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Surface Ligand Valency and Immunoliposome Binding: when More Is Not Always Better

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Abstract

Purpose

Nano-drug delivery systems are designed to contain surface ligands including antibodies for “active targeting”. The number of ligands on each nanoparticle, known as the valency, is considered a critical determinant of the “targeting” property. We sought to understand the correlation between valency and binding properties using antibody conjugated liposomes, i.e. immunoliposomes (ILs), as the model.

Methods

Anti-CD3 Fab containing a terminal cysteine residue were conjugated to DSPE-PEG-maleimide and incubated with preformed liposomes at 60°C. The un-incorporated antibodies were removed and the obtained ILs were characterized to contain in average 2–22 copies of anti-CD3 Fabs per liposome. The Biolayer Interferometry (BLI) probe surface was coated with various densities of CD3 epsilon&delta heterodimer (CD3D/E) to imitate different CD3 expression levels on target cells. The inference wavelength shifts upon anti-CD3 liposome binding were monitored and analyzed.

Results

The data indicated ILs may bind either monovalently or multivalently, determined mainly by the surface ligand density rather than the ILs antibody valency. The ILs valency indeed correlated with the dissociation rate constant (Koff), but not with the association rate constant (Kon). Their binding capabilities also did not necessarily increase with the surface anti-CD3 valency.

Conclusion

We proposed a model for understanding the binding properties of ILs with different ligand valencies. The binding mode may change when the targeted surfaces had different antigen densities. The model should be important for the designing and optimization of active targeting drug delivery systems to fit different applications.

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References

  1. Barenholz Y. Doxil®--the first FDA-approved nano-drug: lessons learned. J Control Release. 2012;160(2):117–34.

    Article  CAS  Google Scholar 

  2. Park J, Park JE, Hedrick VE, Wood KV, Bonham C, Lee W, et al. A comparative in vivo study of albumin-coated paclitaxel nanocrystals and Abraxane. Small. 2018;14(16):1703670.

    Article  Google Scholar 

  3. Hood ED, Greineder CF, Shuvaeva T, Walsh L, Villa CH, Muzykantov VR. Vascular targeting of radiolabeled liposomes with bio-orthogonally conjugated ligands: single chain fragments provide higher specificity than antibodies. Bioconjug Chem. 2018;29(11):3626–37.

    Article  CAS  Google Scholar 

  4. Niwa T, Kasuya Y, Suzuki Y, Ichikawa K, Yoshida H, Kurimoto A, et al. Novel Immunoliposome Technology for Enhancing the activity of the agonistic antibody against the tumor necrosis factor receptor superfamily. Mol Pharm. 2018;15(9):3729–40.

    Article  CAS  Google Scholar 

  5. Sheng Y, Hu J, Shi J, Lee LJ. Stimuli-responsive carriers for controlled intracellular drug release. Curr Med Chem. 2017;26(13):2377–88.

    Article  Google Scholar 

  6. Munster P, Krop IE, LoRusso P, Ma C, Siegel BA, Shields AF, et al. Safety and pharmacokinetics of MM-302, a HER2-targeted antibody-liposomal doxorubicin conjugate, in patients with advanced HER2-positive breast cancer: a phase 1 dose-escalation study. Br J Cancer. 2018;119(9):1086–93.

    Article  CAS  Google Scholar 

  7. Von Hoff DD, Mita MM, Ramanathan RK, Weiss GJ, Mita AC, LoRusso PM, et al. Phase I study of PSMA-targeted docetaxel-containing nanoparticle BIND-014 in patients with advanced solid tumors. Clin Cancer Res. 2016;22(13):3157–63.

    Article  Google Scholar 

  8. Serrano D, Manthe RL, Paul E, Chadha R, Muro S. How Carrier Size and Valency Modulate Receptor-Mediated Signaling: Understanding the Link between Binding and Endocytosis of ICAM-1-Targeted Carriers. Biomacromolecules. 2016;17(10):3127–37.

