1
|
Fu D, Weng X, Su Y, Hong B, Zhao A, Lin J. Establishing a model composed of immune-related gene-modules to predict tumor immunotherapy response. Sci Rep 2024; 14:16630. [PMID: 39025898 PMCID: PMC11258235 DOI: 10.1038/s41598-024-67742-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 07/15/2024] [Indexed: 07/20/2024] Open
Abstract
At present, tumor immunotherapy has been widely applied to treat various cancers. However, the accuracy of predicting treatment efficacy has not yet achieved a significant breakthrough. This study aimed to construct a prediction model based on the modified WGCNA algorithm to precisely judge the anti-tumor immune response. First, we used a murine colon cancer model to screen corresponding DEGs according to different groups. GSEA was used to analyze the potential mechanisms of the immune-related DEGs (irDEGs) in each group. Subsequently, the intersection of the irDEGs in every group was acquired, and 7 gene-modules were mapped. Finally, 4 gene-modules including cogenes, antiPD-1 immu-genes, chemo immu-genes and comb immu-genes, were selected for subsequent study. Furthermore, a clinical dataset of gastric cancer patients receiving immunotherapy was enrolled, and the irDEGs were identified. A total of 34 vital irDEGs were obtained from the intersections of the vital irDEGs and the four gene-modules. Next, the vital irDEGs were analyzed by the modified WGCNA algorithm, and the correlation coefficients between the 4 gene-modules and the response status to immunotherapy were calculated. Thus, a prediction model based on correlation coefficients was built, and the corresponding model scores were acquired. The AUC calculated according to the model score was 0.727, which was non-inferior to that of the ESTIMATE score and the TIDE score. Meanwhile, the AUC calculated according to the classification of the model scores was 0.705, which was non-inferior to that of the ESTIMATE classification and the TIDE classification. The prediction accuracy of the model was validated in clinical datasets of other cancers.
Collapse
Affiliation(s)
- Deqiang Fu
- Department of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Xiaoyuan Weng
- Thyroid and Breast Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
- Quanzhou Medical College, Quanzhou, China
| | - Yunxia Su
- Department of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Binhuang Hong
- Department of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Aiyue Zhao
- Department of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
| | - Jianqing Lin
- Thyroid and Breast Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
| |
Collapse
|
2
|
Murad D, Zafar Paracha R, Saeed MT, Ahmad J, Mushtaq A, Humayun M. Modelling and analysis of the complement system signalling pathways: roles of C3, C5a and pro-inflammatory cytokines in SARS-CoV-2 infection. PeerJ 2023; 11:e15794. [PMID: 37744234 PMCID: PMC10517668 DOI: 10.7717/peerj.15794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 07/04/2023] [Indexed: 09/26/2023] Open
Abstract
The complement system is an essential part of innate immunity. It is activated by invading pathogens causing inflammation, opsonization, and lysis via complement anaphylatoxins, complement opsonin's and membrane attack complex (MAC), respectively. However, in SARS-CoV-2 infection overactivation of complement system is causing cytokine storm leading to multiple organs damage. In this study, the René Thomas kinetic logic approach was used for the development of biological regulatory network (BRN) to model SARS-CoV-2 mediated complement system signalling pathways. Betweenness centrality analysis in cytoscape was adopted for the selection of the most biologically plausible states in state graph. Among the model results, in strongly connected components (SCCs) pro-inflammatory cytokines (PICyts) oscillatory behaviour between recurrent generation and downregulation was found as the main feature of SARS-CoV-2 infection. Diversion of trajectories from the SCCs leading toward hyper-inflammatory response was found in agreement with in vivo studies that overactive innate immunity response caused PICyts storm during SARS-CoV-2 infection. The complex of negative regulators FI, CR1 and DAF in the inhibition of complement peptide (C5a) and PICyts was found desirable to increase immune responses. In modelling role of MAC and PICyts in lowering of SARS-CoV-2 titre was found coherent with experimental studies. Intervention in upregulation of C5a and PICyts by C3 was found helpful in back-and-forth variation of signalling pattern linked with the levels of PICyts. Moreover, intervention in upregulation of PICyts by C5a was found productive in downregulation of all activating factors in the normal SCCs. However, the computational model predictions require experimental studies to be validated by exploring the activation role of C3 and C5a which could change levels of PICyts at various phases of SARS-CoV-2 infection.
