Login / Signup

Systematic evaluation of antibody-mediated siRNA delivery using an industrial platform of THIOMAB-siRNA conjugates.

Trinna L CuellarDwight BarnesChristopher NelsonJoshua TanguayShang-Fan YuXiaohui WenSuzie J ScalesJulie GeschDavid DavisAnja van Brabant SmithDevin LeakeRichard VandlenChristian W Siebel
Published in: Nucleic acids research (2014)
Delivery of siRNA is a key hurdle to realizing the therapeutic promise of RNAi. By targeting internalizing cell surface antigens, antibody-siRNA complexes provide a possible solution. However, initial reports of antibody-siRNA complexes relied on non-specific charged interactions and have not been broadly applicable. To assess and improve this delivery method, we built on an industrial platform of therapeutic antibodies called THIOMABs, engineered to enable precise covalent coupling of siRNAs. We report that such coupling generates monomeric antibody-siRNA conjugates (ARCs) that retain antibody and siRNA activities. To broadly assess this technology, we generated a battery of THIOMABs against seven targets that use multiple internalization routes, enabling systematic manipulation of multiple parameters that impact delivery. We identify ARCs that induce targeted silencing in vitro and extend tests to target prostate carcinoma cells following systemic administration in mouse models. However, optimal silencing was restricted to specific conditions and only observed using a subset of ARCs. Trafficking studies point to ARC entrapment in endocytic compartments as a limiting factor, independent of the route of antigen internalization. Our broad characterization of multiple parameters using therapeutic-grade conjugate technology provides a thorough assessment of this delivery technology, highlighting both examples of success as well as remaining challenges.
Keyphrases
  • cancer therapy
  • drug delivery
  • hyaluronic acid
  • prostate cancer
  • cell surface
  • wastewater treatment
  • heavy metals
  • high throughput
  • immune response
  • emergency department
  • risk assessment
  • machine learning
  • case control