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A test of highly optimized tolerance reveals fragile cell-cycle mechanisms are molecular targets in clinical cancer trials.

Nayak S, Salim S, Luan D, Zai M, Varner JD - PLoS ONE (2008)

Bottom Line: Three cell-cycle models were analyzed using monte-carlo sensitivity analysis.Our analysis predicted that CDC25 and cyclin E mechanisms were strongly implicated in G1/S malfunctions, while fragility in the G2/M checkpoint was predicted to be associated with the regulation of the cyclin B-CDK1 complex.Analysis of a third model containing both G1/S and G2/M checkpoint logic, predicted in addition to mechanisms already mentioned, that translation and programmed proteolysis were also key fragile subsystems.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York, United States of America.

ABSTRACT
Robustness, a long-recognized property of living systems, allows function in the face of uncertainty while fragility, i.e., extreme sensitivity, can potentially lead to catastrophic failure following seemingly innocuous perturbations. Carlson and Doyle hypothesized that highly-evolved networks, e.g., those involved in cell-cycle regulation, can be resistant to some perturbations while highly sensitive to others. The "robust yet fragile" duality of networks has been termed Highly Optimized Tolerance (HOT) and has been the basis of new lines of inquiry in computational and experimental biology. In this study, we tested the working hypothesis that cell-cycle control architectures obey the HOT paradigm. Three cell-cycle models were analyzed using monte-carlo sensitivity analysis. Overall state sensitivity coefficients, which quantify the robustness or fragility of a given mechanism, were calculated using a monte-carlo strategy with three different numerical techniques along with multiple parameter perturbation strategies to control for possible numerical and sampling artifacts. Approximately 65% of the mechanisms in the G1/S restriction point were responsible for 95% of the sensitivity, conversely, the G2-DNA damage checkpoint showed a much stronger dependence on a few mechanisms; approximately 32% or 13 of 40 mechanisms accounted for 95% of the sensitivity. Our analysis predicted that CDC25 and cyclin E mechanisms were strongly implicated in G1/S malfunctions, while fragility in the G2/M checkpoint was predicted to be associated with the regulation of the cyclin B-CDK1 complex. Analysis of a third model containing both G1/S and G2/M checkpoint logic, predicted in addition to mechanisms already mentioned, that translation and programmed proteolysis were also key fragile subsystems. Comparison of the predicted fragile mechanisms with literature and current preclinical and clinical trials suggested a strong correlation between efficacy and fragility. Thus, when taken together, these results support the working hypothesis that cell-cycle control architectures are HOT networks and establish the mathematical estimation and subsequent therapeutic exploitation of fragile mechanisms as a novel strategy for anti-cancer lead generation.

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Related in: MedlinePlus

Schematic of the molecular logic of the G1/S (A) and G2/M (B) checkpoint models used in this study.The G1/S model of Qu et al., is composed of 16 dynamic protein balances, 2 species constraints and 44 parameters [31]. TheG2-DNA damage model of Aguda is composed of 15 dynamic protein balances 1constraint and 40 parameters (30). Both the G1/S and G2/M models employ mass action kinetics and the parameters are linear in the mass balances. Nomenclature G1/S: CDC25A - Dual Specificity Phosphatase CDC25A, Cdk2 - Cyclin Dependent Kinase 2, Cdk4/6 - Cyclin Dependent Kinase 4 or 6, CycE - Cyclin E, CycD - Cyclin D, E2F - Transcription Factor E2F, pRB - Retinoblastoma protein, p27 - A Cyclin Dependent Kinase Inhibitor (CKI), also called Kip1. Nomenclature G2/M: pMPF - pre-Maturation Promoting Factor, a complex of CycB (Cyclin B) and Cdk1 (Cyclin Dependent Kinase1) in inactive form, MPF – active form of MPF, aCDC25 - active CDC25 phosphatase, iCDC25 – inactive form of CDC25, aCDC25(P-216) – active CDC25, phosphorylated at Serine 216 residue, iCDC25(P-216) - inactive CDC25, phosphorylated at Serine 216, 14-3-3σ - 14-3-3σ protein. In both the schematics, small red circles with P represent phosphate group, a (+) sign implies positive regulation whereas a (−) sign represents negative regulation.
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pone-0002016-g002: Schematic of the molecular logic of the G1/S (A) and G2/M (B) checkpoint models used in this study.The G1/S model of Qu et al., is composed of 16 dynamic protein balances, 2 species constraints and 44 parameters [31]. TheG2-DNA damage model of Aguda is composed of 15 dynamic protein balances 1constraint and 40 parameters (30). Both the G1/S and G2/M models employ mass action kinetics and the parameters are linear in the mass balances. Nomenclature G1/S: CDC25A - Dual Specificity Phosphatase CDC25A, Cdk2 - Cyclin Dependent Kinase 2, Cdk4/6 - Cyclin Dependent Kinase 4 or 6, CycE - Cyclin E, CycD - Cyclin D, E2F - Transcription Factor E2F, pRB - Retinoblastoma protein, p27 - A Cyclin Dependent Kinase Inhibitor (CKI), also called Kip1. Nomenclature G2/M: pMPF - pre-Maturation Promoting Factor, a complex of CycB (Cyclin B) and Cdk1 (Cyclin Dependent Kinase1) in inactive form, MPF – active form of MPF, aCDC25 - active CDC25 phosphatase, iCDC25 – inactive form of CDC25, aCDC25(P-216) – active CDC25, phosphorylated at Serine 216 residue, iCDC25(P-216) - inactive CDC25, phosphorylated at Serine 216, 14-3-3σ - 14-3-3σ protein. In both the schematics, small red circles with P represent phosphate group, a (+) sign implies positive regulation whereas a (−) sign represents negative regulation.

