| Literature DB >> 28910151 |
Patty Wong1, Lin Li2, Junie Chea2, Melissa K Delgado2, Erasmus Poku2, Barbara Szpikowska2, Nicole Bowles2, Megan Minnix2, David Colcher2, Jeffrey Y C Wong1, John E Shively2, Paul J Yazaki2.
Abstract
The blood clearance of chemotherapeutic drugs such as doxorubicin (Dox) can be extended by incorporation into lipid nanoparticles (LNPs) and further improved by tumor targeting with antibody fragments. We used positron emission tomography (PET) imaging in a murine prostate cancer model to evaluate tumor targeting of LNPs incorporating Dox and antiprostate-specific membrane antigen (PSMA) diabodies. Dox-LNPs were generated by mixing or covalent attachment to water soluble distearoylphosphatidyl ethanolamine-polyethylene glycol (DSPE-PEG)2000. Cu-64 PET imaging was performed with DOTA-conjugated Dox, PEG-LNP, or an anti-PSMA site-specific cysteine-diabody. Since the mixture Dox+PEG-LNP was unstable in serum, further studies utilized Dox covalently bound to LNP ± covalently bound DOTA-cys-diabody (cys-DB)-LNP. Blood clearance of covalent Dox-PEG-LNP was slower than Dox alone or Dox+PEG-LNP. PET imaging of 64Cu-DOTA-Dox-PEG-LNP reached a maximum of 10% ID/g in tumors compared with 3% ID/g of 64Cu-DOTA-Dox, due to the prolonged blood clearance. Mixing 64Cu-DOTA-cys-DB-PEG-LNP with covalent Dox-PEG-LNP gave LNPs containing both drug and tumor targeting cys-DB. The mixed LNPs exhibited increased tumor uptake (15% ID/g) versus untargeted 64Cu-DOTA-Dox-PEG-LNPs (10% ID/g) demonstrating feasibility of the approach. Based on these results, a therapy study with mixed LNPs containing cys-DB-LNP and either Dox-LNP or the antitubulin drug auristatin-LNP showed significant reduction of tumor growth with the auristatin-diabody-LNP mixture, but not the Dox-diabody-LNP mixture.Entities:
Keywords: diabody; doxorubicin; lipid nanoparticles; positron emission tomography; prostate cancer
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Year: 2017 PMID: 28910151 PMCID: PMC5646751 DOI: 10.1089/cbr.2017.2253
Source DB: PubMed Journal: Cancer Biother Radiopharm ISSN: 1084-9785 Impact factor: 3.099