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A dynamical systems model for combinatorial cancer therapy enhances oncolytic adenovirus efficacy by MEK-inhibition.

Bagheri N, Shiina M, Lauffenburger DA, Korn WM - PLoS Comput. Biol. (2011)

Bottom Line: Specifically, we fit a nonlinear differential equation system to dedicated experimental data and analyzed the resulting simulations for favorable treatment strategies.Simulations predicted enhanced combinatorial therapy when both treatments were applied simultaneously; we successfully validated these predictions in an ensuing explicit test study.We conclude that integrated computational and experimental analysis of combinatorial therapy provides a useful means to identify treatment/infection protocols that yield clinically significant oncolysis.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.

ABSTRACT
Oncolytic adenoviruses, such as ONYX-015, have been tested in clinical trials for currently untreatable tumors, but have yet to demonstrate adequate therapeutic efficacy. The extent to which viruses infect targeted cells determines the efficacy of this approach but many tumors down-regulate the Coxsackievirus and Adenovirus Receptor (CAR), rendering them less susceptible to infection. Disrupting MAPK pathway signaling by pharmacological inhibition of MEK up-regulates CAR expression, offering possible enhanced adenovirus infection. MEK inhibition, however, interferes with adenovirus replication due to resulting G1-phase cell cycle arrest. Therefore, enhanced efficacy will depend on treatment protocols that productively balance these competing effects. Predictive understanding of how to attain and enhance therapeutic efficacy of combinatorial treatment is difficult since the effects of MEK inhibitors, in conjunction with adenovirus/cell interactions, are complex nonlinear dynamic processes. We investigated combinatorial treatment strategies using a mathematical model that predicts the impact of MEK inhibition on tumor cell proliferation, ONYX-015 infection, and oncolysis. Specifically, we fit a nonlinear differential equation system to dedicated experimental data and analyzed the resulting simulations for favorable treatment strategies. Simulations predicted enhanced combinatorial therapy when both treatments were applied simultaneously; we successfully validated these predictions in an ensuing explicit test study. Further analysis revealed that a CAR-independent mechanism may be responsible for amplified virus production and cell death. We conclude that integrated computational and experimental analysis of combinatorial therapy provides a useful means to identify treatment/infection protocols that yield clinically significant oncolysis. Enhanced oncolytic therapy has the potential to dramatically improve non-surgical cancer treatment, especially in locally advanced or metastatic cases where treatment options remain limited.

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Experimental observations motivate a nonlinear ordinary differential equation model for cancer therapy.System states (shown in black bold capital font) represent the nonlinear dynamic behavior of (i) uninfected cancer cell density, C [cells/cm2], (ii) MEK-inhibition induced G1 arrest cell density, CG1 [cells/cm2], (iii) untreated and infected cell density, IC [cells/cm2], and (iv) treated and infected cell density, ICT [cells/cm2]. Parameter values (shown in red italic script) govern treatment/infection dependent state transitions (solid black arrows) that direct proliferation (σ), G1 cell cycle arrest/release, infection (βn), and lysis (δn), where n denotes whether these cells infect/lyse from a treated (n = T or n = T·G1) or untreated (n = ‘blank’) state. Corresponding delay terms are shown in gray font. MEK-inhibition is described as a reversible process since cells undergo G1 arrest via CI1040 treatment and release upon removal of MEK-inhibitor by media change, returning to the proliferating state (dashed block arrow). Infection is an irreversible process that ultimately results in cell death (solid block arrow).
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pcbi-1001085-g002: Experimental observations motivate a nonlinear ordinary differential equation model for cancer therapy.System states (shown in black bold capital font) represent the nonlinear dynamic behavior of (i) uninfected cancer cell density, C [cells/cm2], (ii) MEK-inhibition induced G1 arrest cell density, CG1 [cells/cm2], (iii) untreated and infected cell density, IC [cells/cm2], and (iv) treated and infected cell density, ICT [cells/cm2]. Parameter values (shown in red italic script) govern treatment/infection dependent state transitions (solid black arrows) that direct proliferation (σ), G1 cell cycle arrest/release, infection (βn), and lysis (δn), where n denotes whether these cells infect/lyse from a treated (n = T or n = T·G1) or untreated (n = ‘blank’) state. Corresponding delay terms are shown in gray font. MEK-inhibition is described as a reversible process since cells undergo G1 arrest via CI1040 treatment and release upon removal of MEK-inhibitor by media change, returning to the proliferating state (dashed block arrow). Infection is an irreversible process that ultimately results in cell death (solid block arrow).

Mentions: System states are depicted in black bold capital font (Figure 2) and reflect the nonlinear dynamic behavior of (i) uninfected cancer cell density, C [cells/cm2], (ii) MEK-inhibition induced G1-phase arrest cell density, CG1 [cells/cm2], (iii) untreated and infected cell density, IC [cells/cm2], and (iv) MEK-inhibitor treated and infected cell density, ICT [cells/cm2], where P reflects the total cancer cell population [cells/cm2].


A dynamical systems model for combinatorial cancer therapy enhances oncolytic adenovirus efficacy by MEK-inhibition.

Bagheri N, Shiina M, Lauffenburger DA, Korn WM - PLoS Comput. Biol. (2011)

Experimental observations motivate a nonlinear ordinary differential equation model for cancer therapy.System states (shown in black bold capital font) represent the nonlinear dynamic behavior of (i) uninfected cancer cell density, C [cells/cm2], (ii) MEK-inhibition induced G1 arrest cell density, CG1 [cells/cm2], (iii) untreated and infected cell density, IC [cells/cm2], and (iv) treated and infected cell density, ICT [cells/cm2]. Parameter values (shown in red italic script) govern treatment/infection dependent state transitions (solid black arrows) that direct proliferation (σ), G1 cell cycle arrest/release, infection (βn), and lysis (δn), where n denotes whether these cells infect/lyse from a treated (n = T or n = T·G1) or untreated (n = ‘blank’) state. Corresponding delay terms are shown in gray font. MEK-inhibition is described as a reversible process since cells undergo G1 arrest via CI1040 treatment and release upon removal of MEK-inhibitor by media change, returning to the proliferating state (dashed block arrow). Infection is an irreversible process that ultimately results in cell death (solid block arrow).
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Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC3040662&req=5

pcbi-1001085-g002: Experimental observations motivate a nonlinear ordinary differential equation model for cancer therapy.System states (shown in black bold capital font) represent the nonlinear dynamic behavior of (i) uninfected cancer cell density, C [cells/cm2], (ii) MEK-inhibition induced G1 arrest cell density, CG1 [cells/cm2], (iii) untreated and infected cell density, IC [cells/cm2], and (iv) treated and infected cell density, ICT [cells/cm2]. Parameter values (shown in red italic script) govern treatment/infection dependent state transitions (solid black arrows) that direct proliferation (σ), G1 cell cycle arrest/release, infection (βn), and lysis (δn), where n denotes whether these cells infect/lyse from a treated (n = T or n = T·G1) or untreated (n = ‘blank’) state. Corresponding delay terms are shown in gray font. MEK-inhibition is described as a reversible process since cells undergo G1 arrest via CI1040 treatment and release upon removal of MEK-inhibitor by media change, returning to the proliferating state (dashed block arrow). Infection is an irreversible process that ultimately results in cell death (solid block arrow).
Mentions: System states are depicted in black bold capital font (Figure 2) and reflect the nonlinear dynamic behavior of (i) uninfected cancer cell density, C [cells/cm2], (ii) MEK-inhibition induced G1-phase arrest cell density, CG1 [cells/cm2], (iii) untreated and infected cell density, IC [cells/cm2], and (iv) MEK-inhibitor treated and infected cell density, ICT [cells/cm2], where P reflects the total cancer cell population [cells/cm2].

Bottom Line: Specifically, we fit a nonlinear differential equation system to dedicated experimental data and analyzed the resulting simulations for favorable treatment strategies.Simulations predicted enhanced combinatorial therapy when both treatments were applied simultaneously; we successfully validated these predictions in an ensuing explicit test study.We conclude that integrated computational and experimental analysis of combinatorial therapy provides a useful means to identify treatment/infection protocols that yield clinically significant oncolysis.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.

ABSTRACT
Oncolytic adenoviruses, such as ONYX-015, have been tested in clinical trials for currently untreatable tumors, but have yet to demonstrate adequate therapeutic efficacy. The extent to which viruses infect targeted cells determines the efficacy of this approach but many tumors down-regulate the Coxsackievirus and Adenovirus Receptor (CAR), rendering them less susceptible to infection. Disrupting MAPK pathway signaling by pharmacological inhibition of MEK up-regulates CAR expression, offering possible enhanced adenovirus infection. MEK inhibition, however, interferes with adenovirus replication due to resulting G1-phase cell cycle arrest. Therefore, enhanced efficacy will depend on treatment protocols that productively balance these competing effects. Predictive understanding of how to attain and enhance therapeutic efficacy of combinatorial treatment is difficult since the effects of MEK inhibitors, in conjunction with adenovirus/cell interactions, are complex nonlinear dynamic processes. We investigated combinatorial treatment strategies using a mathematical model that predicts the impact of MEK inhibition on tumor cell proliferation, ONYX-015 infection, and oncolysis. Specifically, we fit a nonlinear differential equation system to dedicated experimental data and analyzed the resulting simulations for favorable treatment strategies. Simulations predicted enhanced combinatorial therapy when both treatments were applied simultaneously; we successfully validated these predictions in an ensuing explicit test study. Further analysis revealed that a CAR-independent mechanism may be responsible for amplified virus production and cell death. We conclude that integrated computational and experimental analysis of combinatorial therapy provides a useful means to identify treatment/infection protocols that yield clinically significant oncolysis. Enhanced oncolytic therapy has the potential to dramatically improve non-surgical cancer treatment, especially in locally advanced or metastatic cases where treatment options remain limited.

Show MeSH
Related in: MedlinePlus