Heparan sulfate induces necroptosis in murine cardiomyocytes – a Medical-In-Silico approach using machine learning


E. Zechendorf, P. Vaßen, J. Zhang, A. Hallawa, A. Martincuks, O. Krenkel, G. Müller-Newen, T. Schuerholz, T. Simon, G. Marx, G. Ascheid, A. Schmeink, G. Dartmann, C. Thiemermann, L. Martin,


        Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical-In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p < 0.001). Notably, the exposure of HS resulted in the induction of necroptosis by tumor necrosis factor α and receptor interaction protein 3 (p < 0.05; p < 0.01) and, hence, an increased level of necrotic cardiomyocytes. In conclusion, using this novel Medical-In silico approach, our data suggest (i) that HS induces necroptosis in cardiomyocytes by phosphorylation (activation) of receptor-interacting protein 3, (ii) that HS is a therapeutic target in trauma- or sepsis-associated cardiomyopathy, and (iii) indicate that this proof-of-concept is a first step toward simulating the extent of activated components in the pro-apoptotic pathway induced by HS with only a small data set gained from the in vitro experiments by using machine learning algorithms.

BibTEX Reference Entry 

	author = {Elisabeth Zechendorf and Phillip Va{\"s}en and Jieyi Zhang and Ahmed Hallawa and Antons Martincuks and Oliver Krenkel and Gerhard M{\"u}ller-Newen and Tobias Schuerholz and Tim-Philipp Simon and Gernot Marx and Gerd Ascheid and Anke Schmeink and Guido Dartmann and Christoph Thiemermann and Lukas Martin},
	title = "Heparan sulfate induces necroptosis in murine cardiomyocytes – a Medical-In-Silico approach using machine learning",
	pages = "1-12",
	journal = "Frontiers in Immunology-Inflammation",
	volume = "9",
	number = "393",
	doi = 10.3389/fimmu.2018.00393,
	month = Mar,
	year = 2018,
	hsb = RWTH-2018-223661,


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