Modelling Serum Immunoglobulin Responses in Multiple Myeloma
In intact immunoglobulin multiple myeloma (MM), patients are monitored using blood tests detecting monoclonal immunoglobulins (Igs) produced by the cancer. Each clone secretes a unique, monoclonal Ig, whose biological properties depend on its type and structure. Recent work by this collaborative multidisciplinary group has found that the different metabolisms of the monoclonal Igs may have a large impact on their response to therapy and thus their utilisation as effective markers. Introduction of novel agents has substantially improved the life expectancy of patients with MM. As such greater emphasis is being placed on markers of response, including the assessments of speed and depth of response. Our multidisciplinary uses of mathematical models in combination with clinical trial data have the potential to provide insights that can inform clinical practice and contribute to the state-of-the-art in patient management.
We are primarily interested in IgA and IgG metabolism in MM. 75% of all MM patients have IgA- or IgG-secreting plasma cell clones. We use mathematical models of IgA and IgG metabolism to predict the relationship between tumour response and Ig response. We then analyse the relationship between Ig responses and survival outcomes in clinical trials.
IgG metabolism
IgG is the most abundant Ig isotype in the circulation, having a plasma concentration of 10–16 g/l . Its high concentration is enabled by its unusually long metabolic half-life. Interestingly the half-life of IgG is not constant, but varies with its plasma concentration, as indicated by the results of tracer experiments.
 |
Plasma concentration-dependence of (a) half-life and (b) fractional catabolic rate of IgG; data from Waldmann et al. (1969) |
The relationship between the concentration and half-life of IgG can be explained by its route of catabolism, mediated by the neonatal Fc receptor (FcRn). The receptor derives its name from its role in transporting IgG across the placenta from mother to foetus.
 |
FcRn-mediated recycling of IgG. (1) IgG molecules are internalised into endosomes by nonspecific pinocytosis. (2) Endosomes acidify allowing FcRn to bind IgG. Bound and unbound proteins are sorted, with (3) unbound proteins degraded in lysosomes and (4) bound IgG trafficked to the cell surface. (5) Bound IgG is exocytosed back into the circulation. |
The Research Problem
IgA and IgG have metabolic half-lives of 6 and 23 days at normal concentrations, respectively. Additionally, the half-life of IgG is concentration-dependent due to saturation of recycling receptors. Consequently IgG clearance is faster when IgG MM patients present and slower after successful induction therapy, when the concentration of IgG is greatly reduced, with recirculating IgG indicating a falsely poor response to treatment. We propose that this causes underestimation of survival in IgG patients when reductions in monoclonal Ig are used as the measure of response.
 |
Illustration of how different elements of the research problem are linked. Each patient has a tumour response to treatment. Rather than assess the tumour response, clinicians measure the serum monoclonal Ig response, which is dependent on the tumour response AND the metabolic rate of the Ig. Our goal is to assess whether Ig metabolism affects the association between measured serum monoclonal Ig responses and survival outcomes. |
The Research Team
|
Felicity Kendrick Postdoctoral research assistant (PDRA), University of Warwick Felicity started working on immunoglobulin metabolism in multiple myeloma in her PhD at the University of Warwick, as part of the Midlands Integrative Biosciences Training Partnership (MIBTP). Her interests include physiological systems modelling and survival analysis. |
 |
 |
Dr Mike Chappell, principal investigator Reader, University of Warwick Mike Chappell along with Neil Evans are supervising the project at the University of Warwick. Mike's areas of expertise include biomedical systems modelling, compartmental modelling, nonlinear dynamics and system identification. Mike's expertise in structural identifiability is particularly important in this project in order to determine which parameters are uniquely identifiable from available data. |
|
Dr Neil Evans Associate professor, University of Warwick Neil Evans is interested in systems modelling, analysis and control of drug kinetic, epidemiological and biomedical processes. Neil's expertise in system identification is particularly applicable to this project, where parameters need to be estimated from limited data. |
 |
Latest outputs
- Kendrick, F., Evans, N. D., Arnulf, B., Avet-Loiseau, H., Decaux, O., Dejoie, T., Fouquet, G., Guidez, S., Harel, S., Hebraud, B., Javaugue, V., Richez, V., Schraen, S., Touzeau, C., Moreau, P., Leleu, X., Harding, S. and Chappell, M. J. (2017), 'Analysis of a compartmental model of endogenous immunoglobulin G metabolism with application to multiple myeloma', Frontiers in Physiology, DOI: 10.3389/fphys.2017.00149
- Kendrick, F., Harding, S., Evans, N. D., Chappell, M. J. (2015), 'Immunoglobulin G (IgG) and neonatal Fc-receptor (FcRn) dynamics in IgG multiple myeloma', IFAC-PapersOnLine, DOI: 10.1016/j.ifacol.2015.10.123
Acknowledgements
This project is financially supported by an EPSRC Impact Acceleration Account (IAA) award.
The project builds on previous research financially supported by a BBSRC Midlands Integrative Biosciences Training Partnership (MIBTP) studentship.
News
17/03/17
Our article written in collaboration with IFM physicians has been published in Frontiers in Physiology doi:10.3389/fphys.2017.00149
09/03/17
Oscar Berlanga of The Binding Site visited Warwick to give a seminar and discuss project progress. In the meeting we discussed response assigment for IgA and IgG patients, and possible novel ways of analysing survival data in myeloma.
24/02/17
Paper accepted in Frontiers in Physiology. Paper in collaboration with Intergroupe Francophone du Myélome (IFM) physicians on a model of IgG metabolism with application to IgG multiple myeloma doi:10.3389/fphys.2017.00149
Useful links