bims-novged Biomed News
on Non-viral vectors for gene delivery
Issue of 2023‒03‒26
ten papers selected by
the Merkel lab
Ludwig-Maximilians University

  1. Expert Opin Ther Pat. 2023 Mar 23.
      INTRODUCTION: mRNA-LNP delivery is currently a research hotspot in pharmaceutics. Lipid nanoparticle has emerged in pharmaceutical industry as popular and effective vehicles for mRNA delivery. It is therefore significant to understand current landscape and recent development of lipid nanoparticle for mRNA delivery.AREAS COVERED: This article provides patent landscape and recent development for mRNA-LNP delivery by US-granted patent analysis. The US-granted patents from January 2003 to December 2022 were retrieved and analyzed by using patsnap.
    EXPERT OPINION: Globally, the present article was the first one which showed that mRNA-LNP delivery system demonstrated three therapeutic applications including vaccines, anticancer, and diseases associated with protein or enzyme deficiencies. Modernatx is most powerful company, and leads almost all technologies in mRNA-LNP field. In addition, the technologies related to lipid nanoparticle for mRNA delivery are virtually controlled by top three assignees. mRNA-LNP delivery in therapy of diseases associated with enzyme deficiencies may be a future trend. The article provides recent advances in lipid nanoparticle for mRNA delivery.
    Keywords:  LNP; lipid nanoparticle; mRNA; mRNA delivery; mRNA-LNP; patent
  2. Biomater Sci. 2023 Mar 20.
      Lipid nanoparticles (LNPs), comprising ionizable lipids, helper lipids, cholesterol, and PEG lipids, can act as delivery carriers for nucleic acids and have achieved clinical success in the delivery of siRNA and mRNA. It has been shown that the morphology of LNPs varies depending on their lipid composition, but the influence of their morphology on nucleic acid efficacy has not been fully elucidated. In this study, we used our previously developed novel lipid, dioleoylglycerophosphate-diethylenediamine conjugate (DOP-DEDA), to create pH-responsive LNPs (DOP-DEDA LNPs). We evaluated the morphology of DOP-DEDA LNPs composed of different helper lipids and the knockdown efficiency of small interfering RNA (siRNA). A distinctive difference in morphology was observed between DOP-DEDA LNPs of different helper lipids. Significant differences were also observed in the apparent pKa of DOP-DEDA LNPs and the knockdown efficiency of siRNA, which may be due to the difference in the localization of DOP-DEDA molecules in DOP-DEDA LNPs. These findings suggest that changing helper lipids alters the morphology of the DOP-DEDA LNP system, which affects the apparent pKa and knockdown efficiency of siRNA.
  3. Biotechnol Adv. 2023 Mar 16. pii: S0734-9750(23)00037-X. [Epub ahead of print] 108130
      Nucleic acid-based therapies such as messenger RNA have the potential to revolutionize modern medicine and enhance the performance of existing pharmaceuticals. The key challenges of mRNA-based therapies are delivering the mRNA safely and effectively to the target tissues and cells and controlling its release from the delivery vehicle. Lipid nanoparticles (LNPs) have been widely studied as drug carriers and are considered to be state-of-the-art technology for nucleic acid delivery. In this review, we begin by presenting the advantages and mechanisms of action of mRNA therapeutics. Then we discuss the design of LNP platforms based on ionizable lipids and the applications of mRNA-LNP vaccines for prevention of infectious diseases and for treatment of cancer and various genetic diseases. Finally, we describe the challenges and future prospects of mRNA-LNP therapeutics.
    Keywords:  Antitumor; Genetic diseases; Infectious disease; Lipid nanoparticles; mRNA vaccine
  4. J Control Release. 2023 Mar 21. pii: S0168-3659(23)00206-7. [Epub ahead of print]
      Messenger RNA (mRNA) lipid nanoparticles (LNPs) have emerged at the forefront during the COVID-19 vaccination campaign. Despite their tremendous success, mRNA vaccines currently require storage at deep freeze temperatures which complicates their storage and distribution, and ultimately leads to lower accessibility to low- and middle-income countries. To elaborate on this challenge, we investigated freeze-drying as a method to enable storage of mRNA LNPs at room- and even higher temperatures. More specifically, we explored a novel continuous freeze-drying technique based on spin-freezing, which has several advantages compared to classical batch freeze-drying including a much shorter drying time and improved process and product quality controlling. Here, we give insight into the variables that play a role during freeze-drying by evaluating the impact of the buffer and mRNA LNP formulation (ionizable lipid to mRNA weight ratio) on properties such as size, morphology and mRNA encapsulation. We found that a sufficiently high ionizable lipid to mRNA weight ratio was necessary to prevent leakage of mRNA during freeze-drying and that phosphate and Tris, but not PBS, were appropriate buffers for lyophilization of mRNA LNPs. We also studied the stability of optimally lyophilized mRNA LNPs at 4 °C, 22 °C, and 37 °C and found that transfection properties of lyophilized mRNA LNPs were maintained during at least 12 weeks. To our knowledge, this is the first study that demonstrates that optimally lyophilized mRNA LNPs can be safely stored at higher temperatures for months without losing their transfection properties.
    Keywords:  Continuous freeze-drying; Cryo-EM; Lyophilization; Stability; Vaccine; mRNA lipid nanoparticle
  5. Sci Technol Adv Mater. 2023 ;24(1): 2170164
      Messenger RNA (mRNA) therapeutics have recently demonstrated high clinical potential with the accelerated approval of SARS-CoV-2 vaccines. To fulfill the promise of unprecedented mRNA-based treatments, the development of safe and efficient carriers is still necessary to achieve effective delivery of mRNA. Herein, we prepared mRNA-loaded nanocarriers for enhanced in vivo delivery using biocompatible block copolymers having functional amino acid moieties for tunable interaction with mRNA. The block copolymers were based on flexible poly(ethylene glycol)-poly(glycerol) (PEG-PG) modified with glycine (Gly), leucine (Leu) or tyrosine (Tyr) via ester bonds to generate block catiomers. Moreover, the amino acids can be gradually detached from the block copolymers after ester bond hydrolyzation, avoiding cytotoxic effects. When mixed with mRNA, the block catiomers formed narrowly distributed polymeric micelles with high stability and enhanced delivery efficiency. Particularly, the micelles based on tyrosine-modified PEG-PG (PEG-PGTyr), which formed a polyion complex (PIC) and π-π stacking with mRNA, displayed excellent stability against polyanions and promoted mRNA integrity in serum. PEG-PGTyr-based micelles also increased the cellular uptake and the endosomal escape, promoting high protein expression both in vitro and in vivo. Furthermore, the PEG-PGTyr-based micelles significantly extended the half-life of the loaded mRNA after intravenous injection. Our results highlight the potential of PEG-PGTyr-based micelles as safe and effective carriers for mRNA, expediting the rational design of polymeric materials for enhanced mRNA delivery.
    Keywords:  Messenger RNA; biocompatible; nanomedicine; poly(ethylene glycol)-poly(glycerol); polymeric micelles; π–π interaction
  6. Front Bioeng Biotechnol. 2023 ;11 1160509
      The intracellular delivery of messenger (m)RNA holds great potential for the discovery and development of vaccines and therapeutics. Yet, in many applications, a major obstacle to clinical translation of mRNA therapy is the lack of efficient strategy to precisely deliver RNA sequence to liver tissues and cells. In this study, we synthesized virus-like mesoporous silica (V-SiO2) nanoparticles for effectively deliver the therapeutic RNA. Then, the cationic polymer polyethylenimine (PEI) was included for the further silica surface modification (V-SiO2-P). Negatively charged mRNA motifs were successfully linked on the surface of V-SiO2 through electrostatic interactions with PEI (m@V-SiO2-P). Finally, the supported lipid bilayer (LB) was completely wrapped on the bionic inspired surface of the nanoparticles (m@V-SiO2-P/LB). Importantly, we found that, compared with traditional liposomes with mRNA loading (m@LNPs), the V-SiO2-P/LB bionic-like morphology effectively enhanced mRNA delivery effect to hepatocytes both in vitro and in vivo, and PEI modification concurrently promoted mRNA binding and intracellular lysosomal escape. Furthermore, m@V-SiO2-P increased the blood circulation time (t1/2 = 7 h) to be much longer than that of the m@LNPs (4.2 h). Understanding intracellular delivery mediated by the V-SiO2-P/LB nanosystem will inspire the next-generation of highly efficient and effective mRNA therapies. In addition, the nanosystem can also be applied to the oral cavity, forehead, face and other orthotopic injections.
    Keywords:  bionic inspired nanosystem; liver target; oral in Situ injection; precise delivery of mRNA; virus-like mesoporous silica
  7. Mol Pharm. 2023 Mar 23.
      Despite the success of mRNA-based vaccines against infectious diseases (including COVID-19), safety concerns have been raised relating to the lipid nanoparticles (LNPs) used to deliver the mRNA cargo. Antibodies against the polyethylene glycol (PEG) coating on these non-viral vectors are present in the general population and can in some instances induce allergic reactions. Furthermore, treatment with PEGylated therapeutics may increase the plasma concentration of such anti-PEG antibodies. The widespread use of PEGylated nanoparticles for mRNA vaccines concerns researchers and clinicians about a potential rise in future cases of allergic reactions against mRNA vaccines and cross-reactions with other PEGylated therapeutics. To determine if vaccination with Comirnaty increased the plasma concentration of antibodies against LNPs, we investigated the blood plasma concentration of anti-LNP antibodies in healthy individuals before and after vaccination with the mRNA-based COVID-19 vaccine Comirnaty (BNT162b2). Blood samples were acquired from 21 healthy adults before vaccination, 3-4 weeks after the first vaccination dose but before the second dose, and 2-6 months after the second (booster) dose. The blood plasma concentration of antibodies recognizing the LNPs was analyzed using a microscopy-based assay capable of measuring antibody-binding to individual authentic LNPs. No significant increase in anti-LNP antibodies was observed after two doses of Comirnaty. The LNPs used for intramuscular delivery of mRNA in the vaccine against COVID-19, Comirnaty, do, therefore, not seem to induce the generation of anti-vector antibodies.
    Keywords:  COVID-19; anti-drug antibody; lipid nanoparticle; mRNA vaccine; poly(ethylene glycol); side effects
  8. Eur J Pharm Sci. 2023 Mar 20. pii: S0928-0987(23)00058-1. [Epub ahead of print] 106427
      Prostate cancer remains a serious condition threatening the health of men. Due to the complicated nature of the tumour microenvironment (TME), conventional treatments face challenges including poor prognosis and tumour resistance, therefore new therapeutic strategies are urgently needed. Small interfering RNA (siRNA), a double-stranded non-coding RNA, regulates specific gene expression through RNA interference. Tumour-associated macrophages (TAMs) are a potential therapeutic target in cancer immunotherapy. Colony stimulating factor-1/colony stimulating factor-1 receptor (CSF-1/CSF-1R) signaling pathway plays a crucial role in the polarization of the immunosuppressive TAMs, M2 macrophages. Downregulation of CSF-1R is known to reprogram the immunosuppressive TAMs, M2 macrophages, to the immunostimulatory phenotype, M1 macrophages. Sialic acid is a ligand for Siglec-1 (CD169) which is overexpressed on M2 macrophages with little expression in other phenotypes. Therefore, a sialic acid-targeted cyclodextrin-based nanoparticle was developed to specifically deliver CSF-1R siRNA to M2 macrophages. The nanoparticles were studied in vitro using both human and mouse prostate cancer cell lines. Results show that the targeted nanoparticles achieved cell specific delivery to M2 macrophages via the sialic acid-CD169 axis. The expression of CSF-1R was significantly downregulated in M2 macrophages (29.64% for targeted vs 19.31% for non-targeted nanoparticles in THP-1-derived M2 macrophages and 38.94% for targeted vs 18.51% for non-targeted nanoparticles in RAW 264.7-derived M2 macrophages, n = 4, p < 0.01). The resulting reprograming of M2 macrophages to M1 enhanced the level of apoptosis in the prostate cancer cells in a Transwell model (49.17% for targeted vs 37.68% for non-targeted nanoparticles in PC-3 cells and 69.15% for targeted vs 44.73% for non-targeted nanoparticles in TRAMP C1 cells, n = 3, p < 0.01). Thus, this targeted cyclodextrin-based siRNA drug delivery system provides a potential strategy for prostate cancer immunotherapy.
