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Modelling the impact of nucleolin expression level on the activity of F3 peptide-targeted pH-sensitive pegylated liposomes containing doxorubicin

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Abstract

Strategies targeting nucleolin have enabled a significant improvement in intracellular bioavailability of their encapsulated payloads. In this respect, assessment of the impact of target cell heterogeneity and nucleolin homology across species (structurally and functionally) is of major importance. This work also aimed at mathematically modelling the nucleolin expression levels at the cell membrane, binding and internalization of pH-sensitive pegylated liposomes encapsulating doxorubicin and functionalized with the nucleolin-binding F3 peptide (PEGASEMP), and resulting cytotoxicity against cancer cells from mouse, rat, canine, and human origin. Herein, it was shown that nucleolin expression levels were not a limitation on the continuous internalization of F3 peptide-targeted liposomes, despite the saturable nature of the binding mechanism. Modeling enabled the prediction of nucleolin-mediated total doxorubicin exposure provided by the experimental settings of the assessment of PEGASEMP’s impact on cell death. The former increased proportionally with nucleolin-binding sites, a measure relevant for patient stratification. This pattern of variation was observed for the resulting cell death in nonsaturating conditions, depending on the cancer cell sensitivity to doxorubicin. This approach differs from standard determination of cytotoxic concentrations, which normally report values of incubation doses rather than the actual intracellular bioactive drug exposure. Importantly, in the context of development of nucleolin-based targeted drug delivery, the structural nucleolin homology (higher than 84%) and functional similarity across species presented herein, emphasized the potential to use toxicological data and other metrics from lower species to infer the dose for a first-in-human trial.

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All data generated or analyzed during this study are included in this published article [and its supplementary information files].

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Acknowledgements

MIT-Portugal Program.

Funding

This work was supported by the following projects: QREN/FEDER MultiNanoMed (Ref: 23240). This work was also financed by the European Regional Development Fund (ERDF), through the Centro 2020 Regional Operational Program under project CENTRO-01-0247-FEDER-017646 (ODD4PEGASEMP), and through the COMPETE 2020—Operational Program for Competitiveness and Internationalisation and Portuguese national funds via FCT – Fundação para a Ciência e a Tecnologia, I.P., under projects POCI-01-0145-FEDER-016390 (CancelStem), Euronanomed (FCT reference ENMed/0005/2015), CENTRO-01-0145-FEDER-000012-HealthyAging2020 and CIBB (FCT reference UIDB/04539/2020).

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  1. Rui Lopes, Kevin Shi, and Nuno A. Fonseca contributed equally.

Authors and Affiliations

  1. CNC – Center for Neurosciences and Cell Biology, Center for Innovative Biomedicine and Biotechnology (CIBB), Faculty of Medicine (Polo 1), Rua Larga, University of Coimbra, 3004-504, Coimbra, Portugal

    Rui Lopes, Nuno A. Fonseca, Sérgio Simões & João N. Moreira

  2. Department of Biological Engineering and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA

    Kevin Shi & Bruce Tidor

  3. TREAT U, SA - Parque Industrial de Taveiro, Lote 44, 3045-508, Coimbra, Portugal

    Nuno A. Fonseca & Vera Moura

  4. Animal and Veterinary Research Centre (CECAV), University of Trás-Os-Montes and Alto Douro (UTAD), Quinta de Prados, Apartado 1013, 5000-801, Vila Real, Portugal

    Adelina Gama

  5. Laboratory of Cellular and Molecular Biology, NOVA Medical School, New University of Lisbon, Campo Mártires da Pátria, 130, 1169-056, Lisboa, Portugal

    José S. Ramalho

  6. Blueclinical, Ltd, 4460-439, Senhora da Hora, Matosinhos, Portugal

    Luís Almeida

  7. UC – University of Coimbra, CIBB, Faculty of Pharmacy, Pólo das Ciências da Saúde, Azinhaga de Santa Comba, 3000-548, Coimbra, Portugal

    Sérgio Simões & João N. Moreira

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Contributions

R.L., K.S., and N.A.F. contributed equally for this work. R.L. designed and performed experiments, analyzed data, prepared figures, wrote and edited the manuscript. K.S. designed and performed the mathematical modeling, prepared figures, wrote and edited the manuscript. N.A.F. designed experiments, performed data interpretation, prepared figures, wrote, and edited the manuscript. A.G. provided support on the canine cell line and edited the manuscript. J.S.R. performed the conservation analysis and edited the manuscript. L.A. contributed to the design of the experiments. V.M. and S.S. supervised all the components of the study and edited the manuscript. B.T. supervised the mathematical modeling and edited the manuscript. J.N.M. supervised all components of this study, designed experiments, wrote and edited the manuscript.

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Correspondence to Bruce Tidor.

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V.M. and N.A.F. were former employees at TREAT U, SA. S.S., L.A. and J.N.M. are share-holders of TREAT U, SA. The remaining authors declare no competing interests.

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Lopes, R., Shi, K., Fonseca, N.A. et al. Modelling the impact of nucleolin expression level on the activity of F3 peptide-targeted pH-sensitive pegylated liposomes containing doxorubicin. Drug Deliv. and Transl. Res. 12, 629–646 (2022). https://doi.org/10.1007/s13346-021-00972-z

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