Reference : Systemic network analysis identifies XIAP and IkappaBalpha as potential drug targets ...
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/37283
Systemic network analysis identifies XIAP and IkappaBalpha as potential drug targets in TRAIL resistant BRAF mutated melanoma.
English
Del Mistro, Greta [> >]
Lucarelli, Philippe mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Life Science Research Unit]
Muller, Ines [> >]
De Landtsheer, Sébastien mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit >]
Zinoveva, Anna [> >]
Hutt, Meike [> >]
Siegemund, Martin [> >]
Kontermann, Roland E. [> >]
Beissert, Stefan [> >]
Sauter, Thomas mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit]
Kulms, Dagmar [> >]
Nov-2018
NPJ systems biology and applications
4
39
Yes (verified by ORBilu)
International
2056-7189
England
[en] Metastatic melanoma remains a life-threatening disease because most tumors develop resistance to targeted kinase inhibitors thereby regaining tumorigenic capacity. We show the 2nd generation hexavalent TRAIL receptor-targeted agonist IZI1551 to induce pronounced apoptotic cell death in mutBRAF melanoma cells. Aiming to identify molecular changes that may confer IZI1551 resistance we combined Dynamic Bayesian Network modelling with a sophisticated regularization strategy resulting in sparse and context-sensitive networks and show the performance of this strategy in the detection of cell line-specific deregulations of a signalling network. Comparing IZI1551-sensitive to IZI1551-resistant melanoma cells the model accurately and correctly predicted activation of NFkappaB in concert with upregulation of the anti-apoptotic protein XIAP as the key mediator of IZI1551 resistance. Thus, the incorporation of multiple regularization functions in logical network optimization may provide a promising avenue to assess the effects of drug combinations and to identify responders to selected combination therapies.
Researchers ; Professionals
http://hdl.handle.net/10993/37283
10.1038/s41540-018-0075-y
H2020 ; 642295 - MEL-PLEX - Exploiting MELanoma disease comPLEXity to address European research training needs in translational cancer systems biology and cancer systems medicine
FnR ; FNR7643621 > Thomas Sauter > Melanoma sensitivity > Predicting individual sensitivity of malignant melanoma to combination therapies by statistical and network modeling on innovative 3D organotypic screening models > 01/05/2015 > 30/04/2018 > 2013

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