase I-II study in patients with metastatic melanoma. Hum. Gene Ther. 1993, 4, 323–330. [Google Scholar] [CrossRef]
  322. Bowman, L.C.; Grossmann, M.; Rill, D.; Brown, M.; Zhong, W.Y.; Alexander, B.; Leimig, T.; Coustan-Smith, E.; Campana, D.; Jenkins, J.; et al. Interleukin-2 gene-modified allogeneic tumor cells for treatment of relapsed neuroblastoma. Hum. Gene Ther. 1998, 9, 1303–1311. [Google Scholar] [CrossRef] [PubMed]
  323. Kali, A. TNFerade, an innovative cancer immunotherapeutic. Indian J. Pharmacol. 2015, 47, 479–483. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  324. Kircheis, R.; Wagner, E. Technology evaluation: TNFerade, GenVec. Curr. Opin. Mol. Ther. 2003, 5, 437–447. [Google Scholar] [PubMed]
  325. Chiocca, E.A.; Yu, J.S.; Lukas, R.V.; Solomon, I.H.; Ligon, K.L.; Nakashima, H.; Triggs, D.A.; Reardon, D.A.; Wen, P.; Stopa, B.M.; et al. Regulatable interleukin-12 gene therapy in patients with recurrent high-grade glioma: Results of a phase 1 trial. Sci. Transl. Med. 2019, 11. [Google Scholar] [CrossRef] [PubMed]
  326. Le, D.T.; Lutz, E.; Uram, J.N.; Sugar, E.A.; Onners, B.; Solt, S.; Zheng, L.; Diaz, L.A., Jr.; Donehower, R.C.; Jaffee, E.M.; et al. Evaluation of ipilimumab in combination with allogeneic pancreatic tumor cells transfected with a GM-CSF gene in previously treated pancreatic cancer. J. Immunother. 2013, 36, 382–389. [Google Scholar] [CrossRef] [Green Version]
  327. Le, D.T.; Wang-Gillam, A.; Picozzi, V.; Greten, T.F.; Crocenzi, T.; Springett, G.; Morse, M.; Zeh, H.; Cohen, D.; Fine, R.L.; et al. Safety and survival with GVAX pancreas prime and Listeria Monocytogenes-expressing mesothelin (CRS-207) boost vaccines for metastatic pancreatic cancer. J. Clin. Oncol. 2015, 33, 1325–1333. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  328. Le, D.T.; Picozzi, V.J.; Ko, A.H.; Wainberg, Z.A.; Kindler, H.; Wang-Gillam, A.; Oberstein, P.; Morse, M.A.; Zeh, H.J., III; Weekes, C.; et al. Results from a Phase IIb, Randomized, Multicenter Study of GVAX Pancreas and CRS-207 Compared with Chemotherapy in Adults with Previously Treated Metastatic Pancreatic Adenocarcinoma (ECLIPSE Study). Clin. Cancer Res. 2019, 25, 5493–5502. [Google Scholar] [CrossRef]
  329. Tsujikawa, T.; Crocenzi, T.; Durham, J.N.; Sugar, E.A.; Wu, A.A.; Onners, B.; Nauroth, J.M.; Anders, R.A.; Fertig, E.J.; Laheru, D.A.; et al. Evaluation of Cyclophosphamide/GVAX Pancreas Followed by Listeria-Mesothelin (CRS-207) with or without Nivolumab in Patients with Pancreatic Cancer. Clin. Cancer Res. 2020. [Google Scholar] [CrossRef] [Green Version]
  330. Duplisea, J.J.; Mokkapati, S.; Plote, D.; Schluns, K.S.; McConkey, D.J.; Yla-Herttuala, S.; Parker, N.R.; Dinney, C.P. The development of interferon-based gene therapy for BCG unresponsive bladder cancer: From bench to bedside. World J. Urol. 2019, 37, 2041–2049. [Google Scholar] [CrossRef]
  331. Nemunaitis, J.; Dillman, R.O.; Schwarzenberger, P.O.; Senzer, N.; Cunningham, C.; Cutler, J.; Tong, A.; Kumar, P.; Pappen, B.; Hamilton, C.; et al. Phase II study of belagenpumatucel-L, a transforming growth factor beta-2 antisense gene-modified allogeneic tumor cell vaccine in non-small-cell lung cancer. J. Clin. Oncol. 2006, 24, 4721–4730. [Google Scholar] [CrossRef]
  332. Nemunaitis, J.; Nemunaitis, M.; Senzer, N.; Snitz, P.; Bedell, C.; Kumar, P.; Pappen, B.; Maples, P.B.; Shawler, D.; Fakhrai, H. Phase II trial of Belagenpumatucel-L, a TGF-beta2 antisense gene modified allogeneic tumor vaccine in advanced non small cell lung cancer (NSCLC) patients. Cancer Gene Ther. 2009, 16, 620–624. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  333. Giaccone, G.; Bazhenova, L.A.; Nemunaitis, J.; Tan, M.; Juhász, E.; Ramlau, R.; van den Heuvel, M.M.; Lal, R.; Kloecker, G.H.; Eaton, K.D.; et al. A phase III study of belagenpumatucel-L, an allogeneic tumour cell vaccine, as maintenance therapy for non-small cell lung cancer. Eur. J. Cancer 2015, 51, 2321–2329. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  334. Xu, L.; Song, X.; Su, L.; Zheng, Y.; Li, R.; Sun, J. New therapeutic strategies based on IL-2 to modulate Treg cells for autoimmune diseases. Int. Immunopharmacol. 2019, 72, 322–329. [Google Scholar] [CrossRef] [PubMed]
  335. Kircheis, R.; Küpcü, Z.; Wallner, G.; Wagner, E. Cytokine gene-modified tumor cells for prophylactic and therapeutic vaccination: IL-2, IFN-gamma, or combination IL-2 + IFN-gamma. Cytokines Cell. Mol. Ther. 1998, 4, 95–103. [Google Scholar]
  336. Rosenberg, S.A.; Anderson, W.F.; Blaese, M.R.; Ettinghausen, S.E.; Hwu, P.; Karp, S.E.; Kasid, A.; Mule, J.J.; Parkinson, D.R.; Salo, J.C.; et al. Immunization of Cancer Patients Using Autologous Cancer Cells Modified by Insertion of the Gene for Interleukin-2 (National Institutes of Health). Hum. Gene Ther. 1992, 3, 75–90. [Google Scholar] [CrossRef]
  337. Kircheis, R.; Küpcü, Z.; Wallner, G.; Rössler, V.; Schweighoffer, T.; Wagner, E. Interleukin-2 gene-modified allogeneic melanoma cell vaccines can induce cross-protection against syngeneic tumors in mice. Cancer Gene Ther. 2000, 7, 870–878. [Google Scholar] [CrossRef] [Green Version]
  338. Wagner, E.; Zatloukal, K.; Cotten, M.; Kirlappos, H.; Mechtler, K.; Curiel, D.T.; Birnstiel, M.L. Coupling of adenovirus to transferrin-polylysine/DNA complexes greatly enhances receptor-mediated gene delivery and expression of transfected genes. Proc. Natl. Acad. Sci. USA 1992, 89, 6099–6103. [Google Scholar] [CrossRef] [Green Version]
  339. Vile, R.; Miller, N.; Chernajovsky, Y.; Hart, I. A comparison of the properties of different retroviral vectors containing the murine tyrosinase promoter to achieve transcriptionally targeted expression of the HSVtk or IL-2 genes. Gene Ther. 1994, 1, 307–316. [Google Scholar]
  340. He, P.; Tang, Z.Y.; Liu, B.B.; Ye, S.L.; Liu, Y.K. The targeted expression of the human interleukin-2/interferon alpha2b fused gene in alpha-fetoprotein-expressing hepatocellular carcinoma cells. J. Cancer Res. Clin. Oncol. 1999, 125, 77–82. [Google Scholar] [CrossRef]
  341. Chaurasiya, S.; Hew, P.; Crosley, P.; Sharon, D.; Potts, K.; Agopsowicz, K.; Long, M.; Shi, C.; Hitt, M.M. Breast cancer gene therapy using an adenovirus encoding human IL-2 under control of mammaglobin promoter/enhancer sequences. Cancer Gene Ther. 2016, 23, 178–187. [Google Scholar] [CrossRef]
  342. Herman, J.M.; Wild, A.T.; Wang, H.; Tran, P.T.; Chang, K.J.; Taylor, G.E.; Donehower, R.C.; Pawlik, T.M.; Ziegler, M.A.; Cai, H.; et al. Randomized phase III multi-institutional study of TNFerade biologic with fluorouracil and radiotherapy for locally advanced pancreatic cancer: Final results. J. Clin. Oncol. 2013, 31, 886–894. [Google Scholar] [CrossRef] [PubMed]
  343. Bottermann, M.; Foss, S.; van Tienen, L.M.; Vaysburd, M.; Cruickshank, J.; O’Connell, K.; Clark, J.; Mayes, K.; Higginson, K.; Hirst, J.C.; et al. TRIM21 mediates antibody inhibition of adenovirus-based gene delivery and vaccination. Proc. Natl. Acad. Sci. USA 2018, 115, 10440–10445. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  344. Kircheis, R.; Ostermann, E.; Wolschek, M.F.; Lichtenberger, C.; Magin-Lachmann, C.; Wightman, L.; Kursa, M.; Wagner, E. Tumor-targeted gene delivery of tumor necrosis factor-α induces tumor necrosis and tumor regression without systemic toxicity. Cancer Gene Ther. 2002, 9, 673–680. [Google Scholar] [CrossRef] [PubMed]
  345. Su, B.; Cengizeroglu, A.; Farkasova, K.; Viola, J.R.; Anton, M.; Ellwart, J.W.; Haase, R.; Wagner, E.; Ogris, M. Systemic TNFα Gene Therapy Synergizes With Liposomal Doxorubicine in the Treatment of Metastatic Cancer. Mol. Ther. 2013, 21, 300–308. [Google Scholar] [CrossRef] [Green Version]
  346. Russ, V.; Günther, M.; Halama, A.; Ogris, M.; Wagner, E. Oligoethylenimine-grafted polypropylenimine dendrimers as degradable and biocompatible synthetic vectors for gene delivery. J. Controlled Release 2008, 132, 131–140. [Google Scholar] [CrossRef]
  347. Schäfer, A.; Pahnke, A.; Schaffert, D.; van Weerden, W.M.; de Ridder, C.M.; Rödl, W.; Vetter, A.; Spitzweg, C.; Kraaij, R.; Wagner, E.; et al. Disconnecting the yin and yang relation of epidermal growth factor receptor (EGFR)-mediated delivery: A fully synthetic, EGFR-targeted gene transfer system avoiding receptor activation. Hum. Gene Ther. 2011, 22, 1463–1473. [Google Scholar] [CrossRef]
  348. Tandle, A.; Hanna, E.; Lorang, D.; Hajitou, A.; Moya, C.A.; Pasqualini, R.; Arap, W.; Adem, A.; Starker, E.; Hewitt, S.; et al. Tumor vasculature-targeted delivery of tumor necrosis factor-α*. Cancer 2009, 115, 128–139. [Google Scholar] [CrossRef]
  349. Yuan, Z.; Syrkin, G.; Adem, A.; Geha, R.; Pastoriza, J.; Vrikshajanani, C.; Smith, T.; Quinn, T.J.; Alemu, G.; Cho, H.; et al. Blockade of inhibitors of apoptosis (IAPs) in combination with tumor-targeted delivery of tumor necrosis factor-α leads to synergistic antitumor activity. Cancer Gene Ther. 2013, 20, 46–56. [Google Scholar] [CrossRef]
  350. Quinn, T.J.; Healy, N.; Sara, A.; Maggi, E.; Claros, C.S.; Kabarriti, R.; Scandiuzzi, L.; Liu, L.; Gorecka, J.; Adem, A.; et al. Preclinical evaluation of radiation and systemic, RGD-targeted, adeno-associated virus phage-TNF gene therapy in a mouse model of spontaneously metastatic melanoma. Cancer Gene Ther. 2017, 24, 13–19. [Google Scholar] [CrossRef]
  351. Lasek, W.; Zagożdżon, R.; Jakobisiak, M. Interleukin 12: Still a promising candidate for tumor immunotherapy? Cancer Immunol. Immunother. 2014, 63, 419–435. [Google Scholar] [CrossRef] [Green Version]
  352. Voest, E.E.; Kenyon, B.M.; O’Reilly, M.S.; Truitt, G.; D’Amato, R.J.; Folkman, J. Inhibition of angiogenesis in vivo by interleukin 12. J. Natl. Cancer Inst. 1995, 87, 581–586. [Google Scholar] [CrossRef] [PubMed]
  353. Dias, S.; Boyd, R.; Balkwill, F. IL-12 regulates VEGF and MMPs in a murine breast cancer model. Int. J. Cancer 1998, 78, 361–365. [Google Scholar] [CrossRef]
  354. Del Vecchio, M.; Bajetta, E.; Canova, S.; Lotze, M.T.; Wesa, A.; Parmiani, G.; Anichini, A. Interleukin-12: Biological properties and clinical application. Clin. Cancer Res. 2007, 13, 4677–4685. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  355. Cohen, J. IL-12 Deaths: Explanation and a Puzzle. Science 1995, 270, 908. [Google Scholar] [CrossRef] [PubMed]
  356. Leonard, J.P.; Sherman, M.L.; Fisher, G.L.; Buchanan, L.J.; Larsen, G.; Atkins, M.B.; Sosman, J.A.; Dutcher, J.P.; Vogelzang, N.J.; Ryan, J.L. Effects of single-dose interleukin-12 exposure on interleukin-12-associated toxicity and interferon-gamma production. Blood 1997, 90, 2541–2548. [Google Scholar] [PubMed]
  357. Pasche, N.; Neri, D. Immunocytokines: A novel class of potent armed antibodies. Drug Discov. Today 2012, 17, 583–590. [Google Scholar] [CrossRef] [PubMed]
  358. Rudman, S.M.; Jameson, M.B.; McKeage, M.J.; Savage, P.; Jodrell, D.I.; Harries, M.; Acton, G.; Erlandsson, F.; Spicer, J.F. A phase 1 study of AS1409, a novel antibody-cytokine fusion protein, in patients with malignant melanoma or renal cell carcinoma. Clin. Cancer. Res. 2011, 17, 1998–2005. [Google Scholar] [CrossRef] [Green Version]
  359. Hernandez-Alcoceba, R.; Poutou, J.; Ballesteros-Briones, M.C.; Smerdou, C. Gene therapy approaches against cancer using in vivo and ex vivo gene transfer of interleukin-12. Immunotherapy 2016, 8, 179–198. [Google Scholar] [CrossRef]
  360. Tugues, S.; Burkhard, S.H.; Ohs, I.; Vrohlings, M.; Nussbaum, K.; vom Berg, J.; Kulig, P.; Becher, B. New insights into IL-12-mediated tumor suppression. Cell Death Differ. 2015, 22, 237–246. [Google Scholar] [CrossRef] [Green Version]
  361. Sangro, B.; Mazzolini, G.; Ruiz, J.; Herraiz, M.; Quiroga, J.; Herrero, I.; Benito, A.; Larrache, J.; Pueyo, J.; Subtil, J.C.; et al. Phase I Trial of Intratumoral Injection of an Adenovirus Encoding Interleukin-12 for Advanced Digestive Tumors. J. Clin. Oncol. 2004, 22, 1389–1397. [Google Scholar] [CrossRef]
  362. Triozzi, P.L.; Strong, T.V.; Bucy, R.P.; Allen, K.O.; Carlisle, R.R.; Moore, S.E.; Lobuglio, A.F.; Conry, R.M. Intratumoral administration of a recombinant canarypox virus expressing interleukin 12 in patients with metastatic melanoma. Hum. Gene Ther. 2005, 16, 91–100. [Google Scholar] [CrossRef] [PubMed]
  363. Triozzi, P.L.; Allen, K.O.; Carlisle, R.R.; Craig, M.; LoBuglio, A.F.; Conry, R.M. Phase I study of the intratumoral administration of recombinant canarypox viruses expressing B7.1 and interleukin 12 in patients with metastatic melanoma. Clin. Cancer. Res. 2005, 11, 4168–4175. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  364. Linette, G.P.; Hamid, O.; Whitman, E.D.; Nemunaitis, J.J.; Chesney, J.; Agarwala, S.S.; Starodub, A.; Barrett, J.A.; Marsh, A.; Martell, L.A.; et al. A phase I open-label study of Ad-RTS-hIL-12, an adenoviral vector engineered to express hIL-12 under the control of an oral activator ligand, in subjects with unresectable stage III/IV melanoma. J. Clin. Oncol. 2013, 31, 3022. [Google Scholar] [CrossRef]
  365. Quetglas, J.I.; Labiano, S.; Aznar, M.Á.; Bolaños, E.; Azpilikueta, A.; Rodriguez, I.; Casales, E.; Sánchez-Paulete, A.R.; Segura, V.; Smerdou, C.; et al. Virotherapy with a Semliki Forest Virus–Based Vector Encoding IL12 Synergizes with PD-1/PD-L1 Blockade. Cancer Immunol. Res. 2015, 3, 449. [Google Scholar] [CrossRef] [Green Version]
  366. Yang, X.; Yu, X.; Wei, Y. Lentiviral delivery of novel fusion protein IL12/FasTI for cancer immune/gene therapy. PLoS ONE 2018, 13, e0201100. [Google Scholar] [CrossRef]
  367. Lucas, M.L.; Heller, L.; Coppola, D.; Heller, R. IL-12 plasmid delivery by in vivo electroporation for the successful treatment of established subcutaneous B16.F10 melanoma. Mol. Ther. 2002, 5, 668–675. [Google Scholar] [CrossRef]
  368. Heinzerling, L.; Burg, G.; Dummer, R.; Maier, T.; Oberholzer, P.A.; Schultz, J.; Elzaouk, L.; Pavlovic, J.; Moelling, K. Intratumoral injection of DNA encoding human interleukin 12 into patients with metastatic melanoma: Clinical efficacy. Hum. Gene Ther. 2005, 16, 35–48. [Google Scholar] [CrossRef] [Green Version]
  369. Mahvi, D.M.; Henry, M.B.; Albertini, M.R.; Weber, S.; Meredith, K.; Schalch, H.; Rakhmilevich, A.; Hank, J.; Sondel, P. Intratumoral injection of IL-12 plasmid DNA--results of a phase I/IB clinical trial. Cancer Gene Ther. 2007, 14, 717–723. [Google Scholar] [CrossRef]
  370. Daud, A.I.; DeConti, R.C.; Andrews, S.; Urbas, P.; Riker, A.I.; Sondak, V.K.; Munster, P.N.; Sullivan, D.M.; Ugen, K.E.; Messina, J.L.; et al. Phase I trial of interleukin-12 plasmid electroporation in patients with metastatic melanoma. J. Clin. Oncol. 2008, 26, 5896–5903. [Google Scholar] [CrossRef] [Green Version]
  371. Cutrera, J.; King, G.; Jones, P.; Kicenuik, K.; Gumpel, E.; Xia, X.; Li, S. Safety and efficacy of tumor-targeted interleukin 12 gene therapy in treated and non-treated, metastatic lesions. Curr. Gene Ther. 2015, 15, 44–54. [Google Scholar] [CrossRef]
  372. Cemazar, M.; Ambrozic Avgustin, J.; Pavlin, D.; Sersa, G.; Poli, A.; Krhac Levacic, A.; Tesic, N.; Lampreht Tratar, U.; Rak, M.; Tozon, N. Efficacy and safety of electrochemotherapy combined with peritumoral IL-12 gene electrotransfer of canine mast cell tumours. Vet. Comp. Oncol. 2017, 15, 641–654. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  373. Cicchelero, L.; Denies, S.; Haers, H.; Vanderperren, K.; Stock, E.; Van Brantegem, L.; de Rooster, H.; Sanders, N.N. Intratumoural interleukin 12 gene therapy stimulates the immune system and decreases angiogenesis in dogs with spontaneous cancer. Vet. Comp. Oncol. 2017, 15, 1187–1205. [Google Scholar] [CrossRef] [PubMed]
  374. Rodrigo-Garzón, M.; Berraondo, P.; Ochoa, L.; Zulueta, J.J.; González-Aseguinolaza, G. Antitumoral efficacy of DNA nanoparticles in murine models of lung cancer and pulmonary metastasis. Cancer Gene Ther. 2010, 17, 20–27. [Google Scholar] [CrossRef] [PubMed]
  375. Anwer, K.; Barnes, M.N.; Fewell, J.; Lewis, D.H.; Alvarez, R.D. Phase-I clinical trial of IL-12 plasmid/lipopolymer complexes for the treatment of recurrent ovarian cancer. Gene Ther. 2010, 17, 360–369. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  376. Anwer, K.; Kelly, F.J.; Chu, C.; Fewell, J.G.; Lewis, D.; Alvarez, R.D. Phase I trial of a formulated IL-12 plasmid in combination with carboplatin and docetaxel chemotherapy in the treatment of platinum-sensitive recurrent ovarian cancer. Gynecol. Oncol. 2013, 131, 169–173. [Google Scholar] [CrossRef] [PubMed]
  377. Men, K.; Huang, R.; Zhang, X.; Zhang, R.; Zhang, Y.; He, M.; Tong, R.; Yang, L.; Wei, Y.; Duan, X. Local and Systemic Delivery of Interleukin-12 Gene by Cationic Micelles for Cancer Immunogene Therapy. J. Biomed. Nanotechnol. 2018, 14, 1719–1730. [Google Scholar] [CrossRef] [PubMed]
  378. Chmielewski, M.; Abken, H. CAR T cells transform to trucks: Chimeric antigen receptor-redirected T cells engineered to deliver inducible IL-12 modulate the tumour stroma to combat cancer. Cancer Immunol. Immunother. 2012, 61, 1269–1277. [Google Scholar] [CrossRef]
  379. Hodi, F.S.; Lee, S.; McDermott, D.F.; Rao, U.N.; Butterfield, L.H.; Tarhini, A.A.; Leming, P.; Puzanov, I.; Shin, D.; Kirkwood, J.M. Ipilimumab plus sargramostim vs ipilimumab alone for treatment of metastatic melanoma: A randomized clinical trial. JAMA 2014, 312, 1744–1753. [Google Scholar] [CrossRef] [Green Version]
  380. Sterner, R.M.; Cox, M.J.; Sakemura, R.; Kenderian, S.S. Using CRISPR/Cas9 to Knock Out GM-CSF in CAR-T Cells. J. Vis. Exp. 2019. [Google Scholar] [CrossRef]
  381. Teicher, B.A.; Fricker, S.P. CXCL12 (SDF-1)/CXCR4 pathway in cancer. Clin. Cancer Res. 2010, 16, 2927–2931. [Google Scholar] [CrossRef] [Green Version]
  382. Meng, W.; Xue, S.; Chen, Y. The role of CXCL12 in tumor microenvironment. Gene 2018, 641, 105–110. [Google Scholar] [CrossRef] [PubMed]
  383. Feig, C.; Jones, J.O.; Kraman, M.; Wells, R.J.; Deonarine, A.; Chan, D.S.; Connell, C.M.; Roberts, E.W.; Zhao, Q.; Caballero, O.L.; et al. Targeting CXCL12 from FAP-expressing carcinoma-associated fibroblasts synergizes with anti-PD-L1 immunotherapy in pancreatic cancer. Proc. Natl. Acad. Sci. USA 2013, 110, 20212–20217. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  384. Zhong, C.; Wang, J.; Li, B.; Xiang, H.; Ultsch, M.; Coons, M.; Wong, T.; Chiang, N.Y.; Clark, S.; Clark, R.; et al. Development and preclinical characterization of a humanized antibody targeting CXCL12. Clin. Cancer Res. 2013, 19, 4433–4445. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  385. Goodwin, T.J.; Zhou, Y.; Musetti, S.N.; Liu, R.; Huang, L. Local and transient gene expression primes the liver to resist cancer metastasis. Sci. Transl. Med. 2016, 8, 364ra153. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  386. Miao, L.; Li, J.; Liu, Q.; Feng, R.; Das, M.; Lin, C.M.; Goodwin, T.J.; Dorosheva, O.; Liu, R.; Huang, L. Transient and Local Expression of Chemokine and Immune Checkpoint Traps To Treat Pancreatic Cancer. ACS Nano 2017, 11, 8690–8706. [Google Scholar] [CrossRef] [PubMed]
