Master of advanced studies

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

ContributorsKogel, Ulrike
DirectorsSorg, Olivier
Defense date2021-08-20

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
Citation (ISO format)
KOGEL, Ulrike. Causal biological network model for the assessment of skin signalling by using transcriptomic data. 2021.
Main files (1)
Master thesis
  • PID : unige:157297

Technical informations

Creation11/26/2021 3:55:00 PM
First validation11/26/2021 3:55:00 PM
Update time03/16/2023 2:08:14 AM
Status update03/16/2023 2:08:14 AM
Last indexation08/31/2023 7:12:53 AM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack