Reference : Phosphoprotein patterns predict trametinib responsiveness and optimal trametinib sens...
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
Systems Biomedicine
http://hdl.handle.net/10993/36978
Phosphoprotein patterns predict trametinib responsiveness and optimal trametinib sensitisation strategies in melanoma.
English
Rozanc, Jan [> >]
Sakellaropoulos, Theodore [> >]
Antoranz, Asier [> >]
Gutta, Cristiano [> >]
Podder, Biswajit [> >]
Vetma, Vesna [> >]
Rufo, Nicole [> >]
Agostinis, Patrizia [> >]
Pliaka, Vaia [> >]
Sauter, Thomas mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit]
Kulms, Dagmar [> >]
Rehm, Markus [> >]
Alexopoulos, Leonidas G. [> >]
15-Oct-2018
Cell death and differentiation
Yes (verified by ORBilu)
International
1350-9047
1476-5403
England
[en] Malignant melanoma is a highly aggressive form of skin cancer responsible for the majority of skin cancer-related deaths. Recent insight into the heterogeneous nature of melanoma suggests more personalised treatments may be necessary to overcome drug resistance and improve patient care. To this end, reliable molecular signatures that can accurately predict treatment responsiveness need to be identified. In this study, we applied multiplex phosphoproteomic profiling across a panel of 24 melanoma cell lines with different disease-relevant mutations, to predict responsiveness to MEK inhibitor trametinib. Supported by multivariate statistical analysis and multidimensional pattern recognition algorithms, the responsiveness of individual cell lines to trametinib could be predicted with high accuracy (83% correct predictions), independent of mutation status. We also successfully employed this approach to case specifically predict whether individual melanoma cell lines could be sensitised to trametinib. Our predictions identified that combining MEK inhibition with selective targeting of c-JUN and/or FAK, using siRNA-based depletion or pharmacological inhibitors, sensitised resistant cell lines and significantly enhanced treatment efficacy. Our study indicates that multiplex proteomic analyses coupled with pattern recognition approaches could assist in personalising trametinib-based treatment decisions in the future.
Researchers
http://hdl.handle.net/10993/36978
10.1038/s41418-018-0210-8
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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