A protein deep sequencing evaluation of metastatic melanoma tissues

Charlotte Welinder; Krzysztof Pawłowski; Yutaka Sugihara; Maria Yakovleva; Göran Jönsson; Christian Ingvar; Lotta Lundgren; Bo Baldetorp; Håkan Olsson; Melinda Rezeli; Bo Jansson; Thomas Laurell; Thomas Fehniger; Balazs Döme; Johan Malm; Elisabet Wieslander; Toshihide Nishimura; György Marko-Varga

doi:10.1371/journal.pone.0123661

A protein deep sequencing evaluation of metastatic melanoma tissues

PLoS One. 2015 Apr 13;10(4):e0123661. doi: 10.1371/journal.pone.0123661. eCollection 2015.

Authors

Charlotte Welinder¹, Krzysztof Pawłowski², Yutaka Sugihara³, Maria Yakovleva⁴, Göran Jönsson³, Christian Ingvar⁵, Lotta Lundgren⁶, Bo Baldetorp³, Håkan Olsson⁷, Melinda Rezeli⁸, Bo Jansson³, Thomas Laurell⁹, Thomas Fehniger¹, Balazs Döme¹⁰, Johan Malm¹¹, Elisabet Wieslander³, Toshihide Nishimura¹², György Marko-Varga¹³

Affiliations

¹ Oncology and Pathology, Dept. of Clinical Sciences, Lund University, Lund, Sweden; Centre of Excellence in Biological and Medical Mass Spectrometry "CEBMMS", Biomedical Centre D13, Lund University, Lund, Sweden.
² Warsaw University of Life Sciences, Warsaw, Poland.
³ Oncology and Pathology, Dept. of Clinical Sciences, Lund University, Lund, Sweden.
⁴ National Korányi Institute of Pulmonology, Budapest, Hungary; Clinical Protein Science & Imaging, Biomedical Centre, Dept. of Biomedical Engineering, Lund University, Lund, Sweden.
⁵ Surgery, Dept. of Clinical Sciences, Lund University, Skåne University Hospital, Lund, Sweden.
⁶ Oncology and Pathology, Dept. of Clinical Sciences, Lund University, Lund, Sweden; Skåne University Hospital, Lund, Sweden.
⁷ Oncology and Pathology, Dept. of Clinical Sciences, Lund University, Lund, Sweden; Skåne University Hospital, Lund, Sweden; Cancer Epidemiology, Dept. of Clinical Sciences, Lund University, Lund, Sweden.
⁸ Clinical Protein Science & Imaging, Biomedical Centre, Dept. of Biomedical Engineering, Lund University, Lund, Sweden.
⁹ Centre of Excellence in Biological and Medical Mass Spectrometry "CEBMMS", Biomedical Centre D13, Lund University, Lund, Sweden; Clinical Protein Science & Imaging, Biomedical Centre, Dept. of Biomedical Engineering, Lund University, Lund, Sweden.
¹⁰ National Korányi Institute of Pulmonology, Budapest, Hungary; Department of Thoracic Surgery, Medical University of Vienna, Vienna, Austria.
¹¹ Section for Clinical Chemistry, Dept. of Laboratory Medicine, Lund University, Skåne University Hospital in Malmö, Malmö, Sweden.
¹² Oncology and Pathology, Dept. of Clinical Sciences, Lund University, Lund, Sweden; Centre of Excellence in Biological and Medical Mass Spectrometry "CEBMMS", Biomedical Centre D13, Lund University, Lund, Sweden; First Dept. of Surgery, Tokyo Medical University, Tokyo, Japan.
¹³ Centre of Excellence in Biological and Medical Mass Spectrometry "CEBMMS", Biomedical Centre D13, Lund University, Lund, Sweden; Clinical Protein Science & Imaging, Biomedical Centre, Dept. of Biomedical Engineering, Lund University, Lund, Sweden; First Dept. of Surgery, Tokyo Medical University, Tokyo, Japan.

Abstract

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 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. The raw data have been deposited to the ProteomeXchange with identifiers PXD001724 and PXD001725.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biological Specimen Banks
Chromatography, Liquid
Computational Biology
Data Mining
Databases, Protein*
Drug Resistance, Neoplasm
Gene Expression Regulation, Neoplastic
Humans
Lymphatic Metastasis
Melanoma / metabolism*
Melanoma, Cutaneous Malignant
Neoplasm Metastasis
Proteomics / methods
Sequence Analysis, Protein / methods*
Skin Neoplasms / metabolism*
Sweden
Tandem Mass Spectrometry

Grants and funding

This work was supported by grants from Mrs. Berta Kamprad Foundation, Swedish Academy of Pharmaceutical Sciences, Swedish Research Council, the Swedish Foundation for Strategic Research, Vinnova, Ingabritt & Arne Lundbergs forskningsstiftelse, the Crafoord Foundation and European Research Council Advanced Grant ERC-2011-294576. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.