Causal biological network model for the assessment of skin signalling by using transcriptomic data

Diplôme Master d'études avancées Causal biological network model for the assessment of skin signalling by using transcriptomic data eng 2021-08-20 author Kogel Ulrike 868251 director Sorg Olivier 32172 The epidermis is the outermost layer of skin and consists mainly of keratinocytes that form a stratified epithelium. Keratinocytes are continuously renewed by proliferation and ongoing differentiation, while migrating upwards to form the terminal differentiated cornified layer, where they finally die and shed off. The epidermis acts as a barrier and represents the first line of defense against environmental challenges, such as UV radiation, mechanical wounding, and chemical agents. The precise mechanisms that maintain or restore the epidermal homeostasis are subject of ongoing research, and in this work the available literature knowledge was assembled into a causal biological network model of keratinocyte signalling. The network of 630 nodes connected with 1213 causal edges allows comprehensive visualization and understanding of the processes that are activated in the skin upon external challenges. The network model was further scored with transcriptomic data to show how the approach can contribute to the mechanistic understanding of the healing process of human epidermis. For this, a public data from different stages of wound healing was selected. The results suggested that ERK1/2 downstream of IL22, IL6, and IFNG was the predominant signalling pathway leading to increased keratinocyte migration and proliferation at the investigated time points. Further, EGFR signalling was identified as prominent regulatory contributor for wound healing promoting processes. This work demonstrates that the keratinocyte network model is a valuable tool for obtaining mechanistic insights from transcriptomic data beyond traditional gene list. It can further support the identification of the key molecular drivers that are perturbed in a disease state or after toxic insult, as well as to investigate the mode of action of novel drug candidates for skin disorders. Network models Biological expression language Keratinocyte Skin signalling Transcriptomics Dewey 610 Dewey 615 31 Section des sciences pharmaceutiques 17 3 Faculté de médecine 2 false 386 La recherche en biochimie dermatologique 652 4eec0069-2299-4215-9910-b4d99edf08d5 Master thesis Restricted Master Thesis Skin Signalling Netwo.pdf 6151898 application/pdf restrictedAccess Faculté des sciences / Section des sciences pharmaceutiques Faculté de médecine

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Causal biological network model for the assessment of skin signalling by using transcriptomic data				2021	102	3

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Kogel, Ulrike