Kendrick, Felicity, Evans, Neil D., Arnulf, Bertrand, Avet-Loiseau, Hervé, Decaux, Olivier, Dejoie, Thomas, Fouquet, Guillemette, Guidez, Stéphanie, Harel, Stéphanie, Hebraud, Benjamin, Javaugue, Vincent, Richez, Valentine, Schraen, Susanna, Touzeau, Cyrille, Moreau, Philippe, Leleu, Xavier, Harding, Stephen and Chappell, Michael J. (2017) Analysis of a compartmental model of endogenous immunoglobulin G metabolism with application to multiple myeloma. Frontiers in Physiology, 8 . 149. doi:10.3389/fphys.2017.00149

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Abstract

Immunoglobulin G (IgG) metabolism has received much attention in the literature for two reasons: (i) IgG homeostasis is regulated by the neonatal Fc receptor (FcRn), by a pH-dependent and saturable recycling process, which presents an interesting biological system; (ii) the IgG-FcRn interaction may be exploitable as a means for extending the plasma half-life of therapeutic monoclonal antibodies, which are primarily IgG-based. A less-studied problem is the importance of endogenous IgG metabolism in IgG multiple myeloma. In multiple myeloma, quantification of serum monoclonal immunoglobulin plays an important role in diagnosis, monitoring and response assessment. In order to investigate the dynamics of IgG in this setting, a mathematical model characterizing the metabolism of endogenous IgG in humans is required. A number of authors have proposed a two-compartment nonlinear model of IgG metabolism in which saturable recycling is described using Michaelis-Menten kinetics; however it may be difficult to estimate the model parameters from the limited experimental data that are available. The purpose of this study is to analyse the model alongside the available data from experiments in humans and estimate the model parameters. In order to achieve this aim we linearize the model and use several methods of model and parameter validation: stability analysis, structural identifiability analysis, and sensitivity analysis based on traditional sensitivity functions and generalized sensitivity functions. We find that all model parameters are identifiable, structurally and taking into account parameter correlations, when several types of model output are used for parameter estimation. Based on these analyses we estimate parameter values from the limited available data and compare them with previously published parameter values. Finally we show how the model can be applied in future studies of treatment effectiveness in IgG multiple myeloma with simulations of serum monoclonal IgG responses during treatment.

Item Type:	Journal Article
Subjects:	Q Science > QP Physiology Q Science > QR Microbiology R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Divisions:	Faculty of Science > Engineering
SWORD Depositor:	Library Publications Router
Library of Congress Subject Headings (LCSH):	Metabolism, Immunoglobulin G, Multiple myeloma
Journal or Publication Title:	Frontiers in Physiology
Publisher:	Frontiers Research Foundation
ISSN:	1664-042X
Official Date:	17 March 2017
Dates:	Date Event 17 March 2017 Published 24 February 2017 Accepted
Volume:	8
Article Number:	149
DOI:	10.3389/fphys.2017.00149
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access
Funder:	Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC), Engineering and Physical Sciences Research Council (EPSRC)

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