Peer Reviewed

1

Document Type

Article

Publication Date

15-10-2018

Keywords

Cell death, Apoptosis, MEK, Trametinib, Melanoma.

Funder/Sponsor

EU Horizon 2020 MEL-PLEX program (grant agreement#642295). Horizon 2020 SyMBioSys program (grant agreement #675585). European Union and Greek National Funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call Research-Create-Innovate (project code:T1EDK-03532). German Research Foundation (FOR2036; MO 3226/1–1) Health Research Board Ireland (HRA POR 2013 245). Federal Ministry of Education and Research (BMBF: FKZ 031A423A, Melanoma Sensitivity). Luxembourg National Research Fund (FNR: BMBF/BM/7643621, Melanoma Sensitivity).

Comments

The original article is available at www.nature.com

Abstract

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.

Disciplines

Physics | Physiology

Citation

Rožanc J, Sakellaropoulos T, Antoranz A, Guttà C, Podder B, Vetma V, Rufo N, Agostinis P, Pliaka V, Sauter T, Kulms D, Rehm M, Alexopoulos LG. Phosphoprotein patterns predict trametinib responsiveness and optimal trametinib sensitisation strategies in melanoma. Cell Death & Differentiation. 2018;

PubMed ID

30323272

DOI Link

10.1038/s41418-018-0210-8

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

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