TY - JOUR
T1 - A protein deep sequencing evaluation of metastatic melanoma tissues
AU - Welinder, Charlotte
AU - Pawłowski, Krzysztof
AU - Sugihara, Yutaka
AU - Yakovleva, Maria
AU - Jönsson, Göran
AU - Ingvar, Christian
AU - Lundgren, Lotta
AU - Baldetorp, Bo
AU - Olsson, Håkan
AU - Rezeli, Melinda
AU - Jansson, Bo
AU - Laurell, Thomas
AU - Fehniger, Thomas
AU - Döme, Balazs
AU - Malm, Johan
AU - Wieslander, Elisabet
AU - Nishimura, Toshihide
AU - Marko-Varga, György
N1 - Publisher Copyright:
© 2015 Welinder et al.
PY - 2015/4/13
Y1 - 2015/4/13
N2 - 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.
AB - 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.
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U2 - 10.1371/journal.pone.0123661
DO - 10.1371/journal.pone.0123661
M3 - Article
C2 - 25874936
AN - SCOPUS:84928798125
SN - 1932-6203
VL - 10
JO - PloS one
JF - PloS one
IS - 4
M1 - e0123661
ER -