  387. Hu, Y.; Haynes, M.T.; Wang, Y.; Liu, F.; Huang, L. A highly efficient synthetic vector: Nonhydrodynamic delivery of DNA to hepatocyte nuclei in vivo. ACS Nano 2013, 7, 5376–5384. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  388. Weis, S.M.; Cheresh, D.A. Tumor angiogenesis: Molecular pathways and therapeutic targets. Nat. Med. 2011, 17, 1359–1370. [Google Scholar] [CrossRef] [PubMed]
  389. Ott, P.A.; Hodi, F.S.; Buchbinder, E.I. Inhibition of Immune Checkpoints and Vascular Endothelial Growth Factor as Combination Therapy for Metastatic Melanoma: An Overview of Rationale, Preclinical Evidence, and Initial Clinical Data. Front. Oncol. 2015, 5, 202. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  390. Lockhart, A.C.; Rothenberg, M.L.; Dupont, J.; Cooper, W.; Chevalier, P.; Sternas, L.; Buzenet, G.; Koehler, E.; Sosman, J.A.; Schwartz, L.H.; et al. Phase I Study of Intravenous Vascular Endothelial Growth Factor Trap, Aflibercept, in Patients With Advanced Solid Tumors. J. Clin. Oncol. 2009, 28, 207–214. [Google Scholar] [CrossRef]
  391. Tarhini, A.A.; Frankel, P.; Margolin, K.A.; Christensen, S.; Ruel, C.; Shipe-Spotloe, J.; Gandara, D.R.; Chen, A.; Kirkwood, J.M. Aflibercept (VEGF Trap) in Inoperable Stage III or Stage IV Melanoma of Cutaneous or Uveal Origin. Clin. Cancer Res. 2011, 17, 6574. [Google Scholar] [CrossRef] [Green Version]
  392. Ferrara, N.; Hillan, K.J.; Novotny, W. Bevacizumab (Avastin), a humanized anti-VEGF monoclonal antibody for cancer therapy. Biochem. Biophys. Res. Commun. 2005, 333, 328–335. [Google Scholar] [CrossRef] [PubMed]
  393. Melosky, B.; Reardon, D.A.; Nixon, A.B.; Subramanian, J.; Bair, A.H.; Jacobs, I. Bevacizumab biosimilars: Scientific justification for extrapolation of indications. Future Oncol. 2018, 14, 2507–2520. [Google Scholar] [CrossRef] [PubMed]
  394. Vennepureddy, A.; Singh, P.; Rastogi, R.; Atallah, J.P.; Terjanian, T. Evolution of ramucirumab in the treatment of cancer - A review of literature. J. Oncol. Pharm. Pract. 2017, 23, 525–539. [Google Scholar] [CrossRef] [PubMed]
  395. Tekade, R.K.; Tekade, M.; Kesharwani, P.; D’Emanuele, A. RNAi-combined nano-chemotherapeutics to tackle resistant tumors. Drug Discov. Today 2016, 21, 1761–1774. [Google Scholar] [CrossRef]
  396. Kanazawa, T.; Sugawara, K.; Tanaka, K.; Horiuchi, S.; Takashima, Y.; Okada, H. Suppression of tumor growth by systemic delivery of anti-VEGF siRNA with cell-penetrating peptide-modified MPEG-PCL nanomicelles. Eur. J. Pharm. Biopharm. 2012, 81, 470–477. [Google Scholar] [CrossRef]
  397. Egorova, A.; Shubina, A.; Sokolov, D.; Selkov, S.; Baranov, V.; Kiselev, A. CXCR4-targeted modular peptide carriers for efficient anti-VEGF siRNA delivery. Int. J. Pharm. 2016, 515, 431–440. [Google Scholar] [CrossRef]
  398. Chung, J.Y.; Ul Ain, Q.; Lee, H.L.; Kim, S.M.; Kim, Y.H. Enhanced Systemic Anti-Angiogenic siVEGF Delivery Using PEGylated Oligo-d-arginine. Mol. Pharm. 2017, 14, 3059–3068. [Google Scholar] [CrossRef]
  399. Lee, Y.W.; Hwang, Y.E.; Lee, J.Y.; Sohn, J.H.; Sung, B.H.; Kim, S.C. VEGF siRNA Delivery by a Cancer-Specific Cell-Penetrating Peptide. J. Microbiol. Biotechnol. 2018, 28, 367–374. [Google Scholar] [CrossRef] [Green Version]
  400. Schiffelers, R.M.; Ansari, A.; Xu, J.; Zhou, Q.; Tang, Q.; Storm, G.; Molema, G.; Lu, P.Y.; Scaria, P.V.; Woodle, M.C. Cancer siRNA therapy by tumor selective delivery with ligand-targeted sterically stabilized nanoparticle. Nucleic Acids Res. 2004, 32, e149. [Google Scholar] [CrossRef]
  401. Kim, S.H.; Jeong, J.H.; Lee, S.H.; Kim, S.W.; Park, T.G. Local and systemic delivery of VEGF siRNA using polyelectrolyte complex micelles for effective treatment of cancer. J. Controlled Release 2008, 129, 107–116. [Google Scholar] [CrossRef]
  402. Jiang, G.; Park, K.; Kim, J.; Kim, K.S.; Hahn, S.K. Target specific intracellular delivery of siRNA/PEI-HA complex by receptor mediated endocytosis. Mol. Pharm. 2009, 6, 727–737. [Google Scholar] [CrossRef] [PubMed]
  403. Zhao, Z.; Li, Y.; Shukla, R.; Liu, H.; Jain, A.; Barve, A.; Cheng, K. Development of a Biocompatible Copolymer Nanocomplex to Deliver VEGF siRNA for Triple Negative Breast Cancer. Theranostics 2019, 9, 4508–4524. [Google Scholar] [CrossRef] [PubMed]
  404. Kim, M.G.; Jo, S.D.; Yhee, J.Y.; Lee, B.S.; Lee, S.J.; Park, S.G.; Kang, S.W.; Kim, S.H.; Jeong, J.H. Synergistic anti-tumor effects of bevacizumab and tumor targeted polymerized VEGF siRNA nanoparticles. Biochem. Biophys. Res. Commun. 2017, 489, 35–41. [Google Scholar] [CrossRef] [PubMed]
  405. Yang, Z.Z.; Li, J.Q.; Wang, Z.Z.; Dong, D.W.; Qi, X.R. Tumor-targeting dual peptides-modified cationic liposomes for delivery of siRNA and docetaxel to gliomas. Biomaterials 2014, 35, 5226–5239. [Google Scholar] [CrossRef] [PubMed]
  406. Li, F.; Wang, Y.; Chen, W.L.; Wang, D.D.; Zhou, Y.J.; You, B.G.; Liu, Y.; Qu, C.X.; Yang, S.D.; Chen, M.T.; et al. Co-delivery of VEGF siRNA and Etoposide for Enhanced Anti-angiogenesis and Anti-proliferation Effect via Multi-functional Nanoparticles for Orthotopic Non-Small Cell Lung Cancer Treatment. Theranostics 2019, 9, 5886–5898. [Google Scholar] [CrossRef] [PubMed]
  407. Conde, J.; Bao, C.; Tan, Y.; Cui, D.; Edelman, E.R.; Azevedo, H.S.; Byrne, H.J.; Artzi, N.; Tian, F. Dual targeted immunotherapy via in vivo delivery of biohybrid RNAi-peptide nanoparticles to tumour-associated macrophages and cancer cells. Adv. Funct. Mater. 2015, 25, 4183–4194. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  408. Sun, Q.; Wang, X.; Cui, C.; Li, J.; Wang, Y. Doxorubicin and anti-VEGF siRNA co-delivery via nano-graphene oxide for enhanced cancer therapy in vitro and in vivo. Int. J. Nanomed. 2018, 13, 3713–3728. [Google Scholar] [CrossRef] [Green Version]
  409. Akhurst, R.J.; Hata, A. Targeting the TGFβ signalling pathway in disease. Nat. Rev. Drug Discov. 2012, 11, 790–811. [Google Scholar] [CrossRef] [Green Version]
  410. Haque, S.; Morris, J.C. Transforming growth factor-β: A therapeutic target for cancer. Hum. Vaccin. Immunother. 2017, 13, 1741–1750. [Google Scholar] [CrossRef] [PubMed]
  411. Ahmadi, A.; Najafi, M.; Farhood, B.; Mortezaee, K. Transforming growth factor-β signaling: Tumorigenesis and targeting for cancer therapy. J. Cell. Physiol. 2019, 234, 12173–12187. [Google Scholar] [CrossRef]
  412. Xu, Z.; Wang, Y.; Zhang, L.; Huang, L. Nanoparticle-delivered transforming growth factor-β siRNA enhances vaccination against advanced melanoma by modifying tumor microenvironment. ACS Nano 2014, 8, 3636–3645. [Google Scholar] [CrossRef] [PubMed]
  413. Cao, Q.; Liu, F.; Ji, K.; Liu, N.; He, Y.; Zhang, W.; Wang, L. MicroRNA-381 inhibits the metastasis of gastric cancer by targeting TMEM16A expression. J. Exp. Clin. Cancer Res. 2017, 36, 29. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  414. Shu, Y.J.; Bao, R.F.; Jiang, L.; Wang, Z.; Wang, X.A.; Zhang, F.; Liang, H.B.; Li, H.F.; Ye, Y.Y.; Xiang, S.S.; et al. MicroRNA-29c-5p suppresses gallbladder carcinoma progression by directly targeting CPEB4 and inhibiting the MAPK pathway. Cell Death Differ. 2017, 24, 445–457. [Google Scholar] [CrossRef] [PubMed]
  415. Fang, F.; Huang, B.; Sun, S.; Xiao, M.; Guo, J.; Yi, X.; Cai, J.; Wang, Z. miR-27a inhibits cervical adenocarcinoma progression by downregulating the TGF-βRI signaling pathway. Cell Death Dis. 2018, 9, 395. [Google Scholar] [CrossRef]
  416. Schlingensiepen, R.; Goldbrunner, M.; Szyrach, M.N.; Stauder, G.; Jachimczak, P.; Bogdahn, U.; Schulmeyer, F.; Hau, P.; Schlingensiepen, K.H. Intracerebral and intrathecal infusion of the TGF-beta 2-specific antisense phosphorothioate oligonucleotide AP 12009 in rabbits and primates: Toxicology and safety. Oligonucleotides 2005, 15, 94–104. [Google Scholar] [CrossRef]
  417. Schlingensiepen, K.H.; Schlingensiepen, R.; Steinbrecher, A.; Hau, P.; Bogdahn, U.; Fischer-Blass, B.; Jachimczak, P. Targeted tumor therapy with the TGF-beta 2 antisense compound AP 12009. Cytokine Growth Factor Rev. 2006, 17, 129–139. [Google Scholar] [CrossRef]
  418. Schlingensiepen, K.H.; Jaschinski, F.; Lang, S.A.; Moser, C.; Geissler, E.K.; Schlitt, H.J.; Kielmanowicz, M.; Schneider, A. Transforming growth factor-beta 2 gene silencing with trabedersen (AP 12009) in pancreatic cancer. Cancer Sci. 2011, 102, 1193–1200. [Google Scholar] [CrossRef]
  419. Hau, P.; Jachimczak, P.; Schlingensiepen, R.; Schulmeyer, F.; Jauch, T.; Steinbrecher, A.; Brawanski, A.; Proescholdt, M.; Schlaier, J.; Buchroithner, J.; et al. Inhibition of TGF-beta2 with AP 12009 in recurrent malignant gliomas: From preclinical to phase I/II studies. Oligonucleotides 2007, 17, 201–212. [Google Scholar] [CrossRef]
  420. Nagaraj, N.S.; Datta, P.K. Targeting the transforming growth factor-beta signaling pathway in human cancer. Expert Opin. Investig. Drugs 2010, 19, 77–91. [Google Scholar] [CrossRef] [Green Version]
  421. Bogdahn, U.; Hau, P.; Stockhammer, G.; Venkataramana, N.K.; Mahapatra, A.K.; Suri, A.; Balasubramaniam, A.; Nair, S.; Oliushine, V.; Parfenov, V.; et al. Targeted therapy for high-grade glioma with the TGF-β2 inhibitor trabedersen: Results of a randomized and controlled phase IIb study. Neuro Oncol. 2011, 13, 132–142. [Google Scholar] [CrossRef] [Green Version]
  422. Zhu, J.; Liu, J.Q.; Shi, M.; Cheng, X.; Ding, M.; Zhang, J.C.; Davis, J.P.; Varikuti, S.; Satoskar, A.R.; Lu, L.; et al. IL-27 gene therapy induces depletion of Tregs and enhances the efficacy of cancer immunotherapy. JCI Insight 2018, 3. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  423. Hashimoto, H.; Ueda, R.; Narumi, K.; Heike, Y.; Yoshida, T.; Aoki, K. Type I IFN gene delivery suppresses regulatory T cells within tumors. Cancer Gene Ther. 2014, 21, 532–541. [Google Scholar] [CrossRef]
