Header

UZH-Logo

Maintenance Infos

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 (2018). Proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases. Clinical Proteomics, 15:13.

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.

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.

Statistics

Citations

Altmetrics

Downloads

0 downloads since deposited on 26 Mar 2018
0 downloads since 12 months

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Dermatology Clinic
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2018
Deposited On:26 Mar 2018 20:10
Last Modified:13 Apr 2018 11:47
Publisher:BioMed Central
ISSN:1542-6416
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1186/s12014-018-9189-x
PubMed ID:29541007

Download

Download PDF  'Proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases'.
Preview
Content: Published Version
Filetype: PDF
Size: 3MB
View at publisher
Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)