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One particle, it seems, can predict the behavior of another. Thankfully, this is not the beginning of a lesson on quantum physics; instead, it is the basis for potentially designing targeted clinical trials in nanomedicine, by knowing if a tumor is likely to respond to a particular therapeutic nanoparticle. Miller et al. hypothesized that if a tumor readily takes up magnetic nanoparticles (MNP), it will also accumulate other nanoparticles carrying a deadly payload. The authors injected MNPs and a fluorescent version of the therapeutic nanoparticles into mice and followed their biodistribution using imaging. Both types of nanoparticles had similar pharmacokinetics and uptake in tumor-associated host cells owing to the enhanced permeability and retention effect. In mice with human tumors, Miller and colleagues found that the tumors with high MNP uptake were significantly more responsive than those with medium or low uptake to nanoparticles delivering chemotherapeutics. Thus, MNPs can be used as companion imaging agents during nanomedicine trials to predict the therapeutic effect of their nanosized counterparts.
Therapeutic nanoparticles (TNPs) have shown heterogeneous responses in human clinical trials, raising questions of whether imaging should be used to identify patients with a higher likelihood of NP accumulation and thus therapeutic response. Despite extensive debate about the enhanced permeability and retention (EPR) effect in tumors, it is increasingly clear that EPR is extremely variable; yet, little experimental data exist to predict the clinical utility of EPR and its influence on TNP efficacy. We hypothesized that a 30-nm magnetic NP (MNP) in clinical use could predict colocalization of TNPs by magnetic resonance imaging (MRI). To this end, we performed single-cell resolution imaging of fluorescently labeled MNPs and TNPs and studied their intratumoral distribution in mice. MNPs circulated in the tumor microvasculature and demonstrated sustained uptake into cells of the tumor microenvironment within minutes. MNPs could predictably demonstrate areas of colocalization for a model TNP, poly(d,l-lactic-co-glycolic acid)-b-polyethylene glycol (PLGA-PEG), within the tumor microenvironment with >85% accuracy and circulating within the microvasculature with >95% accuracy, despite their markedly different sizes and compositions. Computational analysis of NP transport enabled predictive modeling of TNP distribution based on imaging data and identified key parameters governing intratumoral NP accumulation and macrophage uptake. Finally, MRI accurately predicted initial treatment response and drug accumulation in a preclinical efficacy study using a paclitaxel-encapsulated NP in tumor-bearing mice. These approaches yield valuable insight into the in vivo kinetics of NP distribution and suggest that clinically relevant imaging modalities and agents can be used to select patients with high EPR for treatment with TNPs.
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