Collapse
Affiliation(s)
- Didar Murad
- School of Interdisciplinary Engineering and Sciences/Department of Sciences, National University of Science and Technology, Islamabad, Pakistan
| | - Rehan Zafar Paracha
- School of Interdisciplinary Engineering and Sciences/Department of Sciences, National University of Science and Technology, Islamabad, Pakistan
| | - Muhammad Tariq Saeed
- School of Interdisciplinary Engineering and Sciences/Department of Sciences, National University of Science and Technology, Islamabad, Pakistan
| | - Jamil Ahmad
- Department of Computer Science and Information Technology, University of Malakand, Chakdara, Malakand, Pakistan
| | - Ammar Mushtaq
- School of Interdisciplinary Engineering and Sciences/Department of Sciences, National University of Science and Technology, Islamabad, Pakistan
| | - Maleeha Humayun
- School of Interdisciplinary Engineering and Sciences/Department of Sciences, National University of Science and Technology, Islamabad, Pakistan
| |
Collapse
|
3
|
Siddiqa A, Ahmad J, Ali A, Khan S. Deciphering the expression dynamics of ANGPTL8 associated regulatory network in insulin resistance using formal modelling approaches. IET Syst Biol 2020; 14:47-58. [PMID: 32196463 PMCID: PMC8687251 DOI: 10.1049/iet-syb.2019.0032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
ANGPTL8 is a recently identified novel hormone which regulates both glucose and lipid metabolism. The increase in ANGPTL8 during compensatory insulin resistance has been recently reported to improve glucose tolerance and a part of cytoprotective metabolic circuit. However, the exact signalling entities and dynamics involved in this process have remained elusive. Therefore, the current study was conducted with a specific aim to model the regulation of ANGPTL8 with emphasis on its role in improving glucose tolerance during insulin resistance. The main contribution of this study is the construction of a discrete model (based on kinetic logic of René Thomas) and its equivalent Stochastic Petri Net model of ANGPTL8 associated Biological Regulatory Network (BRN) which can predict its dynamic behaviours. The predicted results of these models are in‐line with the previous experimental observations and provide comprehensive insights into the signalling dynamics of ANGPTL8 associated BRN. The authors’ results support the hypothesis that ANGPTL8 plays an important role in supplementing the insulin signalling pathway during insulin resistance and its loss can aggravate the pathogenic process by quickly leading towards Diabetes Mellitus. The results of this study have potential therapeutic implications for treatment of Diabetes Mellitus and are suggestive of its potential as a glucose‐lowering agent.
Collapse
Affiliation(s)
- Amnah Siddiqa
- Research Center for Modelling and Simulation (RCMS), National university of Sciences and Technology (NUST), Sector H-12, Islamabad 46000, Pakistan
| | - Jamil Ahmad
- Department of Computer Science and Information Technology, University of Malakand, Chakdara, Dir Lower, Khyber Pakhtunkhwa 18800, Pakistan.
| | - Amjad Ali
- Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Sector H-12, Islamabad 46000, Pakistan
| | - Sharifullah Khan
- School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Pakistan
| |
Collapse
|
4
|
Sheikh IA, Ahmad J, Magnin M, Roux O. Incorporating Time Delays in Process Hitting Framework for Dynamical Modeling of Large Biological Regulatory Networks. Front Physiol 2019; 10:90. [PMID: 30828302 PMCID: PMC6385622 DOI: 10.3389/fphys.2019.00090] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Accepted: 01/25/2019] [Indexed: 11/29/2022] Open
Abstract
Modeling and simulation of molecular systems helps in understanding the behavioral mechanism of biological regulation. Time delays in production and degradation of expressions are important parameters in biological regulation. Constraints on time delays provide insight into the dynamical behavior of a Biological Regulatory Network (BRN). A recently introduced Process Hitting (PH) Framework has been found efficient in static analysis of large BRNs, however, it lacks the inference of time delays and thus determination of their constraints associated with the evolution of the expression levels of biological entities of BRN is not possible. In this paper we propose a Hybrid Process Hitting scheme for introducing time delays in Process Hitting Framework for dynamical modeling and analysis of Large Biological Regulatory Networks. It provides valuable insights into the time delays corresponding to the changes in the expression levels of biological entities thus possibly helping in identification of therapeutic targets. The proposed framework is applied to a well-known BRNs of Bacteriophage λ and ERBB Receptor-regulated G1/S transition involved in the breast cancer to demonstrate the viability of our approach. Using the proposed approach, we are able to perform goal-oriented reduction of the BRN and also determine the constraints on time delays characterizing the evolution (dynamics) of the reduced BRN.
Collapse
Affiliation(s)
- Iftikhar Ali Sheikh
- Research Centre for Modeling and Simulation, National University of Sciences and Technology, Islamabad, Pakistan
| | - Jamil Ahmad
- Research Centre for Modeling and Simulation, National University of Sciences and Technology, Islamabad, Pakistan.,Department of Computer Science and Information Technology, University of Malakand, Chakdara, Pakistan
| | - Morgan Magnin
- Laboratory of Digital Sciences of Nantes (LS2N), UMR CNRS 6004, Ecole Centrale de Nantes, Nantes, France
| | - Olivier Roux
- Laboratory of Digital Sciences of Nantes (LS2N), UMR CNRS 6004, Ecole Centrale de Nantes, Nantes, France
| |
Collapse
|
5
|
Bibi Z, Ahmad J, Siddiqa A, Paracha RZ, Saeed T, Ali A, Janjua HA, Ullah S, Ben Abdallah E, Roux O. Formal Modeling of mTOR Associated Biological Regulatory Network Reveals Novel Therapeutic Strategy for the Treatment of Cancer. Front Physiol 2017; 8:416. [PMID: 28659828 PMCID: PMC5468443 DOI: 10.3389/fphys.2017.00416] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Accepted: 05/30/2017] [Indexed: 01/25/2023] Open
Abstract
Cellular homeostasis is a continuous phenomenon that if compromised can lead to several disorders including cancer. There is a need to understand the dynamics of cellular proliferation to get deeper insights into the prevalence of cancer. Mechanistic Target of Rapamycin (mTOR) is implicated as the central regulator of the metabolic pathway involved in growth whereas its two distinct complexes mTORC1 and mTORC2 perform particular functions in cellular propagation. To date, mTORC1 is a well defined therapeutic target to inhibit uncontrolled cell division, while the role of mTORC2 is not well characterized. Therefore, the current study is designed to understand the signaling dynamics of mTOR and its partner proteins such as PI3K, PTEN, mTORC2, PKB (Akt), mTORC1, and FOXO. For this purpose, a qualitative model of mTOR-associated Biological Regulatory Network (BRN) is constructed to predict its regulatory behaviors which may not be predictable otherwise. The depleted expression of PTEN and FOXO along with the overexpression of PI3K, mTORC2, mTORC1 and Akt is predicted as a stable steady state which is in accordance with their observed expression levels in the progression of various cancers. The qualitative model also predicts the homeostasis of all the entities in the form of qualitative cycles. The significant qualitative (discrete) cycle is identified by analyzing betweenness centralities of the qualitative (discrete) states. This cycle is further refined as a linear hybrid automaton model with the production (activation) and degradation (inhibition) time delays in order to analyze the real-time constraints for its existence. The analysis of the hybrid model provides a formal proof that during homeostasis the inhibition time delay of Akt is less than the inhibition time delay of mTORC2. In conclusion, our observations characterize that in homeostasis Akt is degraded with a faster rate than mTORC2 which suggests that the inhibition of Akt along with the activation of mTORC2 may be a better therapeutic strategy for the treatment of cancer.
Collapse
Affiliation(s)
- Zurah Bibi
- Research Centre for Modeling and Simulation, National University of Sciences and TechnologyIslamabad, Pakistan
| | - Jamil Ahmad
- Research Centre for Modeling and Simulation, National University of Sciences and TechnologyIslamabad, Pakistan
| | - Amnah Siddiqa
- Research Centre for Modeling and Simulation, National University of Sciences and TechnologyIslamabad, Pakistan
| | - Rehan Z. Paracha
- Research Centre for Modeling and Simulation, National University of Sciences and TechnologyIslamabad, Pakistan
| | - Tariq Saeed
- Research Centre for Modeling and Simulation, National University of Sciences and TechnologyIslamabad, Pakistan
| | - Amjad Ali
- Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and TechnologyIslamabad, Pakistan
| | - Hussnain Ahmed Janjua
- Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and TechnologyIslamabad, Pakistan
| | - Shakir Ullah
- School of Business, Stratford UniversityFalls Church, VA, United States
| | - Emna Ben Abdallah
- IRCCyN UMR Centre National de la Recherche Scientifique 6597, BP 92101Nantes, France
| | - Olivier Roux
- IRCCyN UMR Centre National de la Recherche Scientifique 6597, BP 92101Nantes, France
| |
Collapse
|
6
|
Vergis N, Khamri W, Beale K, Sadiq F, Aletrari MO, Moore C, Atkinson SR, Bernsmeier C, Possamai LA, Petts G, Ryan JM, Abeles RD, James S, Foxton M, Hogan B, Foster GR, O'Brien AJ, Ma Y, Shawcross DL, Wendon JA, Antoniades CG, Thursz MR. Defective monocyte oxidative burst predicts infection in alcoholic hepatitis and is associated with reduced expression of NADPH oxidase. Gut 2017; 66:519-529. [PMID: 26860769 PMCID: PMC5534772 DOI: 10.1136/gutjnl-2015-310378] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Revised: 10/07/2015] [Accepted: 10/25/2015] [Indexed: 12/12/2022]
Abstract
OBJECTIVE In order to explain the increased susceptibility to serious infection in alcoholic hepatitis, we evaluated monocyte phagocytosis, aberrations of associated signalling pathways and their reversibility, and whether phagocytic defects could predict subsequent infection. DESIGN Monocytes were identified from blood samples of 42 patients with severe alcoholic hepatitis using monoclonal antibody to CD14. Phagocytosis and monocyte oxidative burst (MOB) were measured ex vivo using flow cytometry, luminometry and bacterial killing assays. Defects were related to the subsequent development of infection. Intracellular signalling pathways were investigated using western blotting and PCR. Interferon-γ (IFN-γ) was evaluated for its therapeutic potential in reversing phagocytic defects. Paired longitudinal samples were used to evaluate the effect of in vivo prednisolone therapy. RESULTS MOB, production of superoxide and bacterial killing in response to Escherichia coli were markedly impaired in patients with alcoholic hepatitis. Pretreatment MOB predicted development of infection within two weeks with sensitivity and specificity that were superior to available clinical markers. Accordingly, defective MOB was associated with death at 28 and 90 days. Expression of the gp91 phox subunit of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase was reduced in patients with alcoholic hepatitis demonstrating defective MOB. Monocytes were refractory to IFN-γ stimulation and showed high levels of a negative regulator of cytokine signalling, suppressor of cytokine signalling-1. MOB was unaffected by 7 days in vivo prednisolone therapy. CONCLUSIONS Monocyte oxidative burst and bacterial killing is impaired in alcoholic hepatitis while bacterial uptake by phagocytosis is preserved. Defective MOB is associated with reduced expression of NADPH oxidase in these patients and predicts the development of infection and death.
Collapse
Affiliation(s)
- Nikhil Vergis
- Department of Hepatology and Gastroenterology, Imperial College, London, UK
| | - Wafa Khamri
- Department of Hepatology and Gastroenterology, Imperial College, London, UK
| | - Kylie Beale
- Department of Hepatology and Gastroenterology, Imperial College, London, UK
| | - Fouzia Sadiq
- Department of Hepatology and Gastroenterology, Imperial College, London, UK
| | - Mina O Aletrari
- Department of Hepatology and Gastroenterology, Imperial College, London, UK
| | - Celia Moore
- Department of Hepatology and Gastroenterology, Imperial College, London, UK
| | - Stephen R Atkinson
- Department of Hepatology and Gastroenterology, Imperial College, London, UK
| | - Christine Bernsmeier
- Department of Hepatology, King's College Hospital, Institute of Liver Studies, London, UK
| | - Lucia A Possamai
- Department of Hepatology and Gastroenterology, Imperial College, London, UK
| | - Gemma Petts
- Department of Hepatology and Gastroenterology, Imperial College, London, UK
| | - Jennifer M Ryan
- Department of Hepatology, King's College Hospital, Institute of Liver Studies, London, UK
| | - Robin D Abeles
- Department of Hepatology, King's College Hospital, Institute of Liver Studies, London, UK
| | - Sarah James
- Department of Hepatology, University College, London, UK
| | | | - Brian Hogan
- Department of Hepatology, Royal Free Hospital, London, UK
| | - Graham R Foster
- Department of Gastroenterology, Royal London Hospital, London, UK
| | | | - Yun Ma
- Department of Hepatology, King's College Hospital, Institute of Liver Studies, London, UK
| | - Debbie L Shawcross
- Department of Hepatology, King's College Hospital, Institute of Liver Studies, London, UK
| | - Julia A Wendon
- Department of Hepatology, King's College Hospital, Institute of Liver Studies, London, UK
| | | | - Mark R Thursz
- Department of Hepatology and Gastroenterology, Imperial College, London, UK
| |
Collapse
|
7
|
Khalid S, Hanif R, Tareen SH, Siddiqa A, Bibi Z, Ahmad J. Formal modeling and analysis of ER- α associated Biological Regulatory Network in breast cancer. PeerJ 2016; 4:e2542. [PMID: 27781158 PMCID: PMC5075711 DOI: 10.7717/peerj.2542] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2016] [Accepted: 09/07/2016] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Breast cancer (BC) is one of the leading cause of death among females worldwide. The increasing incidence of BC is due to various genetic and environmental changes which lead to the disruption of cellular signaling network(s). It is a complex disease in which several interlinking signaling cascades play a crucial role in establishing a complex regulatory network. The logical modeling approach of René Thomas has been applied to analyze the behavior of estrogen receptor-alpha (ER-α) associated Biological Regulatory Network (BRN) for a small part of complex events that leads to BC metastasis. METHODS A discrete model was constructed using the kinetic logic formalism and its set of logical parameters were obtained using the model checking technique implemented in the SMBioNet software which is consistent with biological observations. The discrete model was further enriched with continuous dynamics by converting it into an equivalent Petri Net (PN) to analyze the logical parameters of the involved entities. RESULTS In-silico based discrete and continuous modeling of ER-α associated signaling network involved in BC provides information about behaviors and gene-gene interaction in detail. The dynamics of discrete model revealed, imperative behaviors represented as cyclic paths and trajectories leading to pathogenic states such as metastasis. Results suggest that the increased expressions of receptors ER-α, IGF-1R and EGFR slow down the activity of tumor suppressor genes (TSGs) such as BRCA1, p53 and Mdm2 which can lead to metastasis. Therefore, IGF-1R and EGFR are considered as important inhibitory targets to control the metastasis in BC. CONCLUSION The in-silico approaches allow us to increase our understanding of the functional properties of living organisms. It opens new avenues of investigations of multiple inhibitory targets (ER-α, IGF-1R and EGFR) for wet lab experiments as well as provided valuable insights in the treatment of cancers such as BC.
Collapse
Affiliation(s)
- Samra Khalid
- Atta-ur-Rahman School of Applied Biosciences (ASAB)/Healthcare Biotechnology, National University of Science and Technology, Islamabad, Pakistan
| | - Rumeza Hanif
- Atta-ur-Rahman School of Applied Biosciences (ASAB)/Healthcare Biotechnology, National University of Science and Technology, Islamabad, Pakistan
| | - Samar H.K. Tareen
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, Netherlands
| | - Amnah Siddiqa
- Research Center for Modeling & Simulation (RCMS), National University of Science and Technology, Islamabad, Pakistan
| | - Zurah Bibi
- Research Center for Modeling & Simulation (RCMS), National University of Science and Technology, Islamabad, Pakistan
| | - Jamil Ahmad
- Research Center for Modeling & Simulation (RCMS), National University of Science and Technology, Islamabad, Pakistan
| |
Collapse
|
8
|
Saeed MT, Ahmad J, Kanwal S, Holowatyj AN, Sheikh IA, Zafar Paracha R, Shafi A, Siddiqa A, Bibi Z, Khan M, Ali A. Formal modeling and analysis of the hexosamine biosynthetic pathway: role of O-linked N-acetylglucosamine transferase in oncogenesis and cancer progression. PeerJ 2016; 4:e2348. [PMID: 27703839 PMCID: PMC5047222 DOI: 10.7717/peerj.2348] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Accepted: 07/19/2016] [Indexed: 12/21/2022] Open
Abstract
The alteration of glucose metabolism, through increased uptake of glucose and glutamine addiction, is essential to cancer cell growth and invasion. Increased flux of glucose through the Hexosamine Biosynthetic Pathway (HBP) drives increased cellular O-GlcNAcylation (hyper-O-GlcNAcylation) and contributes to cancer progression by regulating key oncogenes. However, the association between hyper-O-GlcNAcylation and activation of these oncogenes remains poorly characterized. Here, we implement a qualitative modeling framework to analyze the role of the Biological Regulatory Network in HBP activation and its potential effects on key oncogenes. Experimental observations are encoded in a temporal language format and model checking is applied to infer the model parameters and qualitative model construction. Using this model, we discover step-wise genetic alterations that promote cancer development and invasion due to an increase in glycolytic flux, and reveal critical trajectories involved in cancer progression. We compute delay constraints to reveal important associations between the production and degradation rates of proteins. O-linked N-acetylglucosamine transferase (OGT), an enzyme used for addition of O-GlcNAc during O-GlcNAcylation, is identified as a key regulator to promote oncogenesis in a feedback mechanism through the stabilization of c-Myc. Silencing of the OGT and c-Myc loop decreases glycolytic flux and leads to programmed cell death. Results of network analyses also identify a significant cycle that highlights the role of p53-Mdm2 circuit oscillations in cancer recovery and homeostasis. Together, our findings suggest that the OGT and c-Myc feedback loop is critical in tumor progression, and targeting these mediators may provide a mechanism-based therapeutic approach to regulate hyper-O-GlcNAcylation in human cancer.
