Tailoring nanoparticle designs to target cancer based on tumor pathophysiology.

Abstract

Nanoparticles can provide significant improvements in the diagnosis and treatment of cancer. How nanoparticle size, shape, and surface chemistry can affect their accumulation, retention, and penetration in tumors remains heavily investigated, because such findings provide guiding principles for engineering optimal nanosystems for tumor targeting. Currently, the experimental focus has been on particle design and not the biological system. Here, we varied tumor volume to determine whether cancer pathophysiology can influence tumor accumulation and penetration of different sized nanoparticles. Monte Carlo simulations were also used to model the process of nanoparticle accumulation. We discovered that changes in pathophysiology associated with tumor volume can selectively change tumor uptake of nanoparticles of varying size. We further determine that nanoparticle retention within tumors depends on the frequency of interaction of particles with the perivascular extracellular matrix for smaller nanoparticles, whereas transport of larger nanomaterials is dominated by Brownian motion. These results reveal that nanoparticles can potentially be personalized according to a patient's disease state to achieve optimal diagnostic and therapeutic outcomes.