Dataset Information

A Protein Deep Sequencing Evaluation of Metastatic Melanoma Tissues, fractionated approach

ABSTRACT: Malignant melanoma has currently the highest increase of incidence of malignancies in the western world. In early stages, front line therapy is surgical excision of the primary tumor. Metastatic disease has previously has very limited possibilities to be cured. Recently, several protein kinase inhibitors and immune modifiers have shown promising results but drug resistance in metastasized melanoma remains a major problem. The need for clinical biomarkers to follow disease progression and treatment effects is high. The aim of the present study was to build a protein sequence database in metastatic melanoma, searching for novel, relevant biomarkers. Ten lymph node metastases (South-Swedish Malignant Melanoma Biobank) were subjected to global protein expression analysis using two proteomics approaches (with/without orthogonal fractionation). Fractionation produced higher numbers of protein identifications (4284). Combining both methods, 5326 unique proteins were identified (2641 proteins overlapping). Deep mining proteomics may contribute to the discovery of novel biomarkers for metastatic melanoma, for example dividing the samples into two metastatic melanoma "genomic subtypes", ("pigmentation" and "high immune") revealed several proteins showing differential levels of expression. In conclusion, the present study provides an initial version of a metastatic melanoma protein sequence database producing a total of more than 5000 unique protein identifications. This dataset consists of data for four samples, analysed by applying strong cation exchange chromatography (SCX) step before the MS step. A sister dataset, consisting of ten samples (that included the current four), was analysed without the (SCX) step.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Melanocyte, Lymph Node

DISEASE(S): Metastatic Melanoma

SUBMITTER: Krzysztof Pawlowski

LAB HEAD: György Marko-Varga

PROVIDER: PXD001724 | Pride | 2015-04-17

REPOSITORIES: Pride

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Publications

A protein deep sequencing evaluation of metastatic melanoma tissues.

Welinder Charlotte C Pawłowski Krzysztof K Sugihara Yutaka Y Yakovleva Maria M Jönsson Göran G Ingvar Christian C Lundgren Lotta L Baldetorp Bo B Olsson Håkan H Rezeli Melinda M Jansson Bo B Laurell Thomas T Fehniger Thomas T Döme Balazs B Malm Johan J Wieslander Elisabet E Nishimura Toshihide T Marko-Varga György G

PloS one 20150413 4

Malignant melanoma has the highest increase of incidence of malignancies in the western world. In early stages, front line therapy is surgical excision of the primary tumor. Metastatic disease has very limited possibilities for cure. Recently, several protein kinase inhibitors and immune modifiers have shown promising clinical results but drug resistance in metastasized melanoma remains a major problem. The need for routine clinical biomarkers to follow disease progression and treatment efficacy ...[more]

PMID: 25874936

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Project description:Background Breast cancer patients who present in the early stage of disease are affected by metastasis to the axillary group of lymph nodes. The first among this group that is affected is called as sentinel lymph node, and metastasis to this lymph node is crucial for the staging of cancer and the quality of surgical intervention. Sentinel Lymph Node Biopsy (SLNB) that is currently used to assess lymph node metastasis is neither sensitive, nor specific, is time-consuming, thereby necessitating the identification of novel biomarkers that can flag sentinel lymph node metastasis. Methods Breast cancer patients were screened, and those with early stage were recruited in the study. Surgical resection of the breast was followed by identification of sentinel lymph nodes by methylene fluorescent technique. Histo-pathology of fresh frozen section biopsy was used as the gold standard to assign the clinical phenotypes of metastatic (SLNM+) and non-metastatic sentinel lymph nodes (SLNM-). Discovery phase of the experiment included isobaric Tags for Relative and Absolute Quantitation (iTRAQ) technique comprising of six comparative experiments coupled with mass spectrometric analysis on Orbitrap Fusion to identify differentially expressed proteins on Proteome Discoverer 2.4. Functional enrichment and pathway analyses of differentially regulated genes was carried out in DAVID functional annotation tool. Validation was done by ELISA and protein concentrations were used to estimate the ROC for computing diagnostic parameters. Results Based on MS/MS spectra there were 2396 unique protein groups and 81 differentially expressed proteins comparing SLNB + and SLNB -. Nineteen proteins up-regulated, and eight proteins that were down regulated in SLNB+ as compared to SLNB-. Bioinformatic analysis showed the implication of extra cellular matrix proteins and ECM-receptor interaction pathways to be implicated in lymph node metastasis. ELISA confirmed the up-regulation of caveolin 1, collagen α-1, desmin, fibrillin-1, and microfibrillar associated glycoprotein 4 in metastatic, as compared to non-metastatic lymph nodes. These proteins are known to be integral in tumorogenesis, cell proliferation, invasion, cell survival and anti-apoptosis. These proteins have 80%-100%, of sensitivity and specificity to differentiate the two clinical phenotypes. Conclusion Identified extra cellular matrix protein biomarkers have requisite diagnostic parameters to be developed as a translational tool to assess the status of sentinel lymph nodes during mastectomy procedure to guide surgical therapy of axillary lymph nodes in early breast oncology.

Dataset Information

A Protein Deep Sequencing Evaluation of Metastatic Melanoma Tissues, fractionated approach

Publications

A protein deep sequencing evaluation of metastatic melanoma tissues.

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