  424. Hirata, A.; Hashimoto, H.; Shibasaki, C.; Narumi, K.; Aoki, K. Intratumoral IFN-α gene delivery reduces tumor-infiltrating regulatory T cells through the downregulation of tumor CCL17 expression. Cancer Gene Ther. 2019, 26, 334–343. [Google Scholar] [CrossRef]
  425. Byrne, W.L.; Mills, K.H.G.; Lederer, J.A.; Sullivan, G.C. Targeting Regulatory T Cells in Cancer. Cancer Res. 2011, 71, 6915. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  426. Jacobs, J.F.M.; Nierkens, S.; Figdor, C.G.; de Vries, I.J.M.; Adema, G.J. Regulatory T cells in melanoma: The final hurdle towards effective immunotherapy? Lancet Oncol. 2012, 13, e32–e42. [Google Scholar] [CrossRef]
  427. Pfeffer, L.M.; Dinarello, C.A.; Herberman, R.B.; Williams, B.R.G.; Borden, E.C.; Bordens, R.; Walter, M.R.; Nagabhushan, T.L.; Trotta, P.P.; Pestka, S. Biological Properties of Recombinant α-Interferons: 40th Anniversary of the Discovery of Interferons. Cancer Res. 1998, 58, 2489. [Google Scholar] [PubMed]
  428. Iqbal Ahmed, C.M.; Johnson, D.E.; Demers, G.W.; Engler, H.; Howe, J.A.; Wills, K.N.; Wen, S.F.; Shinoda, J.; Beltran, J.; Nodelman, M.; et al. Interferon alpha2b gene delivery using adenoviral vector causes inhibition of tumor growth in xenograft models from a variety of cancers. Cancer Gene Ther. 2001, 8, 788–795. [Google Scholar] [CrossRef] [Green Version]
  429. Pardoll, D.M. The blockade of immune checkpoints in cancer immunotherapy. Nat. Rev. Cancer 2012, 12, 252–264. [Google Scholar] [CrossRef] [Green Version]
  430. Sadreddini, S.; Baradaran, B.; Aghebati-Maleki, A.; Sadreddini, S.; Shanehbandi, D.; Fotouhi, A.; Aghebati-Maleki, L. Immune checkpoint blockade opens a new way to cancer immunotherapy. J. Cell. Physiol. 2019, 234, 8541–8549. [Google Scholar] [CrossRef]
  431. Brunet, J.F.; Denizot, F.; Luciani, M.F.; Roux-Dosseto, M.; Suzan, M.; Mattei, M.G.; Golstein, P. A new member of the immunoglobulin superfamily--CTLA-4. Nature 1987, 328, 267–270. [Google Scholar] [CrossRef]
  432. Ishida, Y.; Agata, Y.; Shibahara, K.; Honjo, T. Induced expression of PD-1, a novel member of the immunoglobulin gene superfamily, upon programmed cell death. EMBO J. 1992, 11, 3887–3895. [Google Scholar] [CrossRef] [PubMed]
  433. Taams, L.S.; de Gruijl, T.D. Immune checkpoint inhibition: From molecules to clinical application. Clin. Exp. Immunol. 2020, 200, 105–107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  434. Chen, P.-L.; Roh, W.; Reuben, A.; Cooper, Z.A.; Spencer, C.N.; Prieto, P.A.; Miller, J.P.; Bassett, R.L.; Gopalakrishnan, V.; Wani, K.; et al. Analysis of Immune Signatures in Longitudinal Tumor Samples Yields Insight into Biomarkers of Response and Mechanisms of Resistance to Immune Checkpoint Blockade. Cancer Discov. 2016, 6, 827. [Google Scholar] [CrossRef] [Green Version]
  435. Jenkins, R.W.; Barbie, D.A.; Flaherty, K.T. Mechanisms of resistance to immune checkpoint inhibitors. Br. J. Cancer 2018, 118, 9–16. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  436. Barrueto, L.; Caminero, F.; Cash, L.; Makris, C.; Lamichhane, P.; Deshmukh, R.R. Resistance to Checkpoint Inhibition in Cancer Immunotherapy. Transl. Oncol. 2020, 13, 100738. [Google Scholar] [CrossRef]
  437. Kalbasi, A.; Ribas, A. Tumour-intrinsic resistance to immune checkpoint blockade. Nat. Rev. Immunol. 2020, 20, 25–39. [Google Scholar] [CrossRef]
  438. van Elsas, M.J.; van Hall, T.; van der Burg, S.H. Future Challenges in Cancer Resistance to Immunotherapy. Cancers 2020, 12, 935. [Google Scholar] [CrossRef] [Green Version]
  439. Ji, R.-R.; Chasalow, S.D.; Wang, L.; Hamid, O.; Schmidt, H.; Cogswell, J.; Alaparthy, S.; Berman, D.; Jure-Kunkel, M.; Siemers, N.O.; et al. An immune-active tumor microenvironment favors clinical response to ipilimumab. Cancer Immunol. Immunother. 2012, 61, 1019–1031. [Google Scholar] [CrossRef]
  440. Tumeh, P.C.; Harview, C.L.; Yearley, J.H.; Shintaku, I.P.; Taylor, E.J.M.; Robert, L.; Chmielowski, B.; Spasic, M.; Henry, G.; Ciobanu, V.; et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 2014, 515, 568–571. [Google Scholar] [CrossRef]
  441. Granier, C.; De Guillebon, E.; Blanc, C.; Roussel, H.; Badoual, C.; Colin, E.; Saldmann, A.; Gey, A.; Oudard, S.; Tartour, E. Mechanisms of action and rationale for the use of checkpoint inhibitors in cancer. ESMO Open 2017, 2, e000213. [Google Scholar] [CrossRef] [Green Version]
  442. Lamichhane, P.; Amin, N.P.; Agarwal, M.; Lamichhane, N. Checkpoint Inhibition: Will Combination with Radiotherapy and Nanoparticle-Mediated Delivery Improve Efficacy? Medicines 2018, 5, 114. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  443. Wang, D.Y.; Salem, J.-E.; Cohen, J.V.; Chandra, S.; Menzer, C.; Ye, F.; Zhao, S.; Das, S.; Beckermann, K.E.; Ha, L.; et al. Fatal Toxic Effects Associated With Immune Checkpoint Inhibitors: A Systematic Review and Meta-analysis. JAMA Oncol. 2018, 4, 1721–1728. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  444. Urwyler, P.; Earnshaw, I.; Bermudez, M.; Perucha, E.; Wu, W.; Ryan, S.; McDonald, L.; Karagiannis, S.N.; Taams, L.S.; Powell, N.; et al. Mechanisms of checkpoint inhibition-induced adverse events. Clin. Exp. Immunol. 2020, 200, 141–154. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  445. Pruitt, S.K.; Boczkowski, D.; de Rosa, N.; Haley, N.R.; Morse, M.A.; Tyler, D.S.; Dannull, J.; Nair, S. Enhancement of anti-tumor immunity through local modulation of CTLA-4 and GITR by dendritic cells. Eur. J. Immunol. 2011, 41, 3553–3563. [Google Scholar] [CrossRef] [Green Version]
  446. Goodwin, T.J.; Shen, L.; Hu, M.; Li, J.; Feng, R.; Dorosheva, O.; Liu, R.; Huang, L. Liver specific gene immunotherapies resolve immune suppressive ectopic lymphoid structures of liver metastases and prolong survival. Biomaterials 2017, 141, 260–271. [Google Scholar] [CrossRef]
  447. Song, W.; Shen, L.; Wang, Y.; Liu, Q.; Goodwin, T.J.; Li, J.; Dorosheva, O.; Liu, T.; Liu, R.; Huang, L. Synergistic and low adverse effect cancer immunotherapy by immunogenic chemotherapy and locally expressed PD-L1 trap. Nat. Commun. 2018, 9, 2237. [Google Scholar] [CrossRef] [PubMed]
  448. Teo, P.Y.; Yang, C.; Whilding, L.M.; Parente-Pereira, A.C.; Maher, J.; George, A.J.; Hedrick, J.L.; Yang, Y.Y.; Ghaem-Maghami, S. Ovarian cancer immunotherapy using PD-L1 siRNA targeted delivery from folic acid-functionalized polyethylenimine: Strategies to enhance T cell killing. Adv. Healthc. Mater. 2015, 4, 1180–1189. [Google Scholar] [CrossRef]
  449. Wang, D.; Wang, T.; Liu, J.; Yu, H.; Jiao, S.; Feng, B.; Zhou, F.; Fu, Y.; Yin, Q.; Zhang, P.; et al. Acid-Activatable Versatile Micelleplexes for PD-L1 Blockade-Enhanced Cancer Photodynamic Immunotherapy. Nano Lett. 2016, 16, 5503–5513. [Google Scholar] [CrossRef]
  450. Kwak, G.; Kim, D.; Nam, G.H.; Wang, S.Y.; Kim, I.S.; Kim, S.H.; Kwon, I.C.; Yeo, Y. Programmed Cell Death Protein Ligand-1 Silencing with Polyethylenimine-Dermatan Sulfate Complex for Dual Inhibition of Melanoma Growth. ACS Nano 2017, 11, 10135–10146. [Google Scholar] [CrossRef] [Green Version]
  451. Li, G.; Gao, Y.; Gong, C.; Han, Z.; Qiang, L.; Tai, Z.; Tian, J.; Gao, S. Dual-Blockade Immune Checkpoint for Breast Cancer Treatment Based on a Tumor-Penetrating Peptide Assembling Nanoparticle. ACS Appl. Mater. Interfaces 2019, 11, 39513–39524. [Google Scholar] [CrossRef]
  452. Zhou, Y.J.; Wan, W.J.; Tong, Y.; Chen, M.T.; Wang, D.D.; Wang, Y.; You, B.G.; Liu, Y.; Zhang, X.N. Stimuli-responsive nanoparticles for the codelivery of chemotherapeutic agents doxorubicin and siPD-L1 to enhance the antitumor effect. J. Biomed. Mater. Res. B Appl. Biomater. 2020, 108, 1710–1724. [Google Scholar] [CrossRef] [PubMed]
  453. Rupp, L.J.; Schumann, K.; Roybal, K.T.; Gate, R.E.; Ye, C.J.; Lim, W.A.; Marson, A. CRISPR/Cas9-mediated PD-1 disruption enhances anti-tumor efficacy of human chimeric antigen receptor T cells. Sci. Rep. 2017, 7, 737. [Google Scholar] [CrossRef] [PubMed]
  454. Hu, B.; Zou, Y.; Zhang, L.; Tang, J.; Niedermann, G.; Firat, E.; Huang, X.; Zhu, X. Nucleofection with Plasmid DNA for CRISPR/Cas9-Mediated Inactivation of Programmed Cell Death Protein 1 in CD133-Specific CAR T Cells. Hum. Gene. Ther. 2019, 30, 446–458. [Google Scholar] [CrossRef]
  455. Wing, J.B.; Tay, C.; Sakaguchi, S. Control of Regulatory T Cells by Co-signal Molecules. Adv. Exp. Med. Biol. 2019, 1189, 179–210. [Google Scholar] [CrossRef] [PubMed]
  456. Fukuhara, H.; Ino, Y.; Todo, T. Oncolytic virus therapy: A new era of cancer treatment at dawn. Cancer Sci. 2016, 107, 1373–1379. [Google Scholar] [CrossRef]
  457. Lan, Q.; Xia, S.; Wang, Q.; Xu, W.; Huang, H.; Jiang, S.; Lu, L. Development of oncolytic virotherapy: From genetic modification to combination therapy. Front. Med. 2020, 14, 160–184. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  458. Kaufman, H.L.; Kohlhapp, F.J.; Zloza, A. Oncolytic viruses: A new class of immunotherapy drugs. Nat. Rev. Drug Discov. 2015, 14, 642–662. [Google Scholar] [CrossRef] [PubMed]
  459. Marchini, A.; Scott, E.M.; Rommelaere, J. Overcoming Barriers in Oncolytic Virotherapy with HDAC Inhibitors and Immune Checkpoint Blockade. Viruses 2016, 8, 9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  460. Bommareddy, P.K.; Shettigar, M.; Kaufman, H.L. Integrating oncolytic viruses in combination cancer immunotherapy. Nat. Rev. Immunol. 2018, 18, 498–513. [Google Scholar] [CrossRef] [PubMed]
  461. Saha, D.; Wakimoto, H.; Rabkin, S.D. Oncolytic herpes simplex virus interactions with the host immune system. Curr. Opin. Virol. 2016, 21, 26–34. [Google Scholar] [CrossRef] [Green Version]
