Targeted dual-color silica nanoparticles provide univocal identification of micrometastases in preclinical models of colorectal cancer

Marco Soster,1,* Riccardo Juris,2,* Sara Bonacchi,2 Damiano Genovese,2 Marco Montalti,2 Enrico Rampazzo,2 Nelsi Zaccheroni,2 Paolo Garagnani,2 Federico Bussolino,3,4 Luca Prodi,2 Serena Marchiò1,4 1Institute for Cancer Research and Treatment, Laboratory of Tumor Microenvironment and University of Torino, Department of Oncological Sciences, Candiolo, 2University of Bologna, Department of Chemistry "G.Ciamician", Bologna, 3Institute for Cancer Research and Treatment, Laboratory of Vascular Oncology and University of Torino, Department of Oncological Sciences, Candiolo, 4APAvadis Biotechnologies, BioIndustry Park S Fumero, Colleretto Giacosa, Italy*These authors equally contributed to the workBackground and methods: Despite the recent introduction of targeted bio-drugs, the scarcity of successful therapeutic options for advanced colorectal cancer remains a limiting factor in patient management. The efficacy of curative surgical interventions can only be extended through earlier detection of metastatic foci, which is dependent on both the sensitivity and specificity of the diagnostic tools.Results: We propose a high-performance imaging platform based on silica-poly(ethylene glycol) nanoparticles doped with rhodamine B and cyanine 5. Simultaneous detection of these dyes is the basis for background subtraction and signal amplification, thus providing high-sensitivity imaging. The functionalization of poly(ethylene glycol) tails on the external face of the nanoparticles with metastasis-specific peptides guarantees their homing to and accumulation at target tissues, resulting in specific visualization, even of submillimetric metastases.Conclusions: The results reported here demonstrate that our rationally designed modular nanosystems have the ability to produce a breakthrough in the detection of micrometastases for subsequent translation to clinics in the immediate future.Keywords: colorectal cancer, imaging platform, luminescent targeting, micrometastasis, peptide targeting