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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.
Afiliação
  • Zila N; 1Department of Dermatology, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria.
  • Bileck A; 2Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria.
  • Muqaku B; 3University of Applied Sciences (FH Campus Wien), Vienna, Austria.
  • Janker L; 2Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria.
  • Eichhoff OM; 2Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria.
  • Cheng PF; 2Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria.
  • Dummer R; Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland.
  • Levesque MP; Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland.
  • Gerner C; Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland.
  • Paulitschke V; Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland.
Clin Proteomics ; 15: 13, 2018.
Article em En | MEDLINE | ID: mdl-29541007
ABSTRACT

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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Clin Proteomics Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Áustria

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Clin Proteomics Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Áustria