Mentions: The whole-cycle model of Novak and Tyson (Fig. 1), the G1-S model of Qu et al., (Fig. 2A) and the G2/M-DNA damage model of Aguda (Fig. 2B) were implemented from literature and screened for fragile mechanisms using monte-carlo sensitivity analysis [30]–[32]. The Novak and Tyson model, which employed a complex description of the G1/S and G2/M checkpoints, programmed protein expression and degradation, was composed of 18 dynamic species, 4 species constraints and 74 parameters. The mass-action G1/S and G2/M-DNA damage models described only the molecular logic in their respective checkpoints; the G1/S model was composed of 16 dynamic protein balances, 2 species constraints and 44 parameters while the G2/M-DNA damage model consisted of 15 dynamic protein balances,1 constraint and 40 parameters. Parameter values for each model were taken from literature. Unreported initial conditions were adjusted so that simulated model trajectories were qualitatively consistent with published values (Supplementary Material Figure S1). The published parameter sets, with fixed initial conditions, were used to generate random parameter sets (N = 500, unless otherwise noted) where each nominal parameter was perturbed by up to ±50%, ±1-order, or ±2-orders of magnitude. Overall State Sensitivity Coefficients (OSSCs) were calculated over the random parameter families for each cell-cycle model using three different numerical algorithms. For each model, the mean OSSC values were ranked-ordered and plotted. The Area Under the Curve (AUC) was used to measure the cumulative sensitivity contribution of each parameter. A cumulative cutoff of 95% of the overall sensitivity was used to establish the list of mechanisms (Supplementary Material Figure S2) which were clustered into three groups (high, medium and low sensitivity) using a k-means algorithm.


A test of highly optimized tolerance reveals fragile cell-cycle mechanisms are molecular targets in clinical cancer trials.

Nayak S, Salim S, Luan D, Zai M, Varner JD - PLoS ONE (2008)

Schematic of the molecular logic of the G1/S (A) and G2/M (B) checkpoint models used in this study.The G1/S model of Qu et al., is composed of 16 dynamic protein balances, 2 species constraints and 44 parameters [31]. TheG2-DNA damage model of Aguda is composed of 15 dynamic protein balances 1constraint and 40 parameters (30). Both the G1/S and G2/M models employ mass action kinetics and the parameters are linear in the mass balances. Nomenclature G1/S: CDC25A - Dual Specificity Phosphatase CDC25A, Cdk2 - Cyclin Dependent Kinase 2, Cdk4/6 - Cyclin Dependent Kinase 4 or 6, CycE - Cyclin E, CycD - Cyclin D, E2F - Transcription Factor E2F, pRB - Retinoblastoma protein, p27 - A Cyclin Dependent Kinase Inhibitor (CKI), also called Kip1. Nomenclature G2/M: pMPF - pre-Maturation Promoting Factor, a complex of CycB (Cyclin B) and Cdk1 (Cyclin Dependent Kinase1) in inactive form, MPF – active form of MPF, aCDC25 - active CDC25 phosphatase, iCDC25 – inactive form of CDC25, aCDC25(P-216) – active CDC25, phosphorylated at Serine 216 residue, iCDC25(P-216) - inactive CDC25, phosphorylated at Serine 216, 14-3-3σ - 14-3-3σ protein. In both the schematics, small red circles with P represent phosphate group, a (+) sign implies positive regulation whereas a (−) sign represents negative regulation.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2291571&req=5

pone-0002016-g002: Schematic of the molecular logic of the G1/S (A) and G2/M (B) checkpoint models used in this study.The G1/S model of Qu et al., is composed of 16 dynamic protein balances, 2 species constraints and 44 parameters [31]. TheG2-DNA damage model of Aguda is composed of 15 dynamic protein balances 1constraint and 40 parameters (30). Both the G1/S and G2/M models employ mass action kinetics and the parameters are linear in the mass balances. Nomenclature G1/S: CDC25A - Dual Specificity Phosphatase CDC25A, Cdk2 - Cyclin Dependent Kinase 2, Cdk4/6 - Cyclin Dependent Kinase 4 or 6, CycE - Cyclin E, CycD - Cyclin D, E2F - Transcription Factor E2F, pRB - Retinoblastoma protein, p27 - A Cyclin Dependent Kinase Inhibitor (CKI), also called Kip1. Nomenclature G2/M: pMPF - pre-Maturation Promoting Factor, a complex of CycB (Cyclin B) and Cdk1 (Cyclin Dependent Kinase1) in inactive form, MPF – active form of MPF, aCDC25 - active CDC25 phosphatase, iCDC25 – inactive form of CDC25, aCDC25(P-216) – active CDC25, phosphorylated at Serine 216 residue, iCDC25(P-216) - inactive CDC25, phosphorylated at Serine 216, 14-3-3σ - 14-3-3σ protein. In both the schematics, small red circles with P represent phosphate group, a (+) sign implies positive regulation whereas a (−) sign represents negative regulation.
Mentions: The whole-cycle model of Novak and Tyson (Fig. 1), the G1-S model of Qu et al., (Fig. 2A) and the G2/M-DNA damage model of Aguda (Fig. 2B) were implemented from literature and screened for fragile mechanisms using monte-carlo sensitivity analysis [30]–[32]. The Novak and Tyson model, which employed a complex description of the G1/S and G2/M checkpoints, programmed protein expression and degradation, was composed of 18 dynamic species, 4 species constraints and 74 parameters. The mass-action G1/S and G2/M-DNA damage models described only the molecular logic in their respective checkpoints; the G1/S model was composed of 16 dynamic protein balances, 2 species constraints and 44 parameters while the G2/M-DNA damage model consisted of 15 dynamic protein balances,1 constraint and 40 parameters. Parameter values for each model were taken from literature. Unreported initial conditions were adjusted so that simulated model trajectories were qualitatively consistent with published values (Supplementary Material Figure S1). The published parameter sets, with fixed initial conditions, were used to generate random parameter sets (N = 500, unless otherwise noted) where each nominal parameter was perturbed by up to ±50%, ±1-order, or ±2-orders of magnitude. Overall State Sensitivity Coefficients (OSSCs) were calculated over the random parameter families for each cell-cycle model using three different numerical algorithms. For each model, the mean OSSC values were ranked-ordered and plotted. The Area Under the Curve (AUC) was used to measure the cumulative sensitivity contribution of each parameter. A cumulative cutoff of 95% of the overall sensitivity was used to establish the list of mechanisms (Supplementary Material Figure S2) which were clustered into three groups (high, medium and low sensitivity) using a k-means algorithm.

Bottom Line: Three cell-cycle models were analyzed using monte-carlo sensitivity analysis.Our analysis predicted that CDC25 and cyclin E mechanisms were strongly implicated in G1/S malfunctions, while fragility in the G2/M checkpoint was predicted to be associated with the regulation of the cyclin B-CDK1 complex.Analysis of a third model containing both G1/S and G2/M checkpoint logic, predicted in addition to mechanisms already mentioned, that translation and programmed proteolysis were also key fragile subsystems.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York, United States of America.

ABSTRACT
Robustness, a long-recognized property of living systems, allows function in the face of uncertainty while fragility, i.e., extreme sensitivity, can potentially lead to catastrophic failure following seemingly innocuous perturbations. Carlson and Doyle hypothesized that highly-evolved networks, e.g., those involved in cell-cycle regulation, can be resistant to some perturbations while highly sensitive to others. The "robust yet fragile" duality of networks has been termed Highly Optimized Tolerance (HOT) and has been the basis of new lines of inquiry in computational and experimental biology. In this study, we tested the working hypothesis that cell-cycle control architectures obey the HOT paradigm. Three cell-cycle models were analyzed using monte-carlo sensitivity analysis. Overall state sensitivity coefficients, which quantify the robustness or fragility of a given mechanism, were calculated using a monte-carlo strategy with three different numerical techniques along with multiple parameter perturbation strategies to control for possible numerical and sampling artifacts. Approximately 65% of the mechanisms in the G1/S restriction point were responsible for 95% of the sensitivity, conversely, the G2-DNA damage checkpoint showed a much stronger dependence on a few mechanisms; approximately 32% or 13 of 40 mechanisms accounted for 95% of the sensitivity. Our analysis predicted that CDC25 and cyclin E mechanisms were strongly implicated in G1/S malfunctions, while fragility in the G2/M checkpoint was predicted to be associated with the regulation of the cyclin B-CDK1 complex. Analysis of a third model containing both G1/S and G2/M checkpoint logic, predicted in addition to mechanisms already mentioned, that translation and programmed proteolysis were also key fragile subsystems. Comparison of the predicted fragile mechanisms with literature and current preclinical and clinical trials suggested a strong correlation between efficacy and fragility. Thus, when taken together, these results support the working hypothesis that cell-cycle control architectures are HOT networks and establish the mathematical estimation and subsequent therapeutic exploitation of fragile mechanisms as a novel strategy for anti-cancer lead generation.

Show MeSH
Related in: MedlinePlus