  462. Martuza, R.L.; Malick, A.; Markert, J.M.; Ruffner, K.L.; Coen, D.M. Experimental therapy of human glioma by means of a genetically engineered virus mutant. Science 1991, 252, 854–856. [Google Scholar] [CrossRef] [PubMed]
  463. Ganly, I.; Kirn, D.; Eckhardt, S.G.; Rodriguez, G.I.; Soutar, D.S.; Otto, R.; Robertson, A.G.; Park, O.; Gulley, M.L.; Heise, C.; et al. A Phase I Study of Onyx-015, an E1B Attenuated Adenovirus, Administered Intratumorally to Patients with Recurrent Head and Neck Cancer. Clin. Cancer Res. 2000, 6, 798. [Google Scholar] [PubMed]
  464. Aghi, M.; Martuza, R.L. Oncolytic viral therapies - the clinical experience. Oncogene 2005, 24, 7802–7816. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  465. Vacchelli, E.; Eggermont, A.; Sautès-Fridman, C.; Galon, J.; Zitvogel, L.; Kroemer, G.; Galluzzi, L. Trial watch. OncoImmunology 2013, 2, e24612. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  466. Miest, T.S.; Cattaneo, R. New viruses for cancer therapy: Meeting clinical needs. Nat. Rev. Microbiol. 2014, 12, 23–34. [Google Scholar] [CrossRef] [Green Version]
  467. Russell, S.J.; Peng, K.-W.; Bell, J.C. Oncolytic virotherapy. Nat. Biotechnol. 2012, 30, 658–670. [Google Scholar] [CrossRef] [Green Version]
  468. Peters, C.; Rabkin, S.D. Designing Herpes Viruses as Oncolytics. Mol. Ther. Oncolytics 2015, 2, 15010. [Google Scholar] [CrossRef]
  469. Achard, C.; Surendran, A.; Wedge, M.-E.; Ungerechts, G.; Bell, J.; Ilkow, C.S. Lighting a Fire in the Tumor Microenvironment Using Oncolytic Immunotherapy. EBioMedicine 2018, 31, 17–24. [Google Scholar] [CrossRef] [Green Version]
  470. Lemay, C.G.; Keller, B.A.; Edge, R.E.; Abei, M.; Bell, J.C. Oncolytic Viruses: The Best is Yet to Come. Curr. Cancer Drug Targets 2018, 18, 109–123. [Google Scholar] [CrossRef]
  471. Alberts, P.; Tilgase, A.; Rasa, A.; Bandere, K.; Venskus, D. The advent of oncolytic virotherapy in oncology: The Rigvir® story. Eur. J. Pharmacol. 2018, 837, 117–126. [Google Scholar] [CrossRef] [PubMed]
  472. Gong, J.; Sachdev, E.; Mita, A.C.; Mita, M.M. Clinical development of reovirus for cancer therapy: An oncolytic virus with immune-mediated antitumor activity. World J. Methodol. 2016, 6, 25–42. [Google Scholar] [CrossRef] [PubMed]
  473. Mahalingam, D.; Fountzilas, C.; Moseley, J.; Noronha, N.; Tran, H.; Chakrabarty, R.; Selvaggi, G.; Coffey, M.; Thompson, B.; Sarantopoulos, J. A phase II study of REOLYSIN(®) (pelareorep) in combination with carboplatin and paclitaxel for patients with advanced malignant melanoma. Cancer Chemother. Pharmacol. 2017, 79, 697–703. [Google Scholar] [CrossRef] [PubMed]
  474. Xia, Z.J.; Chang, J.H.; Zhang, L.; Jiang, W.Q.; Guan, Z.Z.; Liu, J.W.; Zhang, Y.; Hu, X.H.; Wu, G.H.; Wang, H.Q.; et al. Phase III randomized clinical trial of intratumoral injection of E1B gene-deleted adenovirus (H101) combined with cisplatin-based chemotherapy in treating squamous cell cancer of head and neck or esophagus. Ai Zheng 2004, 23, 1666–1670. [Google Scholar] [PubMed]
  475. Liang, M. Oncorine, the World First Oncolytic Virus Medicine and its Update in China. Curr. Cancer Drug Targets 2018, 18, 171–176. [Google Scholar] [CrossRef] [PubMed]
  476. Packiam Vignesh, T.; Campanile Alexa, N.; Barocas Daniel, A.; Chamie, K.; Davis, I.I.I.R.L.; Kader, A.K.; Lamm Donald, L.; Yeung Alex, W.; Steinberg Gary, D. MP13–19 a phase II/III trial of CG0070, an oncolytic adenovirus, for BCG-refractory non-muscle-invasive bladder cancer (NMIBC). J. Urol. 2016, 195, e142. [Google Scholar] [CrossRef]
  477. Andtbacka, R.H.; Kaufman, H.L.; Collichio, F.; Amatruda, T.; Senzer, N.; Chesney, J.; Delman, K.A.; Spitler, L.E.; Puzanov, I.; Agarwala, S.S.; et al. Talimogene Laherparepvec Improves Durable Response Rate in Patients With Advanced Melanoma. J. Clin. Oncol. 2015, 33, 2780–2788. [Google Scholar] [CrossRef]
  478. Harrington, K.J.; Puzanov, I.; Hecht, J.R.; Hodi, F.S.; Szabo, Z.; Murugappan, S.; Kaufman, H.L. Clinical development of talimogene laherparepvec (T-VEC): A modified herpes simplex virus type-1-derived oncolytic immunotherapy. Expert Rev. Anticancer Ther. 2015, 15, 1389–1403. [Google Scholar] [CrossRef]
  479. Patel, D.M.; Foreman, P.M.; Nabors, L.B.; Riley, K.O.; Gillespie, G.Y.; Markert, J.M. Design of a Phase I Clinical Trial to Evaluate M032, a Genetically Engineered HSV-1 Expressing IL-12, in Patients with Recurrent/Progressive Glioblastoma Multiforme, Anaplastic Astrocytoma, or Gliosarcoma. Hum. Gene Ther. Clin. Dev. 2016, 27, 69–78. [Google Scholar] [CrossRef]
  480. Todo, T.; Martuza, R.L.; Rabkin, S.D.; Johnson, P.A. Oncolytic herpes simplex virus vector with enhanced MHC class I presentation and tumor cell killing. Proc. Natl. Acad. Sci. USA 2001, 98, 6396–6401. [Google Scholar] [CrossRef] [Green Version]
  481. Ino, Y.; Todo, T. CLINICAL DEVELOPMENT OF A THIRD-GENERATION ONCOLYTIC HSV-1 (G47Δ) FOR MALIGNANT GLIOMA. Gene Ther. Regul. 2010, 05, 101–111. [Google Scholar] [CrossRef]
  482. Abou-Alfa, G.K.; Galle, P.R.; Chao, Y.; Brown, K.T.; Heo, J.; Borad, M.J.; Luca, A.; Pelusio, A.; Agathon, D.; Lusky, M.; et al. PHOCUS: A phase 3 randomized, open-label study comparing the oncolytic immunotherapy Pexa-Vec followed by sorafenib (SOR) vs SOR in patients with advanced hepatocellular carcinoma (HCC) without prior systemic therapy. J. Clin. Oncol. 2016, 34, TPS4146. [Google Scholar] [CrossRef]
  483. Saha, D.; Martuza, R.L.; Rabkin, S.D. Oncolytic herpes simplex virus immunovirotherapy in combination with immune checkpoint blockade to treat glioblastoma. Immunotherapy 2018, 10, 779–786. [Google Scholar] [CrossRef] [PubMed]
  484. Niemann, J.; Kühnel, F. Oncolytic viruses: Adenoviruses. Virus Genes 2017, 53, 700–706. [Google Scholar] [CrossRef] [PubMed]
  485. Yang, X.; Huang, B.; Deng, L.; Hu, Z. Progress in gene therapy using oncolytic vaccinia virus as vectors. J. Cancer Res. Clin. Oncol. 2018, 144, 2433–2440. [Google Scholar] [CrossRef] [PubMed]
  486. Hwang, T.-H.; Moon, A.; Burke, J.; Ribas, A.; Stephenson, J.; Breitbach, C.J.; Daneshmand, M.; De Silva, N.; Parato, K.; Diallo, J.-S.; et al. A Mechanistic Proof-of-concept Clinical Trial With JX-594, a Targeted Multi-mechanistic Oncolytic Poxvirus, in Patients With Metastatic Melanoma. Mol. Ther. 2011, 19, 1913–1922. [Google Scholar] [CrossRef] [Green Version]
  487. Breitbach, C.J.; Bell, J.C.; Hwang, T.H.; Kirn, D.H.; Burke, J. The emerging therapeutic potential of the oncolytic immunotherapeutic Pexa-Vec (JX-594). Oncolytic Virother. 2015, 4, 25–31. [Google Scholar] [CrossRef] [Green Version]
  488. Breitbach, C.J.; Parato, K.; Burke, J.; Hwang, T.H.; Bell, J.C.; Kirn, D.H. Pexa-Vec double agent engineered vaccinia: Oncolytic and active immunotherapeutic. Curr. Opin. Virol. 2015, 13, 49–54. [Google Scholar] [CrossRef]
  489. Bourhill, T.; Mori, Y.; Rancourt, D.E.; Shmulevitz, M.; Johnston, R.N. Going (Reo)Viral: Factors Promoting Successful Reoviral Oncolytic Infection. Viruses 2018, 10, 421. [Google Scholar] [CrossRef] [Green Version]
  490. Abdullahi, S.; Jäkel, M.; Behrend, S.J.; Steiger, K.; Topping, G.; Krabbe, T.; Colombo, A.; Sandig, V.; Schiergens, T.S.; Thasler, W.E.; et al. A Novel Chimeric Oncolytic Virus Vector for Improved Safety and Efficacy as a Platform for the Treatment of Hepatocellular Carcinoma. J. Virol. 2018, 92. [Google Scholar] [CrossRef] [Green Version]
  491. Ammi, R.; De Waele, J.; Willemen, Y.; Van Brussel, I.; Schrijvers, D.M.; Lion, E.; Smits, E.L. Poly(I:C) as cancer vaccine adjuvant: Knocking on the door of medical breakthroughs. Pharmacol. Ther. 2015, 146, 120–131. [Google Scholar] [CrossRef]
  492. Smith, M.; García-Martínez, E.; Pitter, M.R.; Fucikova, J.; Spisek, R.; Zitvogel, L.; Kroemer, G.; Galluzzi, L. Trial Watch: Toll-like receptor agonists in cancer immunotherapy. Oncoimmunology 2018, 7, e1526250. [Google Scholar] [CrossRef] [PubMed]
  493. Schwarz, T.F. Clinical update of the AS04-adjuvanted human papillomavirus-16/18 cervical cancer vaccine, Cervarix. Adv. Ther. 2009, 26, 983–998. [Google Scholar] [CrossRef] [PubMed]
  494. ‘Mac’ Cheever, M.A. Twelve immunotherapy drugs that could cure cancers. Immunol. Rev. 2008, 222, 357–368. [Google Scholar] [CrossRef] [PubMed]
  495. Bianchi, F.; Pretto, S.; Tagliabue, E.; Balsari, A.; Sfondrini, L. Exploiting poly(I:C) to induce cancer cell apoptosis. Cancer Biol. Ther. 2017, 18, 747–756. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  496. Salaun, B.; Coste, I.; Rissoan, M.C.; Lebecque, S.J.; Renno, T. TLR3 can directly trigger apoptosis in human cancer cells. J. Immunol. 2006, 176, 4894–4901. [Google Scholar] [CrossRef] [Green Version]
  497. Estornes, Y.; Toscano, F.; Virard, F.; Jacquemin, G.; Pierrot, A.; Vanbervliet, B.; Bonnin, M.; Lalaoui, N.; Mercier-Gouy, P.; Pachéco, Y.; et al. dsRNA induces apoptosis through an atypical death complex associating TLR3 to caspase-8. Cell Death Differ. 2012, 19, 1482–1494. [Google Scholar] [CrossRef] [Green Version]
  498. Feldman, S.; Hughes, W.T.; Darlington, R.W.; Kim, H.K. Evaluation of Topical Polyinosinic Acid-Polycytidylic Acid in Treatment of Localized Herpes Zoster in Children with Cancer: A Randomized, Double-Blind Controlled Study. Antimicrob. Agents Chemother. 1975, 8, 289. [Google Scholar] [CrossRef] [Green Version]
  499. Robinson, R.A.; DeVita, V.T.; Levy, H.B.; Baron, S.; Hubbard, S.P.; Levine, A.S. A Phase I–II Trial of Multiple-Dose Polyriboinosinic-Polyribocytidylic Acid in Patients With Leukemia or Solid Tumors. J. Natl. Cancer Inst. 1976, 57, 599–602. [Google Scholar] [CrossRef]
  500. Herr, H.W.; Kemeny, N.; Yagoda, A.; Whitmore, W.F., Jr. Poly I:C immunotherapy in patients with papillomas or superficial carcinomas of the bladder. Natl. Cancer Inst. Monogr. 1978, 325. [Google Scholar]
  501. Nordlund, J.J.; Wolff, S.M.; Levy, H.B. Inhibition of biologic activity of poly I: Poly C by human plasma. Proc. Soc. Exp. Biol. Med. 1970, 133, 439–444. [Google Scholar] [CrossRef]
  502. Levy, H.B.; Baer, G.; Baron, S.; Buckler, C.E.; Gibbs, C.J.; Iadarola, M.J.; London, W.T.; Rice, J. A Modified Polyriboinosinic-Polyribocytidylic Acid Complex That Induces Interferon in Primates. J. Infect. Dis. 1975, 132, 434–439. [Google Scholar] [CrossRef]
  503. Levine, A.S.; Sivulich, M.; Wiernik, P.H.; Levy, H.B. Initial clinical trials in cancer patients of polyriboinosinic-polyribocytidylic acid stabilized with poly-L-lysine, in carboxymethylcellulose [poly(ICLC)], a highly effective interferon inducer. Cancer Res. 1979, 39, 1645–1650. [Google Scholar]
  504. Patchett, A.L.; Tovar, C.; Corcoran, L.M.; Lyons, A.B.; Woods, G.M. The toll-like receptor ligands Hiltonol® (polyICLC) and imiquimod effectively activate antigen-specific immune responses in Tasmanian devils (Sarcophilus harrisii). Dev. Comp. Immunol. 2017, 76, 352–360. [Google Scholar] [CrossRef] [PubMed]
  505. Rodríguez-Ruiz, M.E.; Perez-Gracia, J.L.; Rodríguez, I.; Alfaro, C.; Oñate, C.; Pérez, G.; Gil-Bazo, I.; Benito, A.; Inogés, S.; López-Diaz de Cerio, A.; et al. Combined immunotherapy encompassing intratumoral poly-ICLC, dendritic-cell vaccination and radiotherapy in advanced cancer patients. Ann. Oncol. 2018, 29, 1312–1319. [Google Scholar] [CrossRef] [PubMed]
  506. Hafner, A.M.; Corthésy, B.; Merkle, H.P. Particulate formulations for the delivery of poly(I:C) as vaccine adjuvant. Adv. Drug Deliv. Rev. 2013, 65, 1386–1399. [Google Scholar] [CrossRef] [PubMed]
  507. Shir, A.; Ogris, M.; Wagner, E.; Levitzki, A. EGF receptor-targeted synthetic double-stranded RNA eliminates glioblastoma, breast cancer, and adenocarcinoma tumors in mice. PLoS Med. 2006, 3, e6. [Google Scholar] [CrossRef]
  508. Shir, A.; Ogris, M.; Roedl, W.; Wagner, E.; Levitzki, A. EGFR-Homing dsRNA Activates Cancer-Targeted Immune Response and Eliminates Disseminated EGFR-Overexpressing Tumors in Mice. Clin. Cancer Res. 2011, 17, 1033. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  509. Schaffert, D.; Kiss, M.; Rödl, W.; Shir, A.; Levitzki, A.; Ogris, M.; Wagner, E. Poly(I:C)-mediated tumor growth suppression in EGF-receptor overexpressing tumors using EGF-polyethylene glycol-linear polyethylenimine as carrier. Pharm. Res. 2011, 28, 731–741. [Google Scholar] [CrossRef]
  510. Abourbeh, G.; Shir, A.; Mishani, E.; Ogris, M.; Rödl, W.; Wagner, E.; Levitzki, A. PolyIC GE11 polyplex inhibits EGFR-overexpressing tumors. IUBMB Life 2012, 64, 324–330. [Google Scholar] [CrossRef] [Green Version]
  511. Lächelt, U.; Wittmann, V.; Müller, K.; Edinger, D.; Kos, P.; Höhn, M.; Wagner, E. Synthetic polyglutamylation of dual-functional MTX ligands for enhanced combined cytotoxicity of poly(I:C) nanoplexes. Mol. Pharm. 2014, 11, 2631–2639. [Google Scholar] [CrossRef]
  512. Krieg, A.M.; Yi, A.K.; Matson, S.; Waldschmidt, T.J.; Bishop, G.A.; Teasdale, R.; Koretzky, G.A.; Klinman, D.M. CpG motifs in bacterial DNA trigger direct B-cell activation. Nature 1995, 374, 546–549. [Google Scholar] [CrossRef] [PubMed]
  513. Hanagata, N. CpG oligodeoxynucleotide nanomedicines for the prophylaxis or treatment of cancers, infectious diseases, and allergies. Int. J. Nanomedicine 2017, 12, 515–531. [Google Scholar] [CrossRef] [Green Version]
  514. Adamus, T.; Kortylewski, M. The revival of CpG oligonucleotide-based cancer immunotherapies. Contemp. Oncol. (Pozn) 2018, 22, 56–60. [Google Scholar] [CrossRef] [PubMed]
  515. Krieg, A.M. Development of TLR9 agonists for cancer therapy. J. Clin. Invest. 2007, 117, 1184–1194. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  516. Zhang, Q.; Hossain, D.M.; Duttagupta, P.; Moreira, D.; Zhao, X.; Won, H.; Buettner, R.; Nechaev, S.; Majka, M.; Zhang, B.; et al. Serum-resistant CpG-STAT3 decoy for targeting survival and immune checkpoint signaling in acute myeloid leukemia. Blood 2016, 127, 1687–1700. [Google Scholar] [CrossRef] [PubMed]
  517. Nikitczuk, K.P.; Schloss, R.S.; Yarmush, M.L.; Lattime, E.C. PLGA-polymer encapsulating tumor antigen and CpG DNA administered into the tumor microenvironment elicits a systemic antigen-specific IFN-γ response and enhances survival. J. Cancer Ther. 2013, 4, 280–290. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  518. Cheng, T.; Miao, J.; Kai, D.; Zhang, H. Polyethylenimine-Mediated CpG Oligodeoxynucleotide Delivery Stimulates Bifurcated Cytokine Induction. ACS Biomater. Sci. Eng. 2018, 4, 1013–1018. [Google Scholar] [CrossRef]
  519. Kwong, B.; Liu, H.; Irvine, D.J. Induction of potent anti-tumor responses while eliminating systemic side effects via liposome-anchored combinatorial immunotherapy. Biomaterials 2011, 32, 5134–5147. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  520. Kwon, S.; Kim, D.; Park, B.K.; Wu, G.; Park, M.C.; Ha, Y.W.; Kwon, H.J.; Lee, Y. Induction of immunological memory response by vaccination with TM4SF5 epitope-CpG-DNA-liposome complex in a mouse hepatocellular carcinoma model. Oncol. Rep. 2013, 29, 735–740. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  521. Kwon, S.; Kim, Y.E.; Park, J.A.; Kim, D.S.; Kwon, H.J.; Lee, Y. Therapeutic effect of a TM4SF5-specific peptide vaccine against colon cancer in a mouse model. BMB Rep. 2014, 47, 215–220. [Google Scholar] [CrossRef]
  522. Zhao, D.; Alizadeh, D.; Zhang, L.; Liu, W.; Farrukh, O.; Manuel, E.; Diamond, D.J.; Badie, B. Carbon nanotubes enhance CpG uptake and potentiate antiglioma immunity. Clin. Cancer Res. 2011, 17, 771–782. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  523. Zhou, S.; Hashida, Y.; Kawakami, S.; Mihara, J.; Umeyama, T.; Imahori, H.; Murakami, T.; Yamashita, F.; Hashida, M. Preparation of immunostimulatory single-walled carbon nanotube/CpG DNA complexes and evaluation of their potential in cancer immunotherapy. Int. J. Pharm. 2014, 471, 214–223. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  524. Lee, I.H.; Kwon, H.K.; An, S.; Kim, D.; Kim, S.; Yu, M.K.; Lee, J.H.; Lee, T.S.; Im, S.H.; Jon, S. Imageable antigen-presenting gold nanoparticle vaccines for effective cancer immunotherapy in vivo. Angew. Chem. Int. Ed. Engl. 2012, 51, 8800–8805. [Google Scholar] [CrossRef] [PubMed]
  525. Lin, A.Y.; Almeida, J.P.; Bear, A.; Liu, N.; Luo, L.; Foster, A.E.; Drezek, R.A. Gold nanoparticle delivery of modified CpG stimulates macrophages and inhibits tumor growth for enhanced immunotherapy. PLoS ONE 2013, 8, e63550. [Google Scholar] [CrossRef] [Green Version]
  526. Cha, B.G.; Jeong, J.H.; Kim, J. Extra-Large Pore Mesoporous Silica Nanoparticles Enabling Co-Delivery of High Amounts of Protein Antigen and Toll-like Receptor 9 Agonist for Enhanced Cancer Vaccine Efficacy. ACS Cent. Sci. 2018, 4, 484–492. [Google Scholar] [CrossRef] [Green Version]
  527. Schüller, V.J.; Heidegger, S.; Sandholzer, N.; Nickels, P.C.; Suhartha, N.A.; Endres, S.; Bourquin, C.; Liedl, T. Cellular immunostimulation by CpG-sequence-coated DNA origami structures. ACS Nano 2011, 5, 9696–9702. [Google Scholar] [CrossRef] [Green Version]
  528. Wang, C.; Sun, W.; Wright, G.; Wang, A.Z.; Gu, Z. Inflammation-Triggered Cancer Immunotherapy by Programmed Delivery of CpG and Anti-PD1 Antibody. Adv. Mater. 2016, 28, 8912–8920. [Google Scholar] [CrossRef] [Green Version]
  529. Guo, L.; Yan, D.D.; Yang, D.; Li, Y.; Wang, X.; Zalewski, O.; Yan, B.; Lu, W. Combinatorial Photothermal and Immuno Cancer Therapy Using Chitosan-Coated Hollow Copper Sulfide Nanoparticles. ACS Nano 2014, 8, 5670–5681. [Google Scholar] [CrossRef]
  530. Tao, Y.; Ju, E.; Ren, J.; Qu, X. Immunostimulatory oligonucleotides-loaded cationic graphene oxide with photothermally enhanced immunogenicity for photothermal/immune cancer therapy. Biomaterials 2014, 35, 9963–9971. [Google Scholar] [CrossRef]
  531. Tao, Y.; Ju, E.; Liu, Z.; Dong, K.; Ren, J.; Qu, X. Engineered, self-assembled near-infrared photothermal agents for combined tumor immunotherapy and chemo-photothermal therapy. Biomaterials 2014, 35, 6646–6656. [Google Scholar] [CrossRef]
  532. Speiser, D.E.; Schwarz, K.; Baumgaertner, P.; Manolova, V.; Devevre, E.; Sterry, W.; Walden, P.; Zippelius, A.; Conzett, K.B.; Senti, G.; et al. Memory and effector CD8 T-cell responses after nanoparticle vaccination of melanoma patients. J. Immunother. 2010, 33, 848–858. [Google Scholar] [CrossRef] [PubMed]
  533. Cho, H.J.; Takabayashi, K.; Cheng, P.M.; Nguyen, M.D.; Corr, M.; Tuck, S.; Raz, E. Immunostimulatory DNA-based vaccines induce cytotoxic lymphocyte activity by a T-helper cell-independent mechanism. Nat. Biotechnol. 2000, 18, 509–514. [Google Scholar] [CrossRef] [PubMed]
  534. Gungor, B.; Yagci, F.C.; Tincer, G.; Bayyurt, B.; Alpdundar, E.; Yildiz, S.; Ozcan, M.; Gursel, I.; Gursel, M. CpG ODN nanorings induce IFNα from plasmacytoid dendritic cells and demonstrate potent vaccine adjuvant activity. Sci Transl. Med. 2014, 6, 235ra261. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  535. Schmoll, H.J.; Wittig, B.; Arnold, D.; Riera-Knorrenschild, J.; Nitsche, D.; Kroening, H.; Mayer, F.; Andel, J.; Ziebermayr, R.; Scheithauer, W. Maintenance treatment with the immunomodulator MGN1703, a Toll-like receptor 9 (TLR9) agonist, in patients with metastatic colorectal carcinoma and disease control after chemotherapy: A randomised, double-blind, placebo-controlled trial. J. Cancer Res. Clin. Oncol. 2014, 140, 1615–1624. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  536. Weihrauch, M.R.; Richly, H.; von Bergwelt-Baildon, M.S.; Becker, H.J.; Schmidt, M.; Hacker, U.T.; Shimabukuro-Vornhagen, A.; Holtick, U.; Nokay, B.; Schroff, M.; et al. Phase I clinical study of the toll-like receptor 9 agonist MGN1703 in patients with metastatic solid tumours. Eur. J. Cancer 2015, 51, 146–156. [Google Scholar] [CrossRef] [PubMed]
