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Proteomics analysis of melanoma metastases: association between S100A13 expression and chemotherapy resistance.

ABSTRACT: Disseminated cutaneous malignant melanoma (CMM) is commonly unresponsive to standard chemotherapies, and there are as yet no predictive markers of therapy response.In the present study we collected fresh-frozen pretreatment lymph-node metastasis samples (n=14) from melanoma patients with differential response to dacarbazine (DTIC) or temozolomide (TMZ) chemotherapy, to identify proteins with an impact on treatment response. We performed quantitative protein profiling using tandem mass spectrometry and compared the proteome differences between responders (R) and non-responders (NR), matched for age, gender and histopathological type of CMM.Biological pathway analyses showed several signalling pathways differing between R vs NR, including Rho signalling. Gene expression profiling data was available for a subset of the samples, and the results were compared with the proteomics data. Four proteins with differential expression between R and NR were selected for technical validation by immunoblotting (ISYNA1, F13A1, CSTB and S100A13), and CSTB and S100A13 were further validated on a larger sample set by immunohistochemistry (n=48). The calcium binding protein S100A13 was found to be significantly overexpressed in NR compared with R in all analyses performed.Our results suggest that S100A13 is involved in CMM resistance to DTIC/TMZ.

SUBMITTER: Azimi A

PROVIDER: S-EPMC4021518 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Proteomics analysis of melanoma metastases: association between S100A13 expression and chemotherapy resistance.

Azimi A A Pernemalm M M Frostvik Stolt M M Hansson J J Lehtiö J J Egyházi Brage S S Hertzman Johansson C C

British journal of cancer 20140410 10

<h4>Background</h4>Disseminated cutaneous malignant melanoma (CMM) is commonly unresponsive to standard chemotherapies, and there are as yet no predictive markers of therapy response.<h4>Methods</h4>In the present study we collected fresh-frozen pretreatment lymph-node metastasis samples (n=14) from melanoma patients with differential response to dacarbazine (DTIC) or temozolomide (TMZ) chemotherapy, to identify proteins with an impact on treatment response. We performed quantitative protein pro ...[more]

PMID: 24722184

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Project description:BackgroundMAP 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.MethodsCerebral 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.ResultsIn 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.ConclusionsEmploying 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.

Project description:Perturbations in microRNA (miRNA) expression profiles has been reported for cutaneous malignant melanoma (CMM). With regards to a rapidly growing number of newly discovered miRNA sequences, the availability of up-to-date miRNA expression profiles for primary cutaneous malignant melanoma (PCMM), cutaneous malignant melanoma metastases (CMMM) and benign melanocytic naevi (BMN) is limited. Patients with PCMM (n=9), CMMM (n=4) and BMN (n=8) were included in the study. Specimens were obtained during surgery from the center of the tumors (lesional). An exploratory microarray analysis was performed by miRNA expression profiling based on miRBase V.16. Additionally, the expression levels of selected miRNA candidates were confirmed by TaqMan real-time quantitative polymerase chain reaction (RT-PCR). New miRNA candidates previously not described to be associated with CMM were found to be potentially dysregulated in CMM. Nine patients with PCMM (PCMM1-PCMM9), four patients with CMMM (CMMM1-CMMM4) and eight patients with BMN (BMN1-BMN8) were enrolled in the present study. All cutaneous specimens were harvested in the operating room, immediately stored in RNAlater (Quiagen, Hilden, Germany) and kept at - 80 °C until RNA isolation. Total RNA including miRNAs was isolated using the miRNeasy Mini Kit (Quiagen, Hilden, Germany) according to the manufacturer’s protocol. RNA concentration and purity was determined by NanoDrop ND-1000 spectral photometer (Peqlab, Erlangen, Germany). RNA integrity control (RIN) was determined by means of capillary electrophoresis with the 2100 Bioanalyzer and the RNA 6000 NanoLabCHip Kits (both Agilent Technologies, Santa Clara, USA). To be further considered for Microarray analysis a RIN ≥ 7.0 indicating medium to good RNA quality was defined as inclusion criteria. For assessment of labeling and hybridization efficiencies total RNA samples were spiked with in-vitro synthesized oligonucleotides by using the MicroRNA Spike-In Kit (Agilent Technologies, Santa Clara, USA). A total of 100 ng total RNA per sample were introduced into a labeling reaction. The spiked total RNA was treated with alkaline calf intestine phosphatase (CIP). The dephosphorylated RNA was labeled with the miRNA Complete Labeling and Hyb Kit (Agilent Technologies, Santa Clara, USA) according to the manufacturer´s instructions using T4 RNA ligase, incorporating Cyanine 3-Cytidine biphosphate (pCp). The Cyanine-3-labeled miRNA samples were prepared for One-Color based hybridization with Complete miRNA Labeling and Hyb Kit (Agilent Technologies, Santa Clara, USA) according to the manufacturer´s instructions. Labeled miRNA samples were hybridized at 55°C for 20 hrs on separate Human miRNA Microarrays Release 16.0 (8x60K format, (Agilent Technologies, Santa Clara, USA). Afterwards, microarrays were washed with increasing stringency using Gene Expression Wash Buffers (Agilent Technologies, Santa Clara, USA) followed by drying with acetonitrile (Sigma-Aldich, St.Louis, USA). Fluorescent signal intensities were detected with Scan Control A.8.4.1 Software (Agilent Technologies, Santa Clara, USA) on the Agilent DNA Microarray Scanner and extracted from the images using Feature Extraction 10.7.3.1 Software (Agilent Technologies, Santa Clara, USA). All the steps described were carried out according to the manufacturer´s instructions.

Project description:The profound disparity in response to immune checkpoint blockade (ICB) by cutaneous melanoma (CM) and uveal melanoma (UM) patients is not well understood. Therefore, we characterized metastases of CM and UM from the same metastatic site (liver), in order to dissect the potential underlying mechanism in differential response on ICB. Tumor liver samples from CM (n=38) and UM (n=28) patients were analyzed at the genomic (whole exome sequencing), transcriptional (RNA sequencing) and protein (immunohistochemistry and GeoMx Digital Spatial Profiling) level. Comparison of CM and UM metastases from the same metastatic site revealed that, although originating from the same melanocyte lineage, CM and UM differed in somatic mutation profile, copy number profile, tumor mutational burden (TMB) and consequently predicted neoantigens. A higher melanin content and higher expression of the melanoma differentiation antigen MelanA was observed in liver metastases of UM patients. No difference in B2M and human leukocyte antigen-DR (HLA-DR) expression was observed. A higher expression of programmed cell death ligand 1 (PD-L1) was found in CM compared with UM liver metastases, although the majority of CM and UM liver metastases lacked PD-L1 expression. There was no difference in the extent of immune infiltration observed between CM and UM metastases, with the exception of a higher expression of CD163 (p<0.0001) in CM liver samples. While the extent of immune infiltration was similar for CM and UM metastases, the ratio of exhausted CD8 T cells to cytotoxic T cells, to total CD8 T cells and to Th1 cells, was significantly higher in UM metastases. While TMB was different between CM and UM metastases, tumor immune infiltration was similar. The greater dependency on PD-L1 as an immune checkpoint in CM and the identification of higher exhaustion ratios in UM may both serve as explanations for the difference in response to ICB. Consequently, in order to improve current treatment for metastatic UM, reversal of T cell exhaustion beyond programmed cell death 1 blockade should be considered.

Dataset Information

Proteomics analysis of melanoma metastases: association between S100A13 expression and chemotherapy resistance.

Publications

Proteomics analysis of melanoma metastases: association between S100A13 expression and chemotherapy resistance.

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