RGD_PLGA Nanoparticles with Docetaxel: A Route for Improving Drug Efficiency and Reducing Toxicity in Breast Cancer Treatment

Breast cancer is the leading cause of cancer-related death in women. Although many therapeutic approaches are available, systemic chemotherapy remains the primary choice, especially for triple-negative and advanced breast cancers. Unfortunately, systemic chemotherapy causes serious side effects and requires high doses to achieve an effective concentration in the tumor. Thus, the use of nanosystems for drug delivery may overcome these limitations. Herein, we formulated Poly (lactic-co-glycolic acid) nanoparticles (PLGA-NPs) containing Docetaxel, a fluorescent probe, and a magnetic resonance imaging (MRI) probe. The cyclic RGD tripeptide was linked to the PLGA surface to actively target αvβ3 integrins, which are overexpressed in breast cancer. PLGA-NPs were characterized using dynamic light scattering, fast field-cycling 1H-relaxometry, and 1H-nuclear magnetic resonance. Their therapeutic effects were assessed both in vitro in triple-negative and HER2+ breast cancer cells, and in vivo in murine models. In vivo MRI and inductively coupled plasma mass spectrometry of excised tumors revealed a stronger accumulation of PLGA-NPs in the RGD_PLGA group. Targeted PLGAs have improved therapeutic efficacy and strongly reduced cardiac side effects compared to free Docetaxel. In conclusion, RGD-PLGA is a promising system for breast cancer treatment, with positive outcome in terms of therapeutic efficiency and reduction in side effects

Use of FCC-NMRD relaxometry for early detection and characterization of ex-vivo murine breast cancer

We acknowledge COST Action AC15209 (EURELAX) for scientific support. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 668119 (project “IDentIFY”). The Italian Ministry for Education and Research (MIUR) is gratefully aknowledged for yearly FOE funding to the Euro-BioImaging Multi-Modal Molecular Imaging Italian Node (MMMI). E.D.G. and G.F. gratefully acknowledge FIRC-AIRC (Fondazione Italiana per la Ricerca sul Cancro AIRC) for their fellowships. We gratefully acknowledge Lionel Broche for the interesting discussion about mathematical models and procedures for the fitting of NMRD data.Peer reviewedPublisher PD

Peptide-Based Soft Hydrogels Modified with Gadolinium Complexes as MRI Contrast Agents

Poly-aromatic peptide sequences are able to self-assemble into a variety of supramolecular aggregates such as fibers, hydrogels, and tree-like multi-branched nanostructures. Due to their biocompatible nature, these peptide nanostructures have been proposed for several applications in biology and nanomedicine (tissue engineering, drug delivery, bioimaging, and fabrication of biosensors). Here we report the synthesis, the structural characterization and the relaxometric behavior of two novel supramolecular diagnostic agents for magnetic resonance imaging (MRI) technique. These diagnostic agents are obtained for self-assembly of DTPA(Gd)-PEG8-(FY)3 or DOTA(Gd)-PEG8-(FY)3 peptide conjugates, in which the Gd-complexes are linked at the Nterminus of the PEG8-(FY)3 polymer peptide. This latter was previously found able to form selfsupporting and stable soft hydrogels at a concentration of 1.0% wt. Analogously, also DTPA(Gd)PEG8-(FY)3 and DOTA(Gd)-PEG8-(FY)3 exhibit the trend to gelificate at the same range of concentration. Moreover, the structural characterization points out that peptide (FY)3 moiety keeps its capability to arrange into β-sheet structures with an antiparallel orientation of the β-strands. The high relaxivity value of these nanostructures (~12 mM−1·s−1 at 20 MHz) and the very low in vitro cytotoxicity suggest their potential application as supramolecular diagnostic agents for MRI

Generation of multiparametric MRI maps by using Gd-labelled-RBCs reveals phenotypes and stages of murine prostate cancer

We acknowledge BRACCO Imaging for providing Gadoteridol (ProHance). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 668119 (project “IDentIFY”) and No 667510 (project “GLINT”) and it was performed in the framework of COST Action AC15209 (EURELAX). E.D.G. and G.F. were supported by FIRC-AIRC (Fondazione Italiana per la Ricerca sul Cancro AIRC) fellowships.Peer reviewedPublisher PD