Nucleic acid nanoparticles (NANPs) represent a relatively new class of nanotechnology products that offer a versatile platform for drug delivery, biosensing, and immunotherapies. Until now, harmonized procedures for the synthesis, physicochemical and biological characterization of these materials were not available, which complicated the comparison of test results between different laboratories and impeded translation of these materials from bench to clinic. Understanding the responses of human blood cells to nanotechnology-based products such as NANPs becomes essential for several reasons: a) evaluating the safety, b) estimating efficacy, and d) identifying new application opportunities. The systemic induction of cytokines in response to a novel drug product may cause cytokine storm or cytokine release syndrome, which would halt clinical translation of such a product. Some recent examples of adverse immune-mediated toxicities that resulted in a suspension of therapeutic nucleic acids from clinical trials emphasize the importance of understanding the safety of novel drug products regardless of technologies used to produce them. In cases when novel formulations are intended to activate the immune system, measuring cytokine response to these materials would provide important information regarding their mechanism of action. Furthermore, uncovering immunological responses would help to explore some alternative indications and routes of administrations to define conditions in which local induction of cytokines would improve vaccines and immunotherapies.
Our labs collaborated to perform a systematic investigation of NANPs recognition by immune cells. Our studies[4-8] utilize primary human peripheral blood mononuclear cells (PBMCs) derived from healthy human donor volunteers. We chose this in vitro model because it has an established record of being predictive of the cytokine storm toxicity in vivo. For example, super-monoclonal antibody drug product TGN1412 resulted in severe cytokine storm syndrome in clinical trial volunteers after successfully passing preclinical in vivo safety studies in rodents and non-human primates. The toxicity of this product, however, was predicted in vitro in PBMCs derived from healthy donors. PBMCs are also widely used to estimate the quality of vaccine adjuvants[10, 11].
Over the course of almost seven years, many graduate students, postdoctoral and visiting fellows, scientists, and research associates in our labs used this protocol to verify its robustness and ruggedness. We worked closely with vendors to identify a reliable platform for cytokine detection since no harmonized procedure was available. Through the hard work and dedication of our teams and with the support of vendors, the protocol was tuned to reproducibly evaluate the induction of cytokines specific to PBMC exposure to NANPs. The biomarkers of NANPs’ pro-inflammatory response include type I and III interferons (INFα, IFNβ, IFNω, and IFNλ). The results generated using this protocol are consistent regardless of differences in individual donors donating the blood, individuals performing the assay, and lots of reagents utilized in NANPs synthesis, PBMC isolation, cell culture experiments, and cytokine analysis.
We are excited about this protocol because it is flexible and allows testing biomarkers beyond the interferon response. For example, if desired, a set of pro-inflammatory cytokines (TNFα, IL-1β, IL-6, IL-8), known as markers of pyrogenic responses, or markers of T-cell activation (IL-2, IFNγ) can also be reproducibly measured. If desired, PBMCs could be replaced with relevant cell lines or other types of primary cells. Moreover, we proposed a set of NANPs and conditions that could be used as controls specific to nucleic acid nanotechnology, as well as reagents and instructions for mechanistic studies to uncover the mechanisms of nanoparticle immune recognition. We hope that other researchers find it as helpful as our teams did.
Most importantly, we want to acknowledge all researchers who used and continue using this protocol in our laboratories as well as scientists at Quansys Biosciences who developed the multiplex chemiluminescent platform technology that enabled the development of our protocol.
- BusinessWire Mirna Therapeutics Reports Third Quarter 2016 Financial Results and MRX34 Clinical Program Updates. https://www.businesswire.com/news/home/20161110006612/en (November 22),
- Chandler, M.; Afonin, K. A., Smart-Responsive Nucleic Acid Nanoparticles (NANPs) with the Potential to Modulate Immune Behavior. Nanomaterials (Basel) 2019, 9, (4).
