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A protein deep sequencing evaluation of metastatic melanoma tissues.

Welinder, Charlotte LU ; Pawlowski, Krzysztof LU ; Sugihara, Yutaka LU ; Yakovleva, Maria LU ; Jönsson, Göran B LU ; Ingvar, Christian LU ; Lundgren, Lotta LU ; Baldetorp, Bo LU ; Olsson, Håkan LU and Rezeli, Melinda LU , et al. (2015) In PLoS ONE 10(4).
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... (More)
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. (Less)
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PLoS ONE
volume
10
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4
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Public Library of Science
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  • pmid:25874936
  • wos:000352845100196
  • scopus:84928798125
ISSN
1932-6203
DOI
10.1371/journal.pone.0123661
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English
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yes
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76b1cd8a-3c2e-4a33-986a-bfc270e616ba (old id 5341806)
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http://www.ncbi.nlm.nih.gov/pubmed/25874936?dopt=Abstract
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2015-05-05 18:39:16
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@article{76b1cd8a-3c2e-4a33-986a-bfc270e616ba,
  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.},
  articleno    = {e0123661},
  author       = {Welinder, Charlotte and Pawlowski, Krzysztof and Sugihara, Yutaka and Yakovleva, Maria and Jönsson, Göran B and Ingvar, Christian and Lundgren, Lotta and Baldetorp, Bo and Olsson, Håkan and Rezeli, Melinda and Jansson, Bo and Laurell, Thomas and Fehniger, Thomas and Döme, Balazs and Malm, Johan and Wieslander, Elisabet and Nishimura, Toshihide and Marko-Varga, György},
  issn         = {1932-6203},
  language     = {eng},
  number       = {4},
  publisher    = {Public Library of Science},
  series       = {PLoS ONE},
  title        = {A protein deep sequencing evaluation of metastatic melanoma tissues.},
  url          = {http://dx.doi.org/10.1371/journal.pone.0123661},
  volume       = {10},
  year         = {2015},
}