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Proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases

BACKGROUND: MAP kinase inhibitor (MAPKi) therapy for BRAF mutated melanoma is characterized by high response rates but development of drug resistance within a median progression-free survival (PFS) of 9–12 months. Understanding mechanisms of resistance and identifying effective therapeutic alternati...

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Autores principales: Zila, Nina, Bileck, Andrea, Muqaku, Besnik, Janker, Lukas, Eichhoff, Ossia M., Cheng, Phil F., Dummer, Reinhard, Levesque, Mitchell P., Gerner, Christopher, Paulitschke, Verena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844114/
https://www.ncbi.nlm.nih.gov/pubmed/29541007
http://dx.doi.org/10.1186/s12014-018-9189-x
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author Zila, Nina
Bileck, Andrea
Muqaku, Besnik
Janker, Lukas
Eichhoff, Ossia M.
Cheng, Phil F.
Dummer, Reinhard
Levesque, Mitchell P.
Gerner, Christopher
Paulitschke, Verena
author_facet Zila, Nina
Bileck, Andrea
Muqaku, Besnik
Janker, Lukas
Eichhoff, Ossia M.
Cheng, Phil F.
Dummer, Reinhard
Levesque, Mitchell P.
Gerner, Christopher
Paulitschke, Verena
author_sort Zila, Nina
collection PubMed
description BACKGROUND: MAP kinase inhibitor (MAPKi) therapy for BRAF mutated melanoma is characterized by high response rates but development of drug resistance within a median progression-free survival (PFS) of 9–12 months. Understanding mechanisms of resistance and identifying effective therapeutic alternatives is one of the most important scientific challenges in melanoma. Using proteomics, we want to specifically gain insight into the pathophysiological process of cerebral metastases. METHODS: Cerebral metastases from melanoma patients were initially analyzed by a LC–MS shotgun approach performed on a QExactive HF hybrid quadrupole-orbitrap mass spectrometer. For further validation steps after bioinformatics analysis, a targeted LC-QQQ-MS approach, as well as Western blot, immunohistochemistry and immunocytochemistry was performed. RESULTS: In this pilot study, we were able to identify 5977 proteins by LC–MS analysis (data are available via ProteomeXchange with identifier PXD007592). Based on PFS, samples were classified into good responders (PFS ≥ 6 months) and poor responders (PFS [Formula: see text]  3 months). By evaluating these proteomic profiles according to gene ontology (GO) terms, KEGG pathways and gene set enrichment analysis (GSEA), we could characterize differences between the two distinct groups. We detected an EMT feature (up-regulation of N-cadherin) as classifier between the two groups, V-type proton ATPases, cell adhesion proteins and several transporter and exchanger proteins to be significantly up-regulated in poor responding patients, whereas good responders showed an immune activation, among other features. We identified class-discriminating proteins based on nearest shrunken centroids, validated and quantified this signature by a targeted approach and could correlate parts of this signature with resistance using the CPL/MUW proteome database and survival of patients by TCGA analysis. We further validated an EMT-like signature as a major discriminator between good and poor responders on primary melanoma cells derived from cerebral metastases. Higher immune activity is demonstrated in patients with good response to MAPKi by immunohistochemical staining of biopsy samples of cerebral melanoma metastases. CONCLUSIONS: Employing proteomic analysis, we confirmed known extra-cerebral resistance mechanisms in the cerebral metastases and further discovered possible brain specific mechanisms of drug efflux, which might serve as treatment targets or as predictive markers for these kinds of metastasis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12014-018-9189-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-58441142018-03-14 Proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases Zila, Nina Bileck, Andrea Muqaku, Besnik Janker, Lukas Eichhoff, Ossia M. Cheng, Phil F. Dummer, Reinhard Levesque, Mitchell P. Gerner, Christopher Paulitschke, Verena Clin Proteomics Research BACKGROUND: MAP kinase inhibitor (MAPKi) therapy for BRAF mutated melanoma is characterized by high response rates but development of drug resistance within a median progression-free survival (PFS) of 9–12 months. Understanding mechanisms of resistance and identifying effective therapeutic alternatives is one of the most important scientific challenges in melanoma. Using proteomics, we want to specifically gain insight into the pathophysiological process of cerebral metastases. METHODS: Cerebral metastases from melanoma patients were initially analyzed by a LC–MS shotgun approach performed on a QExactive HF hybrid quadrupole-orbitrap mass spectrometer. For further validation steps after bioinformatics analysis, a targeted LC-QQQ-MS approach, as well as Western blot, immunohistochemistry and immunocytochemistry was performed. RESULTS: In this pilot study, we were able to identify 5977 proteins by LC–MS analysis (data are available via ProteomeXchange with identifier PXD007592). Based on PFS, samples were classified into good responders (PFS ≥ 6 months) and poor responders (PFS [Formula: see text]  3 months). By evaluating these proteomic profiles according to gene ontology (GO) terms, KEGG pathways and gene set enrichment analysis (GSEA), we could characterize differences between the two distinct groups. We detected an EMT feature (up-regulation of N-cadherin) as classifier between the two groups, V-type proton ATPases, cell adhesion proteins and several transporter and exchanger proteins to be significantly up-regulated in poor responding patients, whereas good responders showed an immune activation, among other features. We identified class-discriminating proteins based on nearest shrunken centroids, validated and quantified this signature by a targeted approach and could correlate parts of this signature with resistance using the CPL/MUW proteome database and survival of patients by TCGA analysis. We further validated an EMT-like signature as a major discriminator between good and poor responders on primary melanoma cells derived from cerebral metastases. Higher immune activity is demonstrated in patients with good response to MAPKi by immunohistochemical staining of biopsy samples of cerebral melanoma metastases. CONCLUSIONS: Employing proteomic analysis, we confirmed known extra-cerebral resistance mechanisms in the cerebral metastases and further discovered possible brain specific mechanisms of drug efflux, which might serve as treatment targets or as predictive markers for these kinds of metastasis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12014-018-9189-x) contains supplementary material, which is available to authorized users. BioMed Central 2018-03-09 /pmc/articles/PMC5844114/ /pubmed/29541007 http://dx.doi.org/10.1186/s12014-018-9189-x Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zila, Nina
Bileck, Andrea
Muqaku, Besnik
Janker, Lukas
Eichhoff, Ossia M.
Cheng, Phil F.
Dummer, Reinhard
Levesque, Mitchell P.
Gerner, Christopher
Paulitschke, Verena
Proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases
title Proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases
title_full Proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases
title_fullStr Proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases
title_full_unstemmed Proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases
title_short Proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases
title_sort proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844114/
https://www.ncbi.nlm.nih.gov/pubmed/29541007
http://dx.doi.org/10.1186/s12014-018-9189-x
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