ArticleActa biomaterialia2017
Efficient tuning of siRNA dose response by combining mixed polymer nanocarriers with simple kinetic modeling.
Article in Acta biomaterialia, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 21 citations in OpenAlex.
- Nanomedicine targeting ECM stiffness: restoring mechanical homeostasis for cancer immunotherapy.Materials today. Bio · 2026Review
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- Quercetin Inhibits Lef1 and Resensitizes Docetaxel-Resistant Breast Cancer Cells.Molecules (Basel, Switzerland) · 2020Article
- Method and its Composition for encapsulation, stabilization, and delivery of siRNA in Anionic polymeric nanoplex: An In vitro- In vivo Assessment.Scientific reports · 2019Article
- Attenuation of Maladaptive Responses in Aortic Adventitial Fibroblasts through Stimuli-Triggered siRNA Release from Lipid-Polymer Nanocomplexes.Advanced biosystems · 2017Article
- Predicting Gene Silencing Through the Spatiotemporal Control of siRNA Release from Photo-responsive Polymeric Nanocarriers.Journal of visualized experiments : JoVE · 2017Article
- Anionic Polymer and Quantum Dot Excipients to Facilitate siRNA Release and Self-Reporting of Disassembly in Stimuli-Responsive Nanocarrier Formulations.Biomacromolecules · 2017Article
- Nanoparticle-Mediated Gene Regulation as a Novel Strategy for Cancer Therapy.Delaware journal of public health · 2017Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Two of the most prominent challenges that limit the clinical success of siRNA therapies are a lack of control over cargo release from the delivery vehicle and an incomplete understanding of the link between gene silencing dynamics and siRNA dosing. Herein, we address these challenges through the formulation of siRNA polyplexes containing light-responsive polymer mixtures, whose varied compositions and triggered release behavior provide enhanced gene silencing and controlled dose responses that can be predicted by simple kinetic models. Through the straightforward mixing of two block copolymers, the level of gene knockdown was easily optimized to achieve the maximum level of GAPDH protein silencing in NIH/3T3 cells (~70%) using a single siRNA dose. The kinetic model was used to describe the dynamic changes in mRNA and protein concentrations in response to siRNA treatment. These predictions enabled the application of a second dose of siRNA to maximally suppress gene expression over multiple days, leading to a further 50% reduction in protein levels relative to those measured following a single dose. Furthermore, polyplexes remained dormant in cells until exposed to the photo-stimulus, demonstrating the complete control over siRNA activity as well as the stability of the nanocarriers. Thus, this work demonstrates that pairing advances in biomaterials design with simple kinetic modeling provides new insight into gene silencing dynamics and presents a powerful strategy to control gene expression through siRNA delivery. STATEMENT OF SIGNIFICANCE: Our manuscript describes two noteworthy impacts: (1) we designed mixed polymer formulations to enhance gene silencing, and (2) we simultaneously developed a simple kinetic model for determining optimal siRNA dose responses to maintain silencing over several days. These advances address critical challenges in siRNA delivery and provide new opportunities in therapeutics development. The structure-function relationships prevalent in these formulations were established to enable tuning and forecasting of nanocarrier efficiency a priori, leading to siRNA dosing regimens able to maximally suppress gene expression. Our advances are significant because the mixed polymer formulations provide a straightforward and scalable approach to tailor siRNA delivery regimens. Moreover, the implementation of accurate dosing frameworks addresses a major knowledge gap that has hindered clinical implementation of siRNA.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.