    Article  CAS  Google Scholar 

  9. Di J, Xie F, Xu Y. When liposomes met antibodies: Drug delivery and beyond. Adv Drug Deliv Rev. 2020;154–155:151–62.

    Article  Google Scholar 

  10. Alkilany AM, Zhu L, Weller H, Mews A, Parak WJ, Barz M, et al. Ligand density on nanoparticles: a parameter with critical impact on nanomedicine. Adv Drug Deliv Rev. 2019;143(15):22–36.

    Article  CAS  Google Scholar 

  11. Cao J, Zhang Y, Wu Y, Wu J, Wang W, Wu Q, et al. The effects of ligand valency and density on the targeting ability of multivalent nanoparticles based on negatively charged chitosan nanoparticles. Colloids Surf B Biointerfaces. 2017;161(1):508–18.

    PubMed  Google Scholar 

  12. Li MH, Zong H, Leroueil PR, Choi SK, Baker JR Jr. Ligand characteristics important to avidity interactions of multivalent nanoparticles. Bioconjug Chem. 2017;28(6):1649–57.

    Article  CAS  Google Scholar 

  13. Cao J, Li C, Wei X, Tu M, Zhang Y, Xu F, et al. Selective targeting and eradication of LGR5+ Cancer stem cells using RSPO-conjugated doxorubicin liposomes. Mol Cancer Ther. 2018;17(7):1475–85.

    Article  CAS  Google Scholar 

  14. Belfiore L, Spenkelink LM, Ranson M, van Oijen AM, Vine KL. Quantification of ligand density and stoichiometry on the surface of liposomes using single-molecule fluorescence imaging. J Control Release. 2018;278:80–6.

    Article  CAS  Google Scholar 

  15. Johnsen KB, Bak M, Kempen PJ, Melander F, Burkhart A, Thomsen MS, et al. Antibody affinity and valency impact brain uptake of transferrin receptor-targeted gold nanoparticles. Theranostics. 2018;8(12):3416–36.

    Article  CAS  Google Scholar 

  16. Espelin CW, Leonard SC, Geretti E, Wickham TJ, Hendriks BS. Dual HER2 targeting with Trastuzumab and liposomal-encapsulated doxorubicin (MM-302) demonstrates synergistic antitumor activity in breast and gastric Cancer. Cancer Res. 2016;76(6):1517–27.

    Article  CAS  Google Scholar 

  17. Hrkach J, Von Hoff D, Mukkaram Ali M, Andrianova E, Auer J, Campbell T, et al. Preclinical development and clinical translation of a PSMA-targeted docetaxel nanoparticle with a differentiated pharmacological profile. Sci Transl Med. 2012;4(128):128ra39.

    Article  Google Scholar 

  18. Ouyang S, Hu B, Zhou R, Liu D, Peng D, Li Z, et al. Rapid and sensitive detection of nodularin-R in water by a label-free BLI aptasensor. Analyst. 2018;143(18):4316–22.

    Article  CAS  Google Scholar 

  19. Brunner J, Skrabal P, Hauser H. Single bilayer vesicles prepared without sonication. Physico-Chem Properties Biochim Biophys Acta. 1976;455(2):322–31.

    Article  CAS  Google Scholar 

  20. Iden DL, Allen TM. In vitro and in vivo comparison of immunoliposomes made by conventional coupling techniques with those made by a new post-insertion approach. BBA-Biomembranes. 2001;1513(2):207–16.

    Article  CAS  Google Scholar 

  21. Loomis K, Smith B, Feng Y, Garg H, Yavlovich A, Campbell-Massa R, et al. Specific targeting to B cells by lipid-based nanoparticles conjugated with a novel CD22-ScFv. Exp Mol Pathol. 2010;88(2):238–49.

    Article  CAS  Google Scholar 

  22. Kulkarni CV. Calculating the 'chain splay' of amphiphilic molecules: towards quantifying the molecular shapes. Chem Phys Lipids. 2019;218:16–21.

    Article  CAS  Google Scholar 

  23. Do T, Ho F, Heidecker B, Witte K, Chang L, Lerner L. A rapid method for determining dynamic binding capacity of resins for the purification of proteins. Protein Expr Purif. 2008;60(2):147–50.

    Article  CAS  Google Scholar 

  24. Kumaraswamy S, Tobias R. Label-free kinetic analysis of an antibody-antigen interaction using biolayer interferometry. Methods Mol Biol. 2015;1278:165–82.

    Article  CAS  Google Scholar 

  25. Verzijl D, Riedl T, Parren PWHI, Gerritsen AF. A novel label-free cell-based assay technology using biolayer interferometry. Biosens Bioelectron. 2016;87:388–95.

    Article  Google Scholar 

  26. Concepcion J, Witte K, Wartchow C, Choo S, Yao D, Persson H, et al. Label-free detection of biomolecular interactions using BioLayer interferometry for kinetic characterization. Comb Chem High Throughput Screen. 2009;12(8):791–800.

    Article  CAS  Google Scholar 

  27. Chen Q, Yuan S, Sun H, Peng L. CD3+CD20+ T cells and their roles in human diseases. Hum Immunol. 2019;80(3):191–4.

    Article  CAS  Google Scholar 

  28. Wernly B, Paar V, Aigner A, Pilz PM, Podesser BK, Förster M, et al. Anti-CD3 antibody treatment reduces scar formation in a rat model of myocardial infarction. Cells. 2020;9(2):295.

    Article  CAS  Google Scholar 

  29. Cook DP, JPMCM C, Martens PJ, Sassi G, Mancarella F, Ventriglia G, et al. Intestinal Delivery of Proinsulin and IL-10 via Lactococcus lactis Combined With Low-Dose Anti-CD3 Restores Tolerance Outside the Window of Acute Type 1 Diabetes Diagnosis. Front Immunol. 2020;11:1103.

    Article  CAS  Google Scholar 

  30. Mathis KW, Taylor EB, Ryan MJ. Anti-CD3 antibody therapy attenuates the progression of hypertension in female mice with systemic lupus erythematosus. Pharmacol Res. 2017;120:252–7.

    Article  CAS  Google Scholar 

  31. Lambert C, Genin C. CD3 bright lymphocyte population reveal gammadelta T cells. Cytometry B Clin Cytom. 2004;61(1):45–53.

    Article  Google Scholar 

  32. Mullersman JE, White G, Tung KS. Differential staining of human alpha beta and gamma delta T cells by the fluorescein conjugate of an anti-CD3 monoclonal antibody. Clin Exp Immunol. 1991;84(2):324–8.

    Article  CAS  Google Scholar 

  33. Wei M, Shen D, Mulmi Shrestha S, Liu J, Zhang J, Yin Y. The Progress of T cell immunity related to prognosis in gastric Cancer. Biomed Res Int. 2018;2018:3201940.

    PubMed  PubMed Central  Google Scholar 

  34. Walsh SR, Simovic B, Chen L, Bastin D, Nguyen A, Stephenson K, et al. Endogenous T cells prevent tumor immune escape following adoptive T cell therapy. J Clin Invest. 2019;129(12):5400–10.

    Article  CAS  Google Scholar 

  35. Chen X, Song M, Zhang B, Zhang Y. Reactive oxygen species regulate T cell immune response in the tumor microenvironment. Oxidative Med Cell Longev. 2016;2016:1580967.

    Google Scholar 

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Data Availability Statement

The datasets generated during the current study are available from the corresponding authors upon request.

Funding

This study was supported by the National Natural Science Foundation of China (NSFC) No. 81690262 and Fundings from Yunnan Provincial Sci & Tech Department.

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Authors and Affiliations

Authors

Contributions

H. Li designed and implement the experiments and wrote the manuscript.

J. Di did some experiments, analyzed the data and wrote the manuscript.

B. Peng helped in the experiment implementation.

Y. Xu designed the study, analyzed the data and wrote the manuscript.

N. Zhang designed the study, analyzed the data and revised the manuscript.

Corresponding authors

Correspondence to Yuhong Xu or Ning Zhang.

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Li, H., Di, J., Peng, B. et al. Surface Ligand Valency and Immunoliposome Binding: when More Is Not Always Better. Pharm Res 38, 1593–1600 (2021). https://doi.org/10.1007/s11095-021-03092-y

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  • DOI: https://doi.org/10.1007/s11095-021-03092-y

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