Logical and experimental modeling of cytokine and eicosanoid signaling in psoriatic keratinocytes

Abstract

Summary Psoriasis is a chronic skin disease, in which immune cells and keratinocytes keep each other in a state of inflammation. It is believed that phospholipase A 2 (PLA 2 )-dependent eicosanoid release plays a key role in this. T-helper (Th) 1-derived cytokines are established activators of phospholipases in keratinocytes, whereas Th17-derived cytokines have largely unknown effects. Logical model simulations describing the function of cytokine and eicosanoid signaling networks combined with experimental data suggest that Th17 cytokines stimulate proinflammatory cytokine expression in psoriatic keratinocytes via activation of cPLA 2 α-Prostaglandin E 2 -EP4 signaling, which could be suppressed using the anti-psoriatic calcipotriol. cPLA 2 α inhibition and calcipotriol distinctly regulate expression of key psoriatic genes, possibly offering therapeutic advantage when applied together. Model simulations additionally suggest EP4 and protein kinase cAMP-activated catalytic subunit alpha as drug targets that may restore a normal phenotype. Our work illustrates how the study of complex diseases can benefit from an integrated systems approach.

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

“…Lastly, integrating both pathway and cell models in a multicellular-multiscale model helped reveal the impact of mutations of FADD and p38 on the cellular death of epithelial cells upon infection and the recruitment of immune cells. Whereas these results demonstrate the value of COVID-19 disease logical models for generating new hypotheses and understanding of disease mechanisms, they also provide an important tool set for preclinical discovery and testing of targeted drugs and drug combinations, as demonstrated in several studies (7,(66)(67)(68). Insilico model simulations can prescreen many drug combinations, with the best-performing candidates advancing to further preclinical testing.…”

Modeling signaling pathways in biology with MaBoSS: From one single cell to a dynamic population of heterogeneous interacting cells

“…Autoimmune disorders have also been characterized to better understand the signaling pathways that could be responsible for the diseases. Among them, models of Rheumatoid arthritis (RA) [77] , [78] or of psoriasis [79] have provided insights into the mechanisms at stake.…”

A dynamic Boolean model of molecular and cellular interactions represents psoriasis development and predicts drug candidates

“…Several studies show that PGE2 shifts adaptive immunity toward Th1 and Th17 responses by affecting DCs [45], priming the expansion of Th17 cells, and promoting the differentiation of Th1 cells [46]. The effect of PGE2 on cell fate decisions of KC has been previously described by our work on the computational and experimental modeling of KC behavior upon cytokine and PGE2 stimulation [33]. Inhibitors against cPLA2a, the phospholipase regulating PGE2 expression, have shown high efficacy against plaque psoriasis in clinical trials [47], and while several well-established psoriasis drugs are reducing EP and, subsequently, PGE2 levels, the direct inhibition of EP receptors has not been fully explored in psoriasis, but it is being investigated in other diseases, such as treatment of solid tumors [48].…”