January  2017, 14(1): 305-319. doi: 10.3934/mbe.2017020

The role of TNF-α inhibitor in glioma virotherapy: A mathematical model

1. 

Institute of Mathematics, Lodz University of Technology, 90-924 Lodz, Poland

2. 

Dept. of Mathematics and Statistics, Southern Illinois University Edwardsville, Illinois, 62026-1653, USA

3. 

Department of Mathematics, The Ohio State University, Columbus, OH 43210, USA

Received  June 22, 2016 Accepted  June 30, 2016 Published  October 2016

Virotherapy, using herpes simplex virus, represents a promising therapy of glioma. But the innate immune response, which includes TNF-α produced by macrophages, reduces the effectiveness of the treatment. Hence treatment with TNF-α inhibitor may increase the effectiveness of the virotherapy. In the present paper we develop a mathematical model that includes continuous infusion of the virus in combination with TNF-α inhibitor. We study the efficacy of the treatment under different combinations of the two drugs for different scenarios of the burst size of newly formed virus emerging from dying infected cancer cells. The model may serve as a first step toward developing an optimal strategy for the treatment of glioma by the combination of TNF-α inhibitor and oncolytic virus injection.

Citation: Elzbieta Ratajczyk, Urszula Ledzewicz, Maciej Leszczynski, Avner Friedman. The role of TNF-α inhibitor in glioma virotherapy: A mathematical model. Mathematical Biosciences & Engineering, 2017, 14 (1) : 305-319. doi: 10.3934/mbe.2017020
References:
[1]

C. Antoni and J. Braun, Side effects of anti-TNF therapy: Current knowledge, Clin Exp Rheumatol, 22 (2002), 152-157. Google Scholar

[2]

B. AuffingerA.U. Ahmed and M.S. Lesniak, Oncolytic virotherapy for malignant glioma: Translating laboratory insights into clinical practice, Front. Oncol., 3 (2013), 1-32. doi: 10.3389/fonc.2013.00032. Google Scholar

[3]

E.A. Chiocca, Oncolytic viruses, Nat. Rev. Cancer, 2 (2002), 938-950. Google Scholar

[4]

L.K. CsataryG. GosztonyiJ. SzeberenyiZ. FabianV. LiszkaB. Bodey and C.M. Csatary, MTH-68/H oncolytic viral treatment in human highgrade gliomas, J. Neurooncol, 67 (2004), 83-93. Google Scholar

[5]

A. FriedmanJ. TianG. FulciE. Chioca and J. Wang, Glioma virotherapy: Effects of innate immune suppression and increased viral replication capacity, Cancer Res., 66 (2006), 2314-2319. doi: 10.1158/0008-5472.CAN-05-2661. Google Scholar

[6]

G. FulciL. BreymannD. GianniK. KurozomiS.S. RheeJ. YuB. KaurD.N. LouisR. WeisslederM.A. Caligiuri and E.A. Chiocca, Cyclophosphamide enhances glioma virotherapy by inhibiting innate immune responses, PNAS, 103 (2006), 12873-12878. doi: 10.1073/pnas.0605496103. Google Scholar

[7]

I. GanlyD. KirnG. EckhardtG.I. RodriguezD.S. SoutarR. OttoA.G. RobertsonO. ParkM.L. GulleyC. HeiseD.D. Von HoffS.B. Kaye and S.G. Eckhardt, A phase I study of ONYX-015, an EiBattenuated adenovirus, administered intratumorally to patients with recurrent head and neck cancer, Clin. Cancer Res., 6 (2000), 798-806. Google Scholar

[8]

M.P. HallsworthC.P. SohS.J. LaneJ.P. Arm and T.H. Lee, Selective enhancement of GM-CSF, TNF-alpha, IL-1 and IL-8 production by monocytes and macrophages of asthmatic subjects, Eur Respir J., 7 (1994), 1096-1102. Google Scholar

[9]

W. HaoE.D. Crouser and A. Friedman, Mathematical model of sarcoidosis, PNAS, 111 (2014), 16065-16070. doi: 10.1073/pnas.1417789111. Google Scholar

[10]

K. JacobsenL. RusselB. Kaur and A. Friedman, Effects of CCN1 and macrophage content on glioma virotherapy: A mathematical model, Bull Math Biol, 77 (2015), 984-1012. doi: 10.1007/s11538-015-0074-8. Google Scholar

[11]

F.R. KhuriJ. NemunaitisI. GanlyJ. ArseneauI.F. TannockL. RomelM. GoreJ. IronsideR.H. MacDougallC. HeiseB. RandleyA.M. GillenwaterP. BruseS.B. KayeW.K. Hong and D.H. Kirn, A controlled trial of ONYX-015, a selectively-replicating adenovirus, in combination with cisplatin and 5-fluorouracil in patients with recurrent head and neck cancer, Nat. Med., 6 (2000), 879-885. Google Scholar

[12]

Y. Kim, H. G. Lee, N. Dmitrieva, J. Kim, B. Kaur and A. Friedman, Choindroitinase ABC I-mediated enhancement of oncolytic virus spread and anti tumor efficacy: A mathematical model PLOS ONE 9 (2014), e102499. doi: 10.1371/journal.pone.0102499. Google Scholar

[13]

R.M. LorenceA.L. PecoraP.P. MajorS.J. HotteS.A. LaurieM.S. RobertsW.S. Groene and M.K. Bamat, Overview of phase I studies of intravenous administration of PV701, an oncolytic virus, Curr. Opin. Mol. Ther., 5 (2003), 618-624. Google Scholar

[14]

J.M. Markert, Conditionally replicating herpes simplex virus mutant, G207 for the treatment of malignant glioma: Results of a phase I trial, Gene. Ther., 7 (2000), 867-874. doi: 10.1038/sj.gt.3301205. Google Scholar

[15]

W.H. MeisenE.S. WohlebA.C. Jaime-RamirezC. BolyardJ.Y. YooL. RusselJ. HardcastleS. DubinK. MuiliJ. YuM. CallgiuriJ. Godbout and B. Kaur, The impact of macrophage-and microglia-secreted TNF-α on oncolitic hsv-1 therapy in the glioblastoma tumor microenvironment, Clin Cancer Res., 21 (2015), 3274-3285. Google Scholar

[16]

T. MinetaS. RabkinT. YazakiW. Hunter and R. Martuza, Attenuated multi-mutated herpes simplex virus-1 for the treatment of malignant gliomas, Nat. Med., 1 (1995), 938-943. doi: 10.1038/nm0995-938. Google Scholar

[17]

J.C. OliverL.A. BlandC.W. OettingerM.J. ArduinoS.K. McAllisterS.M. Aguero and M.S. Favero, Cytokine kinetics in an in vitro whole blood model following an endotoxin challenge, Lymphokine Cytokine Res., 12 (1993), 115-120. Google Scholar

[18]

R. RodriguezE.R. SchuurH.Y. LimG.A. HendersonJ.W. Simons and D.R. Henderson, Prostate attenuated replication competent daenovirus (ARCA) CN706: A selective cytotoxic for prostate-specific anti-positive prostate cancer cells, Cancer Res., 57 (2000), 2559-2563. Google Scholar

[19]

H. Schättler and U. Ledzewicz, Optimal Control for Mathematical Models of Cancer Therapies Springer Publishing Co., New York, USA, 2015. doi: 10.1007/978-1-4939-2972-6. Google Scholar

[20]

G. WollmannK. Ozduman and A. N. van den Pol, Oncolytic virus therapy for glioblastoma multiforme: Concepts and candidates, Cancer J., 18 (2012), 69-81. doi: 10.1097/PPO.0b013e31824671c9. Google Scholar

[21]

J.T. WuH.M. ByrneD.H. Kirn and L.M. Wein, Modeling and analysis of a virus that replicates selectively in tumor cells, Bull. Math. Biol., 63 (2001), 731-768. doi: 10.1006/bulm.2001.0245. Google Scholar

[22]

J.T. WuD.H. Kirn and L.M. Wein, Analysis of a three-way race between tumor growth, a replication-competent virus and an immune response, Bull. Math. Biol., 66 (2004), 605-625. doi: 10.1016/j.bulm.2003.08.016. Google Scholar

show all references

References:
[1]

C. Antoni and J. Braun, Side effects of anti-TNF therapy: Current knowledge, Clin Exp Rheumatol, 22 (2002), 152-157. Google Scholar

[2]

B. AuffingerA.U. Ahmed and M.S. Lesniak, Oncolytic virotherapy for malignant glioma: Translating laboratory insights into clinical practice, Front. Oncol., 3 (2013), 1-32. doi: 10.3389/fonc.2013.00032. Google Scholar

[3]

E.A. Chiocca, Oncolytic viruses, Nat. Rev. Cancer, 2 (2002), 938-950. Google Scholar

[4]

L.K. CsataryG. GosztonyiJ. SzeberenyiZ. FabianV. LiszkaB. Bodey and C.M. Csatary, MTH-68/H oncolytic viral treatment in human highgrade gliomas, J. Neurooncol, 67 (2004), 83-93. Google Scholar

[5]

A. FriedmanJ. TianG. FulciE. Chioca and J. Wang, Glioma virotherapy: Effects of innate immune suppression and increased viral replication capacity, Cancer Res., 66 (2006), 2314-2319. doi: 10.1158/0008-5472.CAN-05-2661. Google Scholar

[6]

G. FulciL. BreymannD. GianniK. KurozomiS.S. RheeJ. YuB. KaurD.N. LouisR. WeisslederM.A. Caligiuri and E.A. Chiocca, Cyclophosphamide enhances glioma virotherapy by inhibiting innate immune responses, PNAS, 103 (2006), 12873-12878. doi: 10.1073/pnas.0605496103. Google Scholar

[7]

I. GanlyD. KirnG. EckhardtG.I. RodriguezD.S. SoutarR. OttoA.G. RobertsonO. ParkM.L. GulleyC. HeiseD.D. Von HoffS.B. Kaye and S.G. Eckhardt, A phase I study of ONYX-015, an EiBattenuated adenovirus, administered intratumorally to patients with recurrent head and neck cancer, Clin. Cancer Res., 6 (2000), 798-806. Google Scholar

[8]

M.P. HallsworthC.P. SohS.J. LaneJ.P. Arm and T.H. Lee, Selective enhancement of GM-CSF, TNF-alpha, IL-1 and IL-8 production by monocytes and macrophages of asthmatic subjects, Eur Respir J., 7 (1994), 1096-1102. Google Scholar

[9]

W. HaoE.D. Crouser and A. Friedman, Mathematical model of sarcoidosis, PNAS, 111 (2014), 16065-16070. doi: 10.1073/pnas.1417789111. Google Scholar

[10]

K. JacobsenL. RusselB. Kaur and A. Friedman, Effects of CCN1 and macrophage content on glioma virotherapy: A mathematical model, Bull Math Biol, 77 (2015), 984-1012. doi: 10.1007/s11538-015-0074-8. Google Scholar

[11]

F.R. KhuriJ. NemunaitisI. GanlyJ. ArseneauI.F. TannockL. RomelM. GoreJ. IronsideR.H. MacDougallC. HeiseB. RandleyA.M. GillenwaterP. BruseS.B. KayeW.K. Hong and D.H. Kirn, A controlled trial of ONYX-015, a selectively-replicating adenovirus, in combination with cisplatin and 5-fluorouracil in patients with recurrent head and neck cancer, Nat. Med., 6 (2000), 879-885. Google Scholar

[12]

Y. Kim, H. G. Lee, N. Dmitrieva, J. Kim, B. Kaur and A. Friedman, Choindroitinase ABC I-mediated enhancement of oncolytic virus spread and anti tumor efficacy: A mathematical model PLOS ONE 9 (2014), e102499. doi: 10.1371/journal.pone.0102499. Google Scholar

[13]

R.M. LorenceA.L. PecoraP.P. MajorS.J. HotteS.A. LaurieM.S. RobertsW.S. Groene and M.K. Bamat, Overview of phase I studies of intravenous administration of PV701, an oncolytic virus, Curr. Opin. Mol. Ther., 5 (2003), 618-624. Google Scholar

[14]

J.M. Markert, Conditionally replicating herpes simplex virus mutant, G207 for the treatment of malignant glioma: Results of a phase I trial, Gene. Ther., 7 (2000), 867-874. doi: 10.1038/sj.gt.3301205. Google Scholar

[15]

W.H. MeisenE.S. WohlebA.C. Jaime-RamirezC. BolyardJ.Y. YooL. RusselJ. HardcastleS. DubinK. MuiliJ. YuM. CallgiuriJ. Godbout and B. Kaur, The impact of macrophage-and microglia-secreted TNF-α on oncolitic hsv-1 therapy in the glioblastoma tumor microenvironment, Clin Cancer Res., 21 (2015), 3274-3285. Google Scholar

[16]

T. MinetaS. RabkinT. YazakiW. Hunter and R. Martuza, Attenuated multi-mutated herpes simplex virus-1 for the treatment of malignant gliomas, Nat. Med., 1 (1995), 938-943. doi: 10.1038/nm0995-938. Google Scholar

[17]

J.C. OliverL.A. BlandC.W. OettingerM.J. ArduinoS.K. McAllisterS.M. Aguero and M.S. Favero, Cytokine kinetics in an in vitro whole blood model following an endotoxin challenge, Lymphokine Cytokine Res., 12 (1993), 115-120. Google Scholar

[18]

R. RodriguezE.R. SchuurH.Y. LimG.A. HendersonJ.W. Simons and D.R. Henderson, Prostate attenuated replication competent daenovirus (ARCA) CN706: A selective cytotoxic for prostate-specific anti-positive prostate cancer cells, Cancer Res., 57 (2000), 2559-2563. Google Scholar

[19]

H. Schättler and U. Ledzewicz, Optimal Control for Mathematical Models of Cancer Therapies Springer Publishing Co., New York, USA, 2015. doi: 10.1007/978-1-4939-2972-6. Google Scholar

[20]

G. WollmannK. Ozduman and A. N. van den Pol, Oncolytic virus therapy for glioblastoma multiforme: Concepts and candidates, Cancer J., 18 (2012), 69-81. doi: 10.1097/PPO.0b013e31824671c9. Google Scholar

[21]

J.T. WuH.M. ByrneD.H. Kirn and L.M. Wein, Modeling and analysis of a virus that replicates selectively in tumor cells, Bull. Math. Biol., 63 (2001), 731-768. doi: 10.1006/bulm.2001.0245. Google Scholar

[22]

J.T. WuD.H. Kirn and L.M. Wein, Analysis of a three-way race between tumor growth, a replication-competent virus and an immune response, Bull. Math. Biol., 66 (2004), 605-625. doi: 10.1016/j.bulm.2003.08.016. Google Scholar

Figure 1.  Flow chart of the model for virotherapy
Figure 2.  Graphs of model variables for $C=0,\; D=0.$
Figure 3.  Graphs of model variables for $C=5\cdot10^{-7},\; D=0.$
Figure 4.  Graph of $R(50)$ for $b\in[70,110]$ and different values od C
Figure 5.  Graph of $R(50)$ for $b\in [110,150]$ and different values od C
Figure 6.  Graphs of model variables for $C=5\cdot10^{-7},\; D=15.$
Figure 7.  Graph of R(50) for $ b \in [70,90]$ with different D and fixed $C=5\cdot10^{-7}$
Figure 8.  Graph of R(50) for $ b \in [110,130]$ with different D and fixed $C=3\cdot10^{-7}$
Figure 9.  Efficacy map for b = 90
Figure 10.  Efficacy map for b = 150
Table 1.  Parameters of the model
ParameterDescriptionNum. valuesDimension
$\alpha$Proliferation rate of uninfected tumor cells$0.2$1/day
$\beta$Infection rate of tumor cells by viruses$2\cdot10^{4}$$\frac{cm^{3}}{g\cdot day}$
$\rho$Rate of loss of viruses during infection$4\cdot10^{-2}$$\frac{cm^{3}}{g\cdot day}$
$k$Effectiveness of the inhibitory action of TNF-$\alpha$$0.4$1/day
$\delta_{y}$Infected tumor cell death rate$0.2$1/day
$\lambda$TNF-$\alpha$ production rate$2.86\cdot10^{-3}$1/day
$\delta_{T}$TNF -$\alpha$ cell degradation rate$55.45$1/day
$\delta_{M}$Macrophages death rate$0.015$1/day
$b$Burst size of infected cells during apoptosis$(50-150) \cdot10^{-6}$
$b_{1}$Burst size of infected cells during necrosis$0,\,\ll b$
$K$Carrying capacity of the TNF-$\alpha$$5\cdot10^{-7}$$\frac{g}{cm^{3}}$
$\kappa$Degradation of TNF-$\alpha$$4\cdot10^{-10}$1/day
due to its action on infected cells
$\delta_{v}$Virus lysis rate$0.5$1/day
$A$Constant source of macrophages$9\cdot10^{-7}$$\frac{g}{cm^{3}\cdot day}$
$s$Stimulation rate of macrophages by infected cells$0.15$$\frac{cm^{3}}{g\cdot day}$
without stimulus
$\delta_{x}$death rate of uninfected cancer cells$0.1$1/day
$\mu$removal rate of dead cells$0.25$1/day
$\theta_{0}$average of total densitiy of cells$0.9$$g/cm^{3}$
$C$constant infusion of the virus$(0-5) \cdot10^{-7}$$\frac{g}{cm^{3}\cdot day}$
$D$constant infusion of the TNF-$\alpha$ inhibitor$0-30$
ParameterDescriptionNum. valuesDimension
$\alpha$Proliferation rate of uninfected tumor cells$0.2$1/day
$\beta$Infection rate of tumor cells by viruses$2\cdot10^{4}$$\frac{cm^{3}}{g\cdot day}$
$\rho$Rate of loss of viruses during infection$4\cdot10^{-2}$$\frac{cm^{3}}{g\cdot day}$
$k$Effectiveness of the inhibitory action of TNF-$\alpha$$0.4$1/day
$\delta_{y}$Infected tumor cell death rate$0.2$1/day
$\lambda$TNF-$\alpha$ production rate$2.86\cdot10^{-3}$1/day
$\delta_{T}$TNF -$\alpha$ cell degradation rate$55.45$1/day
$\delta_{M}$Macrophages death rate$0.015$1/day
$b$Burst size of infected cells during apoptosis$(50-150) \cdot10^{-6}$
$b_{1}$Burst size of infected cells during necrosis$0,\,\ll b$
$K$Carrying capacity of the TNF-$\alpha$$5\cdot10^{-7}$$\frac{g}{cm^{3}}$
$\kappa$Degradation of TNF-$\alpha$$4\cdot10^{-10}$1/day
due to its action on infected cells
$\delta_{v}$Virus lysis rate$0.5$1/day
$A$Constant source of macrophages$9\cdot10^{-7}$$\frac{g}{cm^{3}\cdot day}$
$s$Stimulation rate of macrophages by infected cells$0.15$$\frac{cm^{3}}{g\cdot day}$
without stimulus
$\delta_{x}$death rate of uninfected cancer cells$0.1$1/day
$\mu$removal rate of dead cells$0.25$1/day
$\theta_{0}$average of total densitiy of cells$0.9$$g/cm^{3}$
$C$constant infusion of the virus$(0-5) \cdot10^{-7}$$\frac{g}{cm^{3}\cdot day}$
$D$constant infusion of the TNF-$\alpha$ inhibitor$0-30$
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