    Keywords:  Modified cyclodextrins; RNA interference; immunotherapy; prostate cancer; sialic acid; tumor-associated macrophages
  9. Nat Mater. 2023 Mar 20.
      RNA-based therapeutics have shown tremendous promise in disease intervention at the genetic level, and some have been approved for clinical use, including the recent COVID-19 messenger RNA vaccines. The clinical success of RNA therapy is largely dependent on the use of chemical modification, ligand conjugation or non-viral nanoparticles to improve RNA stability and facilitate intracellular delivery. Unlike molecular-level or nanoscale approaches, macroscopic hydrogels are soft, water-swollen three-dimensional structures that possess remarkable features such as biodegradability, tunable physiochemical properties and injectability, and recently they have attracted enormous attention for use in RNA therapy. Specifically, hydrogels can be engineered to exert precise spatiotemporal control over the release of RNA therapeutics, potentially minimizing systemic toxicity and enhancing in vivo efficacy. This Review provides a comprehensive overview of hydrogel loading of RNAs and hydrogel design for controlled release, highlights their biomedical applications and offers our perspectives on the opportunities and challenges in this exciting field of RNA delivery.
  10. BMC Bioinformatics. 2023 Mar 22. 24(1): 109
      BACKGROUND: Subcellular localization of messenger RNA (mRNAs) plays a pivotal role in the regulation of gene expression, cell migration as well as in cellular adaptation. Experiment techniques for pinpointing the subcellular localization of mRNAs are laborious, time-consuming and expensive. Therefore, in silico approaches for this purpose are attaining great attention in the RNA community.METHODS: In this article, we propose MSLP, a machine learning-based method to predict the subcellular localization of mRNA. We propose a novel combination of four types of features representing k-mer, pseudo k-tuple nucleotide composition (PseKNC), physicochemical properties of nucleotides, and 3D representation of sequences based on Z-curve transformation to feed into machine learning algorithm to predict the subcellular localization of mRNAs.
    RESULTS: Considering the combination of the above-mentioned features, ennsemble-based models achieved state-of-the-art results in mRNA subcellular localization prediction tasks for multiple benchmark datasets. We evaluated the performance of our method  in ten subcellular locations, covering cytoplasm, nucleus, endoplasmic reticulum (ER), extracellular region (ExR), mitochondria, cytosol, pseudopodium, posterior, exosome, and the ribosome. Ablation study highlighted k-mer and PseKNC to be more dominant than other features for predicting cytoplasm, nucleus, and ER localizations. On the other hand, physicochemical properties and Z-curve based features contributed the most to ExR and mitochondria detection. SHAP-based analysis revealed the relative importance of features to provide better insights into the proposed approach.
    AVAILABILITY: We have implemented a Docker container and API for end users to run their sequences on our model. Datasets, the code of API and the Docker are shared for the community in GitHub at: .
    Keywords:  Localization prediction; Machine learning; RNA; Sequence analysis; Subcellular localization; mRNA