- Hong, E.; Halman, J. R.; Shah, A. B.; Khisamutdinov, E. F.; Dobrovolskaia, M. A.; Afonin, K. A., Structure and Composition Define Immunorecognition of Nucleic Acid Nanoparticles. Nano Lett 2018, 18, (7), 4309-4321.
- Afonin, K. A.; Viard, M.; Kagiampakis, I.; Case, C. L.; Dobrovolskaia, M. A.; Hofmann, J.; Vrzak, A.; Kireeva, M.; Kasprzak, W. K.; KewalRamani, V. N.; Shapiro, B. A., Triggering of RNA Interference with RNA-RNA, RNA-DNA, and DNA-RNA Nanoparticles. ACS Nano 2015, 9, (1), 251-9.
- Halman, J. R.; Satterwhite, E.; Roark, B.; Chandler, M.; Viard, M.; Ivanina, A.; Bindewald, E.; Kasprzak, W. K.; Panigaj, M.; Bui, M. N.; Lu, J. S.; Miller, J.; Khisamutdinov, E. F.; Shapiro, B. A.; Dobrovolskaia, M. A.; Afonin, K. A., Functionally-interdependent shape-switching nanoparticles with controllable properties. Nucleic acids research 2017, 45, (4), 2210-2220.
- Sajja, S.; Chandler, M.; Fedorov, D.; Kasprzak, W. K.; Lushnikov, A.; Viard, M.; Shah, A.; Dang, D.; Dahl, J.; Worku, B.; Dobrovolskaia, M. A.; Krasnoslobodtsev, A.; Shapiro, B. A.; Afonin, K. A., Dynamic Behavior of RNA Nanoparticles Analyzed by AFM on a Mica/Air Interface. Langmuir 2018, 34, (49), 15099-15108,
- Ke, W.; Hong, E.; Saito, R. F.; Rangel, M. C.; Wang, J.; Viard, M.; Richardson, M.; Khisamutdinov, E. F.; Panigaj, M.; Dokholyan, N. V.; Chammas, R.; Dobrovolskaia, M. A.; Afonin, K. A., RNA-DNA fibers and polygons with controlled immunorecognition activate RNAi, FRET and transcriptional regulation of NF-kappaB in human cells. Nucleic acids research 2018, 47, (3), 1350-1361
- Rackley, L.; Stewart, J. M.; Salotti, J.; Krokhotin, A.; Shah, A.; Halman, J. R.; Juneja, R.; Smollett, J.; Lee, L.; Roark, K.; Viard, M.; Tarannum, M.; Vivero-Escoto, J.; Johnson, P. F.; Dobrovolskaia, M. A.; Dokholyan, N. V.; Franco, E.; Afonin, K. A., RNA Fibers as Optimized Nanoscaffolds for siRNA Coordination and Reduced Immunological Recognition. Adv Funct Mater 2018, 28, (48), 1805959.
- Vessillier, S.; Eastwood, D.; Fox, B.; Sathish, J.; Sethu, S.; Dougall, T.; Thorpe, S. J.; Thorpe, R.; Stebbings, R., Cytokine release assays for the prediction of therapeutic mAb safety in first-in man trials--Whole blood cytokine release assays are poorly predictive for TGN1412 cytokine storm. J Immunol Methods 2015, 424, 43-52.
- Gregg, K. A.; Harberts, E.; Gardner, F. M.; Pelletier, M. R.; Cayatte, C.; Yu, L.; McCarthy, M. P.; Marshall, J. D.; Ernst, R. K., Rationally Designed TLR4 Ligands for Vaccine Adjuvant Discovery. MBio 2017, 8, (3).
- Oh, D. Y.; Dowling, D. J.; Ahmed, S.; Choi, H.; Brightman, S.; Bergelson, I.; Berger, S. T.; Sauld, J. F.; Pettengill, M.; Kho, A. T.; Pollack, H. J.; Steen, H.; Levy, O., Adjuvant-induced Human Monocyte Secretome Profiles Reveal Adjuvant- and Age-specific Protein Signatures. Mol Cell Proteomics 2016, 15, (6), 1877-94.
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