Formal modeling and analysis of the hexosamine biosynthetic pathway: role of O-linked N-acetylglucosamine transferase in oncogenesis and cancer progression

Saeed, Tahir; Ahmad, Jamil; Kanwal, Shahzina; Holowatyj, Andreana N.; Sheikh, Ijaz; Paracha, Rehan Zafar; Shafi, Aamir; Siddiqa, Amnah; Bibi, Zurah; Khan, Mukaram; Ali, Amjad

doi:10.7717/peerj.2348

Cited by 16 publications

(29 citation statements)

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“…Computational tools such as Ordinary Diﬀerential Equations based models have been applied to study various biological systems. Recently, the role of OGT enzyme in cancer progression has been studied by Saeed et al (2016) through computational modeling in which formal modeling has been applied. An established technique for modeling of the biological systems is the Petri nets (PNs).…”

Section: Introductionmentioning

confidence: 99%

Model-based in silico analysis of the PI3K/Akt pathway: the elucidation of cross-talk between diabetes and breast cancer

Rehman¹,

Obaid²,

Naz³

et al. 2018

PeerJ

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BackgroundA positive association between diabetes and breast cancer has been identified by various epidemiological and clinical studies. However, the possible molecular interactions between the two heterogeneous diseases have not been fully determined yet. There are several underlying mechanisms which may increase the risk of breast cancer in diabetic patients.IntroductionIn this study, we focused on the role of O-GlcNAc transferase (OGT) enzyme in the regulation of phosphatidylinositol-3 kinase (PI3K) pathway through activation/deactivation of Akt protein. The efficiency of insulin signaling in adipocytes is reduced as a result of OGT overexpression which further attenuates Akt signaling; as a result, the efficiency of insulin signaling is reduced by downregulation of insulin-responsive genes. On the other hand, increased expression of OGT results in Akt activation in breast cancer cells, leading to enhanced cell proliferation and inhibition of the apoptosis. However, the interplay amongst these signaling pathways is still under investigation.MethodsIn this study, we used Petri nets (PNs) to model and investigate the role of PI3K and OGT pathways, acting as key players in crosstalk between diabetes and breast cancer, resulting in progression of these chronic diseases. Moreover, in silico perturbation experiments were applied on the model to analyze the effects of anti-cancer agents (shRNA and BZX) and anti-diabetic drug (Metformin) on the system.ResultsOur PN model reflects the alterations in protein expression and behavior and the correlation between breast cancer and diabetes. The analysis proposed two combination therapies to combat breast cancer progression in diabetic patients including combination of OGTmRNA silencing and OGT inhibitor (BZX) as first combination and BZX and Metformin as the second.ConclusionThe PN model verified that alterations in O-GlcNAc signaling affect both insulin resistance and breast cancer. Moreover, the combination therapy for breast cancer patients consisting of anti-diabetic drugs such as Metformin along with OGT inhibitors, for example BZX, can produce better treatment regimens.

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Section: Introductionmentioning

confidence: 99%

Model-based in silico analysis of the PI3K/Akt pathway: the elucidation of cross-talk between diabetes and breast cancer

Rehman¹,

Obaid²,

Naz³

et al. 2018

PeerJ

Self Cite

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“…In order to validate results of our parallel implementation, we undertake case study of Hexosamine Biosynthetic Pathway (HBP) and its involvement in Cancer [1, 48].…”

Section: Resultsmentioning

confidence: 99%

“…A qualitative model of the Hexosamine Biosynthetic pathway (HBP) explaining the association between hyper O-GlcNAcylation and cancer progression was developed by [48]. The qualitative BRN (see Fig.…”

Section: Resultsmentioning

confidence: 99%

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Parameter estimation of qualitative biological regulatory networks on high performance computing hardware

Saeed¹,

Ahmad

Baumbach

et al. 2018

BMC Syst Biol

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BackgroundBiological Regulatory Networks (BRNs) are responsible for developmental and maintenance related functions in organisms. These functions are implemented by the dynamics of BRNs and are sensitive to regulations enforced by specific activators and inhibitors. The logical modeling formalism by René Thomas incorporates this sensitivity with a set of logical parameters modulated by available regulators, varying with time. With the increase in complexity of BRNs in terms of number of entities and their interactions, the task of parameters estimation becomes computationally expensive with existing sequential SMBioNET tool. We extend the existing sequential implementation of SMBioNET by using a data decomposition approach using a Java messaging library called MPJ Express. The approach divides the parameters space into different regions and each region is then explored in parallel on High Performance Computing (HPC) hardware.ResultsThe performance of the parallel approach is evaluated on BRNs of different sizes, and experimental results on multicore and cluster computers showed almost linear speed-up. This parallel code can be executed on a wide range of concurrent hardware including laptops equipped with multicore processors, and specialized distributed memory computer systems. To demonstrate the application of parallel implementation, we selected a case study of Hexosamine Biosynthetic Pathway (HBP) in cancer progression to identify potential therapeutic targets against cancer. A set of logical parameters were computed for HBP model that directs the biological system to a state of recovery. Furthermore, the parameters also suggest a potential therapeutic intervention that restores homeostasis. Additionally, the performance of parallel application was also evaluated on a network (comprising of 23 entities) of Fibroblast Growth Factor Signalling in Drosophila melanogaster.ConclusionsQualitative modeling framework is widely used for investigating dynamics of biological regulatory networks. However, computation of model parameters in qualitative modeling is computationally intensive. In this work, we presented results of our Java based parallel implementation that provides almost linear speed-up on both multicore and cluster platforms. The parallel implementation is available at https://psmbionet.github.io.Electronic supplementary materialThe online version of this article (10.1186/s12918-018-0670-y) contains supplementary material, which is available to authorized users.

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“…discussed below under section "Parameters Interpretation using Model Checking". The detailed semantics of the kinetic logic formalism (Samaga & Klamt 2013) have already been discussed in the studies of Ahmad et al, (2012) and Saeed et al, (2016) (Ahmad et al 2012;Saeed et al 2016). However, some of the important definitions and the terms quite necessary to comprehend the semantics employed in this study have been stated below.…”

Section: Qualitative Framework For Modeling the Hepatitis C Virus (Hcmentioning

confidence: 99%

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Supplemental Information 3: BRN Model GINSIM Tool

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Background. Hepatitis C Virus (HCV) is a major causative agent of liver infection leading to critical liver damage. In response to HCV, the improper regulation of host immune system leads to chronic infection. The host immune system employs multiple cell types, diverse variety of cytokine mediators and interacting signaling networks to neutralize the HCV infection. To understand the complexity of the interactions within the immune signaling networks, systems biology provides an efficient alternative approach. Integrating such approaches with immunology and virology helps to study highly complex immune regulatory networks within the host and presents a concise view of the whole system. Methods. Initially, a logic-based diagram is generated based on multiple reported interactions between immune cells and cytokines during host immune response to HCV. Furthermore, an abstracted subnetwork is modeled qualitatively which consists of both the key cellular and cytokine components of the HCV induced immune system. Rene' Thomas formalism is applied in the study to generate a qualitative model which requires only the qualitative thresholds and associated logical parameters generated via SMBioNet software in accordance with biological observations. Furthermore, the continuous dynamics of the model have been studied via Petri nets based analysis. Results. In the presence of NS5A protein of HCV, the behaviors of the Natural Killer (NK) and T regulatory (Tregs) cells along with cytokines such as IFN-γ, IL-10, IL-12 are predicted. The model also attempts to consider the viral strategies to circumvent immune response mediated by viral proteins. The state graph analysis enabled the prediction of paths leading to disease state. The most probable cycle is predicted based on maximum betweenness centrality. Furthermore, to study the continuous dynamics of the modeled network, a Petri net (PN) model was generated. The predictive ability of the model implicates the critical role of IL-12 over-expression in pathogenesis. This observation speculates that IL-12 has a dual role under varying circumstances and leads to varying disease outcomes. Conclusion. This model attempts to reduce the noisy biological data and captures a holistic view of the regulations amongst the key determinants of HCV induced adaptive immune responses. The observations warrant for further studies to elucidate the role of IL-12 under varying external and internal stimuli. Also, introducing diversion by therapeutic perturbation may divert the system from diseased paths to recovery by stabilizing the activation of IFN-γ producing NK cells. The modeling approach employed in this study can be extended to include real-time experimental data to propose new therapeutic interventions.

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Formal modeling and analysis of the hexosamine biosynthetic pathway: role of O-linked N-acetylglucosamine transferase in oncogenesis and cancer progression

Cited by 16 publications

References 113 publications

Model-based in silico analysis of the PI3K/Akt pathway: the elucidation of cross-talk between diabetes and breast cancer

Model-based in silico analysis of the PI3K/Akt pathway: the elucidation of cross-talk between diabetes and breast cancer

Parameter estimation of qualitative biological regulatory networks on high performance computing hardware

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