  537. Wittig, B.; Schmidt, M.; Scheithauer, W.; Schmoll, H.J. MGN1703, an immunomodulator and toll-like receptor 9 (TLR-9) agonist: From bench to bedside. Crit. Rev. Oncol. Hematol. 2015, 94, 31–44. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  538. Fire, A.; Xu, S.; Montgomery, M.K.; Kostas, S.A.; Driver, S.E.; Mello, C.C. Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 1998, 391, 806–811. [Google Scholar] [CrossRef]
  539. Müller, K.; Wagner, E. RNAi-Based Nano-Oncologicals: Delivery and Clinical Applications. In Nano-Oncologicals: New Targeting and Delivery Approaches; Alonso, M.J., Garcia-Fuentes, M., Eds.; Springer International Publishing: Cham, Switzerland, 2014; pp. 245–268. [Google Scholar]
  540. Allen, K.E.; Weiss, G.J. Resistance may not be futile: microRNA biomarkers for chemoresistance and potential therapeutics. Mol. Cancer Ther. 2010, 9, 3126–3136. [Google Scholar] [CrossRef] [Green Version]
  541. Kong, Y.W.; Ferland-McCollough, D.; Jackson, T.J.; Bushell, M. microRNAs in cancer management. Lancet Oncol. 2012, 13, e249–e258. [Google Scholar] [CrossRef]
  542. Kobayashi, E.; Hornicek, F.J.; Duan, Z. MicroRNA Involvement in Osteosarcoma. Sarcoma 2012, 2012, 359739. [Google Scholar] [CrossRef]
  543. Iyer, A.K.; Duan, Z.; Amiji, M.M. Nanodelivery Systems for Nucleic Acid Therapeutics in Drug Resistant Tumors. Mol. Pharm. 2014, 11, 2511–2526. [Google Scholar] [CrossRef] [PubMed]
  544. Croce, C.M. Causes and consequences of microRNA dysregulation in cancer. Nat. Rev. Genet. 2009, 10, 704–714. [Google Scholar] [CrossRef] [PubMed]
  545. Calin, G.A.; Dumitru, C.D.; Shimizu, M.; Bichi, R.; Zupo, S.; Noch, E.; Aldler, H.; Rattan, S.; Keating, M.; Rai, K.; et al. Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc. Natl. Acad. Sci. USA 2002, 99, 15524. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  546. Awasthi, R.; Rathbone, M.J.; Hansbro, P.M.; Bebawy, M.; Dua, K. Therapeutic prospects of microRNAs in cancer treatment through nanotechnology. Drug Deliv. Transl. Res. 2018, 8, 97–110. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  547. Bader, A.G.; Brown, D.; Winkler, M. The promise of microRNA replacement therapy. Cancer Res. 2010, 70, 7027–7030. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  548. Garzon, R.; Marcucci, G.; Croce, C.M. Targeting microRNAs in cancer: Rationale, strategies and challenges. Nat. Rev. Drug Discov. 2010, 9, 775–789. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  549. Wagner, E. Biomaterials in RNAi therapeutics: Quo vadis? Biomater. Sci. 2013, 1, 804–809. [Google Scholar] [CrossRef] [Green Version]
  550. Krützfeldt, J.; Rajewsky, N.; Braich, R.; Rajeev, K.G.; Tuschl, T.; Manoharan, M.; Stoffel, M. Silencing of microRNAs in vivo with ‘antagomirs’. Nature 2005, 438, 685–689. [Google Scholar] [CrossRef] [PubMed]
  551. Li, Z.; Rana, T.M. Therapeutic targeting of microRNAs: Current status and future challenges. Nat. Rev. Drug Discov. 2014, 13, 622–638. [Google Scholar] [CrossRef]
  552. Cheng, C.J.; Bahal, R.; Babar, I.A.; Pincus, Z.; Barrera, F.; Liu, C.; Svoronos, A.; Braddock, D.T.; Glazer, P.M.; Engelman, D.M.; et al. MicroRNA silencing for cancer therapy targeted to the tumour microenvironment. Nature 2015, 518, 107–110. [Google Scholar] [CrossRef] [Green Version]
  553. Guilford, P.; Hopkins, J.; Harraway, J.; McLeod, M.; McLeod, N.; Harawira, P.; Taite, H.; Scoular, R.; Miller, A.; Reeve, A.E. E-cadherin germline mutations in familial gastric cancer. Nature 1998, 392, 402–405. [Google Scholar] [CrossRef] [PubMed]
  554. Gregory, P.A.; Bert, A.G.; Paterson, E.L.; Barry, S.C.; Tsykin, A.; Farshid, G.; Vadas, M.A.; Khew-Goodall, Y.; Goodall, G.J. The miR-200 family and miR-205 regulate epithelial to mesenchymal transition by targeting ZEB1 and SIP1. Nat. Cell Bio. 2008, 10, 593–601. [Google Scholar] [CrossRef] [PubMed]
  555. Howe, E.N.; Cochrane, D.R.; Richer, J.K. Targets of miR-200c mediate suppression of cell motility and anoikis resistance. Breast Cancer Res. 2011, 13, R45. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  556. Kopp, F.; Oak, P.S.; Wagner, E.; Roidl, A. miR-200c sensitizes breast cancer cells to doxorubicin treatment by decreasing TrkB and Bmi1 expression. PLoS ONE 2012, 7, e50469. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  557. Kopp, F.; Wagner, E.; Roidl, A. The proto-oncogene KRAS is targeted by miR-200c. Oncotarget 2014, 5, 185–195. [Google Scholar] [CrossRef] [PubMed]
  558. Mutlu, M.; Raza, U.; Saatci, Ö.; Eyüpoğlu, E.; Yurdusev, E.; Şahin, Ö. miR-200c: A versatile watchdog in cancer progression, EMT, and drug resistance. J. Mol. Med. 2016, 94, 629–644. [Google Scholar] [CrossRef] [PubMed]
  559. Müller, K.; Klein, P.M.; Heissig, P.; Roidl, A.; Wagner, E. EGF receptor targeted lipo-oligocation polyplexes for antitumoral siRNA and miRNA delivery. Nanotechnology 2016, 27, 464001. [Google Scholar] [CrossRef]
  560. Beg, M.S.; Brenner, A.J.; Sachdev, J.; Borad, M.; Kang, Y.K.; Stoudemire, J.; Smith, S.; Bader, A.G.; Kim, S.; Hong, D.S. Phase I study of MRX34, a liposomal miR-34a mimic, administered twice weekly in patients with advanced solid tumors. Invest. New Drugs 2017, 35, 180–188. [Google Scholar] [CrossRef]
  561. Hong, D.S.; Kang, Y.K.; Borad, M.; Sachdev, J.; Ejadi, S.; Lim, H.Y.; Brenner, A.J.; Park, K.; Lee, J.L.; Kim, T.Y.; et al. Phase 1 study of MRX34, a liposomal miR-34a mimic, in patients with advanced solid tumours. Br. J. Cancer 2020, 122, 1630–1637. [Google Scholar] [CrossRef]
  562. June, C.H.; O’Connor, R.S.; Kawalekar, O.U.; Ghassemi, S.; Milone, M.C. CAR T cell immunotherapy for human cancer. Science 2018, 359, 1361. [Google Scholar] [CrossRef] [Green Version]
  563. Ali, S.; Kjeken, R.; Niederlaender, C.; Markey, G.; Saunders, T.S.; Opsata, M.; Moltu, K.; Bremnes, B.; Grønevik, E.; Muusse, M.; et al. The European Medicines Agency Review of Kymriah (Tisagenlecleucel) for the Treatment of Acute Lymphoblastic Leukemia and Diffuse Large B-Cell Lymphoma. Oncologist 2020, 25, e321–e327. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  564. Papadouli, I.; Mueller-Berghaus, J.; Beuneu, C.; Ali, S.; Hofner, B.; Petavy, F.; Tzogani, K.; Miermont, A.; Norga, K.; Kholmanskikh, O.; et al. EMA Review of Axicabtagene Ciloleucel (Yescarta) for the Treatment of Diffuse Large B-Cell Lymphoma. Oncologist 2020. [Google Scholar] [CrossRef] [PubMed]
  565. Tejeda-Mansir, A.; García-Rendón, A.; Guerrero-Germán, P. Plasmid-DNA lipid and polymeric nanovaccines: A new strategic in vaccines development. Biotechnol. Genet. Eng. Rev. 2019, 35, 46–68. [Google Scholar] [CrossRef] [PubMed]
  566. Caruso, H.G.; Tanaka, R.; Liang, J.; Ling, X.; Sabbagh, A.; Henry, V.K.; Collier, T.L.; Heimberger, A.B. Shortened ex vivo manufacturing time of EGFRvIII-specific chimeric antigen receptor (CAR) T cells reduces immune exhaustion and enhances antiglioma therapeutic function. J. Neurooncol. 2019, 145, 429–439. [Google Scholar] [CrossRef] [PubMed]
  567. Iurescia, S.; Fioretti, D.; Rinaldi, M. A blueprint for DNA vaccine design. Methods Mol. Biol. (Clifton, N.J.) 2014, 1143, 3–10. [Google Scholar] [CrossRef]
  568. Weiss, T.; Weller, M.; Guckenberger, M.; Sentman, C.L.; Roth, P. NKG2D-Based CAR T Cells and Radiotherapy Exert Synergistic Efficacy in Glioblastoma. Cancer Res. 2018, 78, 1031–1043. [Google Scholar] [CrossRef] [Green Version]
  569. Di, S.; Zhou, M.; Pan, Z.; Sun, R.; Chen, M.; Jiang, H.; Shi, B.; Luo, H.; Li, Z. Combined Adjuvant of Poly I:C Improves Antitumor Effects of CAR-T Cells. Front. Oncol. 2019, 9, 241. [Google Scholar] [CrossRef]
  570. Li, Y.; Xiao, F.; Zhang, A.; Zhang, D.; Nie, W.; Xu, T.; Han, B.; Seth, P.; Wang, H.; Yang, Y.; et al. Oncolytic adenovirus targeting TGF-β enhances anti-tumor responses of mesothelin-targeted chimeric antigen receptor T cell therapy against breast cancer. Cell Immunol. 2020, 348, 104041. [Google Scholar] [CrossRef]
  571. Grunwitz, C.; Kranz, L.M. mRNA Cancer Vaccines-Messages that Prevail. Curr. Top. Microbiol. Immunol. 2017, 405, 145–164. [Google Scholar] [CrossRef]
Figure 1. Nucleic acid-based strategies for tumor therapy. Vaccination of dendritic cells (DC) aims to induce tumor-specific effector T cells (Teff), which in turn kill tumor cells. Regulatory immune cells, regulatory T cells (Treg) and myeloid-derived suppressor cells (MDSC), are induced by the tumor and other cells of the tumor microenvironment (TEM) and inhibit both DC and Teff. The expansion and suppressive activity of Treg/MDSC can be inhibited by RNA interference (RNAi) and MDSC may be reprogramed to yield antigen presenting cells by applying nucleic acid-based stimuli. Further, T cells can be transfected/transduced with chimeric antigen receptors (CAR) to gain tumor specificity. Teff are inhibited by factors within the TME. Tumor-specific delivery of nucleic acids (gene-coding or conferring RNAi) is aimed to induce apoptosis in tumor cells, and to inhibit or reprogram accessory cells within the TME, tumor-associated macrophages (TAM), and cancer-associated fibroblasts (CAF).
Figure 1. Nucleic acid-based strategies for tumor therapy. Vaccination of dendritic cells (DC) aims to induce tumor-specific effector T cells (Teff), which in turn kill tumor cells. Regulatory immune cells, regulatory T cells (Treg) and myeloid-derived suppressor cells (MDSC), are induced by the tumor and other cells of the tumor microenvironment (TEM) and inhibit both DC and Teff. The expansion and suppressive activity of Treg/MDSC can be inhibited by RNA interference (RNAi) and MDSC may be reprogramed to yield antigen presenting cells by applying nucleic acid-based stimuli. Further, T cells can be transfected/transduced with chimeric antigen receptors (CAR) to gain tumor specificity. Teff are inhibited by factors within the TME. Tumor-specific delivery of nucleic acids (gene-coding or conferring RNAi) is aimed to induce apoptosis in tumor cells, and to inhibit or reprogram accessory cells within the TME, tumor-associated macrophages (TAM), and cancer-associated fibroblasts (CAF).
Cells 09 02061 g001
Figure 2. Mechanism of RNA interference (RNAi) and options for therapeutic intervention. (1) Substitution of tumor suppressor micro-RNA (miRNA, miR) in form of pre-miRNA or miRNA mimics, thereby inducing RNAi. (2) Blocking of oncogenic miRNA by miRNA-specific antagomirs (anti-miR). This figure is reprinted with permission from [103]. Copyright © 2020; John Wiley and Sons.
Figure 2. Mechanism of RNA interference (RNAi) and options for therapeutic intervention. (1) Substitution of tumor suppressor micro-RNA (miRNA, miR) in form of pre-miRNA or miRNA mimics, thereby inducing RNAi. (2) Blocking of oncogenic miRNA by miRNA-specific antagomirs (anti-miR). This figure is reprinted with permission from [103]. Copyright © 2020; John Wiley and Sons.
Cells 09 02061 g002
Figure 3. Immune checkpoint inhibition mediated by nucleic acid-based strategies. (a) Besides recognition of major histocompatibility complex (MHC)-bound antigen on the surface of APC via TCR, co-stimulatory signals—inter alia interaction of CD80 (B7-1) and CD28—are required for full T cell activation. The duration and intensity of activation is regulated among other things by immune checkpoint CTLA-4 that binds with high affinity to CD80. Blocking of this interaction results in enhanced T cell activity. One therapeutic option is delivery of mRNA encoding for anti-CTLA-4 antibodies. (b) Tumor cells often upregulate PD-L1 that binds to PD-1 on effector T cells, thereby inhibiting the activity of effector T cells. Nucleic acid-based approaches for blocking this immune checkpoint comprise siRNA against PD-L1, pDNA encoding for PD-L1 trap proteins (pPD-L1-trap), and CRISPR/Cas9-mediated knock-down of PD-1 gene.
Figure 3. Immune checkpoint inhibition mediated by nucleic acid-based strategies. (a) Besides recognition of major histocompatibility complex (MHC)-bound antigen on the surface of APC via TCR, co-stimulatory signals—inter alia interaction of CD80 (B7-1) and CD28—are required for full T cell activation. The duration and intensity of activation is regulated among other things by immune checkpoint CTLA-4 that binds with high affinity to CD80. Blocking of this interaction results in enhanced T cell activity. One therapeutic option is delivery of mRNA encoding for anti-CTLA-4 antibodies. (b) Tumor cells often upregulate PD-L1 that binds to PD-1 on effector T cells, thereby inhibiting the activity of effector T cells. Nucleic acid-based approaches for blocking this immune checkpoint comprise siRNA against PD-L1, pDNA encoding for PD-L1 trap proteins (pPD-L1-trap), and CRISPR/Cas9-mediated knock-down of PD-1 gene.
Cells 09 02061 g003
Figure 4. Genetic modifications to enhance selectivity, safety, and efficacy of oncolytic virotherapies.
Figure 4. Genetic modifications to enhance selectivity, safety, and efficacy of oncolytic virotherapies.
Cells 09 02061 g004
Table 1. Examples of clinical trials investigating nucleic acid-based approaches for adjusting intratumoral cytokine levels.
Table 1. Examples of clinical trials investigating nucleic acid-based approaches for adjusting intratumoral cytokine levels.
Signaling MoleculeTherapy StrategyApplication RouteTreated CancerClinical StateReferences
IL-2Syngeneic tumor cell vaccine modified with IL-2 gene ex vivoIntradermal or subcutaneous injectionMetastatic melanomaPhase I[319]
Allogeneic tumor cell vaccine modified with IL-2 gene ex vivoSubcutaneous injectionMetastatic melanomaPilot study[320]
Phase I–II[321]
Allogeneic tumor cell vaccine modified with IL-2 gene ex vivoSubcutaneous injectionRelapsed neuroblastomaPhase I[322]
TNF-αTNFerade, a replication-deficient adenoviral vector encoding for TNF-α under the control of a radiation inducible promotor (erg-1 gene promotor)Intratumoral injectionVarious cancer types, e.g., advanced pancreatic cancerPhase III[323,324]
IL-12Ad–RTS–hIL-12, an adenoviral vector encoding for IL-12 transgene designed with a ligand-inducible expression switchInjection in the resection cavityRecurrent high-grade gliomaPhase I[325]
GM-CSFGVAX, an allogeneic tumor cell vaccine modified with GM-CSF gene ex vivo,(in combination with immune checkpoint inhibitors and/or cyclophosphamide and Listeria monocytogenes-expressing mesothelin (CRS-207))Intradermal injectionAdvanced pancreatic cancerPhase Ib[326]
Phase II[327]
Phase IIb[328]
Phase II[329]
IFN-αInstiladrin® (rAdIFNα2b/Syn3), an IFN-α encoding adenoviral vectorIntravesical injectionBCG unresponsive bladder cancerPhase IIIresults pending (NCT02773849)[330]
TGF-β (inhibition)Belagenpneumatucel-L, an allogeneic tumor cell vaccine altered to express ASO directed against TGF-βIntradermal injectionAdvanced non-small cell lung cancerPhase II[331,332]
Phase III[333]
Table 2. Examples of oncolytic virotherapies approved or in clinical trials.
Table 2. Examples of oncolytic virotherapies approved or in clinical trials.
Oncolytic VirusGenetic ModificationTreated CancerClinical StateReference
Wild-Type Virus
RIGVIR® (wild-type ECHO-7; (+)ssRNA virus)MelanomaApproved in Lativa in 2004[471]
Reolysin® (pelareorep, type 3 Dearing (T3D) strain reovirus; dsRNA virus)Many advanced malignancies (e.g., melanoma, sarcomas, non-small cell lung cancer, pancreatic adenocarcinoma)Phase I and II[457,472,473]
Advanced, metastatic head and neck cancerPhase III[472]
Oncolytic Adenovirus (dsDNA virus)
Oncorine® (rAdV H101)Deletion in E1B-55K and E3 genesNasopharyngeal carcinomaApproved in China in 2005[474,475]
CG0070 (AdV-5)Deletion in E3 gene; insertion of GM-CSF geneNon-muscle-invasive bladder cancerPhase II/III (BOND, NCT01438112); phase II (BOND2, NCT02365818)[456,476]
Oncolytic Herpes Simplex Virus, HSV-1 (dsDNA virus)
T-Vec (talminogene laherparepvec)Deletion in ICP34.5 and ICP47 genes; insertion of GM-CSF geneAdvanced melanomaApproved by FDA and EMA in 2015[477,478]
M032Deletion in ICP34.5 gene; insertion of IL-12 geneGlioblastoma multiformePhase I[479]
G47ΔDeletion in ICP34.5, ICP47 and ICP6 genes; insertion of GM-CSF geneRecurrent glioblastoma, castration resistant prostate cancer, recurrent olfactory neuroblastomaClinical trials in Japan[456,480,481]
Oncolytic Vaccinia Virus (dsDNA virus)
Pexa-Vec (JX-594, pexastimogene devacirepvec)Mutation in TK gene; insertion of GM-CSF geneAdvanced hepatocellular carcinomaPhase III (in combination with sorafenib)[482]

Share and Cite

MDPI and ACS Style

Hager, S.; Fittler, F.J.; Wagner, E.; Bros, M. Nucleic Acid-Based Approaches for Tumor Therapy. Cells 2020, 9, 2061. https://doi.org/10.3390/cells9092061

AMA Style

Hager S, Fittler FJ, Wagner E, Bros M. Nucleic Acid-Based Approaches for Tumor Therapy. Cells. 2020; 9(9):2061. https://doi.org/10.3390/cells9092061

Chicago/Turabian Style

Hager, Simone, Frederic Julien Fittler, Ernst Wagner, and Matthias Bros. 2020. "Nucleic Acid-Based Approaches for Tumor Therapy" Cells 9, no. 9: 2061. https://doi.org/10.3390/cells9092061

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop