title: A Kinetic-Model-Based Approach to Identify Malfunctioning Components in Signal Transduction Pathways from Artificial Clinical Data.
abstract: Detection of malfunctioning reactions or molecules from clinical data is essential for disease treatments. In order to find an alternative to the existing oversimplistic mathematical models, a kinetic model is developed in this work to infer the malfunctioning reactions/molecules by quantifying the similarity between the clinical profile and the output profiles predicted from the model in which certain reactions/molecules malfunction. The new approach was tested in IL-6 and TNF-α/NF-κB signaling pathway, for four abnormal conditions including up/downregulation of single reaction rate constants and up/downregulation of single molecules. Since limited quantitative clinical data were available, the IL-6 ODE model was used to generate artificial clinical data for the abnormal steady-state value shown in two key molecules: nuclear STAT3 and SOCS3. Similarly, the TNF-α/NF-κB model was used to obtain the data in which abnormal oscillation dynamic was shown in the profile of NF-κB. The results show that the approach developed in this study was able to successfully identify the malfunctioning reactions and molecules from the clinical data. It was also found that this new approach was noise-robust and that it managed to reveal unique solution for the faulty components in a network.
authors.affiliation: Department of Chemical Engineering, Villanova University, Villanova, PA 19085, USA.
authors.forename: Xianhua
authors.initials: X
authors.lastname: Li
authors.affiliation: Department of Chemical Engineering, Villanova University, Villanova, PA 19085, USA.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Ribaudo
authors.affiliation: Department of Chemical Engineering, Villanova University, Villanova, PA 19085, USA ; The Center for Nonlinear Dynamics & Control (CENDAC), Villanova University, Villanova, PA 19085, USA ; Villanova Center for the Advancement of Sustainability in Engineering (VCASE), Villanova University, Villanova, PA 19085, USA.
authors.forename: Zuyi Jacky
authors.initials: ZJ
authors.lastname: Huang
mesh_terms: D006801:Humans; D015850:Interleukin-6 / Q000378:metabolism; D007700:Kinetics; D008962:Models, Theoretical; D016328:NF-kappa B / Q000378:metabolism*; D050796:STAT3 Transcription Factor / Q000378:metabolism; D015398:Signal Transduction; D000071223:Suppressor of Cytokine Signaling 3 Protein; D050826:Suppressor of Cytokine Signaling Proteins / Q000378:metabolism; D014409:Tumor Necrosis Factor-alpha / Q000378:metabolism*
chemical_list: D015850:Interleukin-6; D016328:NF-kappa B; C106644:SOCS3 protein, human; D050796:STAT3 Transcription Factor; D000071223:Suppressor of Cytokine Signaling 3 Protein; D050826:Suppressor of Cytokine Signaling Proteins; D014409:Tumor Necrosis Factor-alpha