Collapse
Affiliation(s)
- Muhammad Tariq Saeed
- Research Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST) , Islamabad , Pakistan
| | - Jamil Ahmad
- Research Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST), Islamabad, Pakistan; School of Computer Science and IT, Stratford University, VA, United States
| | - Shahzina Kanwal
- Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences , Guangzhou , China
| | - Andreana N Holowatyj
- Department of Oncology, Wayne State University School of Medicine and Barbara Ann Karmanos Cancer Institute , Detroit , MI , United States
| | - Iftikhar A Sheikh
- Research Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST) , Islamabad , Pakistan
| | - Rehan Zafar Paracha
- Research Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST) , Islamabad , Pakistan
| | - Aamir Shafi
- School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad, Pakistan; College of Computer Science and Information Technology, University of Dammam, Al Khobar, Kingdom of Saudi Arabia
| | - Amnah Siddiqa
- Research Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST) , Islamabad , Pakistan
| | - Zurah Bibi
- Research Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST) , Islamabad , Pakistan
| | - Mukaram Khan
- Research Centre for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST) , Islamabad , Pakistan
| | - Amjad Ali
- Atta-ur-Rehman School of Applied Bio-science (ASAB), National University of Sciences and Technology (NUST) , Islamabad , Pakistan
| |
Collapse
|
9
|
Bibi Z, Ahmad J, Ali A, Siddiqa A, Shahzad S, Tareen SHK, Janjua HA, Khusro S. On the modeling and analysis of the biological regulatory network of NF-$${\kappa }$$B activation in HIV-1 infection. ACTA ACUST UNITED AC 2016. [DOI: 10.1186/s40294-015-0013-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Abstract
Purpose
The complex interactions between genetic machinery of HIV-1 and host immune cells mediate dynamic adaptive responses leading to Autoimmune Deficiency Syndrome. These interactions are captured as Biological Regulatory Network (BRN) which acts to maintain the viability of host cell machinery through feedback control mechanism which is a characteristic of complex adaptive systems. In this study, the BRN of immune response against HIV-1 infection is modeled to investigate the role of NF-κB and TNF-α in disease transmission using qualitative (discrete) and hybrid modeling formalisms.
Methods
Qualitative and Hybrid modeling approaches are used to model the BRN for the dynamic analysis. The qualitative model is based on the logical parameters while the hybrid model is based on the time delay parameters.
Results
The qualitative model gives useful insights about the physiological condition observed as the homeostasis of all the entities of the BRN as well as pathophysiological behaviors representing high expression levels of NF-κB, TNF-α and HIV. Since the qualitative model is time abstracted, so a hybrid model is developed to analyze the behavior of the BRN by associating activation and inhibition time delays with each entity. HyTech tool synthesizes time delay constraints for the existence of homeostasis.
Conclusion
Hybrid model reveals various viability constraints that characterize the conditional existence of cyclic states (homeostasis). The resultant relations suggest larger cycle period of HIV-1 than the cycle periods of the other two entities (NF-κB and TNF-α) to maintain a homeostatic expressions of these entities.
Collapse
|