Investigating the Impact of Nanoparticle Size on Active and Passive Tumor Targeting Efficiency

TLDR

The design of nanoparticles for tumor targeting is essential for solid tumor diagnosis and treatment, yet a poor understanding exists on how to rationally engineer them. The study aims to engineer gold nanoparticles of varying sizes to compare passive and active tumor targeting and to use computational modeling to explore parameters affecting tumor accumulation. Spherical gold nanoparticles of different diameters were fabricated and computational modeling was employed to assess how particle size, coating, avidity, and clearance influence tumor accumulation. Active targeting achieved five‑fold faster and two‑fold higher tumor accumulation than passive targeting for 60 nm particles, while 15, 30, and 100 nm sizes showed no significant differences; high avidity drives accumulation with weak dependence on clearance, suggesting empirical models can screen nanomaterials without animal work.

Abstract

Understanding the principles governing the design of nanoparticles for tumor targeting is essential for the effective diagnosis and treatment of solid tumors. There is currently a poor understanding of how to rationally engineer nanoparticles for tumor targeting. Here, we engineered different-sized spherical gold nanoparticles to discern the effect of particle diameter on passive (poly(ethylene glycol)-coated) and active (transferrin-coated) targeting of MDA-MB-435 orthotopic tumor xenografts. Tumor accumulation of actively targeted nanoparticles was found to be 5 times faster and approximately 2-fold higher relative to their passive counterparts within the 60 nm diameter range. For 15, 30, and 100 nm, we observed no significant differences. We hypothesize that such enhancements are the result of an increased capacity to penetrate into tumors and preferentially associate with cancer cells. We also use computational modeling to explore the mechanistic parameters that can impact tumor accumulation efficacy. We demonstrate that tumor accumulation can be mediated by high nanoparticle avidity and are weakly dependent on their plasma clearance rate. Such findings suggest that empirical models can be used to rapidly screen novel nanomaterials for relative differences in tumor targeting without the need for animal work. Although our findings are specific to MDA-MB-435 tumor xenografts, our experimental and computational findings help to enrich knowledge of design considerations that will aid in the optimal engineering of spherical gold nanoparticles for cancer applications in the future.