Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical-In silico Approach Combining In vitro Experiments and Machine Learning - Zechendorf, Elisabeth; Vaßen, Phillip; Zhang, Jieyi; Hallawa, Ahmed; Martincuks, Antons; Krenkel, Oliver; Müller-Newen, Gerhard; Schuerholz, Tobias; Simon, Tim-Philipp; Marx, Gernot; Ascheid, Gerd; Schmeink, Anke; et al. (Frontiers in Immunology, 2018)
Abstract Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signalling pathways involved in apoptosis and necroptosis are linked to trauma or sepsis associated cardiomyopathy. The underling causative factors, however, are still debatable. Heparan sulfate fragments belong to the class of danger/damage-associated molecular patterns (DAMP) liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that heparan sulfate induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical-In-Silico approach which 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 & replacement). Cardiomyocytes exposed to heparan sulfate 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 heparan sulfate resulted in the induction of necroptosis by tumour 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 suggests i) that heparan sulfate induces necroptosis in cardiomyocytes by phosphorylation (activation) of RIP3, ii) that heparan sulfate is a therapeutic target in trauma or sepsis associated cardiomyopathy and iii) indicate that this proof-of-concept is a first step towards simulating the extent of activated components in the pro-apoptotic pathway induced by heparan sulfate with only a small data-set gained from the in vitro experiments by using machine learning algorithms.