Dataset Information

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

ABSTRACT: Background MAP kinase inhibitor (MAPKi) therapy for BRAF mutated melanoma is characterized by high response rates but also development of drug resistance within a median progression-free survival (PFS) of 9 to 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 prepared for MS analysis by tryptic digestion. Mass spectrometric analysis was performed on a QExactive HF hybrid quadrupole-orbitrap mass spectrometer, equipped with a nanospray ion source, coupled with a nano HPLC system. Results In this pilot study, we were able to identify 5,977 proteins by LC-MS analysis. Samples were classified into good and poor responders based on PFS. 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 further detected an EMT signature, V-type proton ATPases, calcium ion binding proteins, eukaryotic translation initiation factors, 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 and involvement of extracellular matrix structural constituents, among other features. Subsequently we identified the most class-discriminating proteins based on nearest shrunken centroids. Conclusions Using proteomics helped to identify already known extra-cerebral resistance mechanisms in the cerebral metastases and further discovered possible brain specific mechanisms of drug efflux, which might serve as interesting targets, especially for treatment of these types of metastases or as predictive marker.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Skin

DISEASE(S): Melanoma

SUBMITTER: Christopher Gerner

LAB HEAD: Christopher Gerner

PROVIDER: PXD007592 | Pride | 2018-03-16

REPOSITORIES: Pride

ACCESS DATA

Publications

Octenidine-based hydrogel shows anti-inflammatory and protease-inhibitory capacities in wounded human skin.

Seiser Saskia S Janker Lukas L Zila Nina N Mildner Michael M Rakita Ana A Matiasek Johannes J Bileck Andrea A Gerner Christopher C Paulitschke Verena V Elbe-Bürger Adelheid A

Scientific reports 20210108 1

Octenidine dihydrochloride (OCT) is a widely used antiseptic molecule, promoting skin wound healing accompanied with improved scar quality after surgical procedures. However, the mechanisms by which OCT is contributing to tissue regeneration are not yet completely clear. In this study, we have used a superficial wound model by tape stripping of ex vivo human skin. Protein profiles of wounded skin biopsies treated with OCT-containing hydrogel and the released secretome were analyzed using liquid ...[more]

PMID: 33420112

Publication: 1/2

Similar Datasets

Project description:Brain metastases of melanoma are associated with therapy resistance and poor prognosis. It is not fully understood whether and how the selection of cells capable of metastasizing into the brain is accompanied by the establishment of specific features. For the investigation of these questions, we made use of previously described xenograft mouse models for primary human melanoma cells distinguishing cutaneous from cerebellar metastases from the same genetic background. Previous experiments suggested that cultured cells derived from these xenografts still maintain properties characteristic for the microenvironment of the originating metastases. Such corresponding pairs of metastatic cells were obtained from four individual donors, resulting in eight cell-lines presently investigated with regard to molecular properties characteristic for metastasis. Label free proteome profiling revealed significant alterations when comparing corresponding pairs of cutaneous and cerebellar metastases from the same donor. Molecules previously associated with metastasis such as cell adhesion molecules, immune regulators, epithelial mesenchymal transition markers, stem cell markers, redox regulators and cytokines were found differently expressed. This was also observed with regard to eicosanoids considered relevant for metastasis such as PGE2 and 12-HETE. However, no commonalities in the molecular characteristics of cerebellar metastases were identified in all four donors. Multiparametric morphological analysis of cells also revealed alterations associated with the kind of metastases, while lacking uniformity. In conclusion, here we describe that xenografted melanoma cells derived from two different microenvironments, i.e. cutaneous and cerebellar metastases, display significant alterations in the expression of molecules associated with metastastic properties. The observed lack of uniformity suggests that metastatic cells may find individual strategies to adapt to their microenvironmental challenges accompanied by the establishment of individual cell characteristics.

Project description:In patients with advanced colorectal cancer, leucovorin, fluorouracil, and irinotecan (FOLFIRI) is considered as one of the reference first-line treatments. However, only about half of treated patients respond to this regimen, and there is no clinically useful marker that predicts response. A major clinical challenge is to identify the subset of patients who could benefit from this chemotherapy. We aimed to identify a gene expression profile in primary colon cancer tissue that could predict chemotherapy response. Patients and Methods:- Tumor colon samples from 21 patients with advanced colorectal cancer were analyzed for gene expression profiling using Human Genome GeneChip arrays U133. At the end of the first-line treatment, the best observed response, according to WHO criteria, was used to define the responders and nonresponders. Discriminatory genes were first selected by the significance analysis of microarrays algorithm and the area under the receiver operating characteristic curve. A predictor classifier was then constructed using support vector machines. Finally, leave-one-out cross validation was used to estimate the performance and the accuracy of the output class prediction rule. Results:- We determined a set of 14 predictor genes of response to FOLFIRI. Nine of nine responders (100% specificity) and 11 of 12 nonresponders (92% sensitivity) were classified correctly, for an overall accuracy of 95%. Conclusion:- After validation in an independent cohort of patients, our gene signature could be used as a decision tool to assist oncologists in selecting colorectal cancer patients who could benefit from FOLFIRI chemotherapy, both in the adjuvant and the first-line metastatic setting. All tissue samples were maintained at −180°C (liquid nitrogen) until RNA extraction and were weighed before homogenization. Tissue samples were then disrupted directly into a lysis buffer using Mixer Mill MM 300 (Qiagen, Valencia, CA). Total RNA was isolated from tissue lysates using the RNeasy Mini Kit (Qiagen), and additional DNAse digestion was performed on all samples during the extraction process (RNase-Free DNase Set Protocol for DNase treatment on RNeasy Mini Spin Columns; Qiagen). After each extraction, a small fraction of the total RNA preparation was taken to determine the quality of the sample and the yield of total RNA. Controls analyses were performed by UV spectroscopy and analysis of total RNA profile using the Agilent RNA 6000 Nano LabChip Kit with the Agilent 2100 Bioanalyser (Agilent Technologies, Palo Alto, CA) to determine RNA purity, quantity, and integrity.

Dataset Information

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

Publications

Octenidine-based hydrogel shows anti-inflammatory and protease-inhibitory capacities in wounded human skin.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure