Noninvasive multimodal and multiparametric imaging for preclinical tumor characterization and nanoparticle validation

Cancer is the world’s number one killer. Conventional cancer treatment, however, is still insufficient for many patients, in part due to the large inter- and intra-tumoral heterogeneity and the many therapy-associated side effects. Therefore, the search for novel and especially, personalized and targeted strategies is still on-going. Furthermore, close monitoring of the treatment using different non-invasive imaging modalities is essential. To fill this treatment gap, highly biocompatible and theranostic iron oxide (IO) nanoparticles (NPs) have been suggested and developed. These combine a diagnostic agent and a therapeutic compound, which can be targeted to the tumor. However, their translation to the clinic has been limited to mainly applications in the liver as over 99% of the systemically injected IONPs do not reach the tumor, but are eliminated by the organs of the reticuloendothelial system. Furthermore, IONPs are difficult to visualize in the liver in vivo due to their negative contrast properties. In this PhD project, we aimed at addressing these limitations in a preclinical setting. First, we aimed at improving NP uptake within the tumors. Therefore, we developed a multimodal, multiparametric approach to characterize a subcutaneous tumor model of HER2+ ovarian cancer in mice and thus, to determine the most optimal time window for nanomaterial-based therapy. Within this time window, we tested different IONPs in order to evaluate their tumor uptake. Last, we created and validated a dual PET/MR contrast agent to improve their biodistribution assessment over all organs of the body. In conclusion, we addressed two major limitations hindering the translation of IONPs to the clinic. Despite their promise and these small steps forward made in this project, more focus on tumor biology is required to improve the translation of these theranostics to the clinic.