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Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data

Metastatic melanoma is one of the most common deadly cancers, and robust biomarkers are still needed, e.g. to predict survival and treatment efficiency. Here, protein expression analysis of one hundred eleven melanoma lymph node metastases using high resolution mass spectrometry is coupled with in-d...

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Autores principales: Betancourt, Lazaro Hiram, Pawłowski, Krzysztof, Eriksson, Jonatan, Szasz, A. Marcell, Mitra, Shamik, Pla, Indira, Welinder, Charlotte, Ekedahl, Henrik, Broberg, Per, Appelqvist, Roger, Yakovleva, Maria, Sugihara, Yutaka, Miharada, Kenichi, Ingvar, Christian, Lundgren, Lotta, Baldetorp, Bo, Olsson, Håkan, Rezeli, Melinda, Wieslander, Elisabet, Horvatovich, Peter, Malm, Johan, Jönsson, Göran, Marko-Varga, György
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6435712/
https://www.ncbi.nlm.nih.gov/pubmed/30914758
http://dx.doi.org/10.1038/s41598-019-41625-z
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author Betancourt, Lazaro Hiram
Pawłowski, Krzysztof
Eriksson, Jonatan
Szasz, A. Marcell
Mitra, Shamik
Pla, Indira
Welinder, Charlotte
Ekedahl, Henrik
Broberg, Per
Appelqvist, Roger
Yakovleva, Maria
Sugihara, Yutaka
Miharada, Kenichi
Ingvar, Christian
Lundgren, Lotta
Baldetorp, Bo
Olsson, Håkan
Rezeli, Melinda
Wieslander, Elisabet
Horvatovich, Peter
Malm, Johan
Jönsson, Göran
Marko-Varga, György
author_facet Betancourt, Lazaro Hiram
Pawłowski, Krzysztof
Eriksson, Jonatan
Szasz, A. Marcell
Mitra, Shamik
Pla, Indira
Welinder, Charlotte
Ekedahl, Henrik
Broberg, Per
Appelqvist, Roger
Yakovleva, Maria
Sugihara, Yutaka
Miharada, Kenichi
Ingvar, Christian
Lundgren, Lotta
Baldetorp, Bo
Olsson, Håkan
Rezeli, Melinda
Wieslander, Elisabet
Horvatovich, Peter
Malm, Johan
Jönsson, Göran
Marko-Varga, György
author_sort Betancourt, Lazaro Hiram
collection PubMed
description Metastatic melanoma is one of the most common deadly cancers, and robust biomarkers are still needed, e.g. to predict survival and treatment efficiency. Here, protein expression analysis of one hundred eleven melanoma lymph node metastases using high resolution mass spectrometry is coupled with in-depth histopathology analysis, clinical data and genomics profiles. This broad view of protein expression allowed to identify novel candidate protein markers that improved prediction of survival in melanoma patients. Some of the prognostic proteins have not been reported in the context of melanoma before, and few of them exhibit unexpected relationship to survival, which likely reflects the limitations of current knowledge on melanoma and shows the potential of proteomics in clinical cancer research.
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spelling pubmed-64357122019-04-03 Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data Betancourt, Lazaro Hiram Pawłowski, Krzysztof Eriksson, Jonatan Szasz, A. Marcell Mitra, Shamik Pla, Indira Welinder, Charlotte Ekedahl, Henrik Broberg, Per Appelqvist, Roger Yakovleva, Maria Sugihara, Yutaka Miharada, Kenichi Ingvar, Christian Lundgren, Lotta Baldetorp, Bo Olsson, Håkan Rezeli, Melinda Wieslander, Elisabet Horvatovich, Peter Malm, Johan Jönsson, Göran Marko-Varga, György Sci Rep Article Metastatic melanoma is one of the most common deadly cancers, and robust biomarkers are still needed, e.g. to predict survival and treatment efficiency. Here, protein expression analysis of one hundred eleven melanoma lymph node metastases using high resolution mass spectrometry is coupled with in-depth histopathology analysis, clinical data and genomics profiles. This broad view of protein expression allowed to identify novel candidate protein markers that improved prediction of survival in melanoma patients. Some of the prognostic proteins have not been reported in the context of melanoma before, and few of them exhibit unexpected relationship to survival, which likely reflects the limitations of current knowledge on melanoma and shows the potential of proteomics in clinical cancer research. Nature Publishing Group UK 2019-03-26 /pmc/articles/PMC6435712/ /pubmed/30914758 http://dx.doi.org/10.1038/s41598-019-41625-z Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Betancourt, Lazaro Hiram
Pawłowski, Krzysztof
Eriksson, Jonatan
Szasz, A. Marcell
Mitra, Shamik
Pla, Indira
Welinder, Charlotte
Ekedahl, Henrik
Broberg, Per
Appelqvist, Roger
Yakovleva, Maria
Sugihara, Yutaka
Miharada, Kenichi
Ingvar, Christian
Lundgren, Lotta
Baldetorp, Bo
Olsson, Håkan
Rezeli, Melinda
Wieslander, Elisabet
Horvatovich, Peter
Malm, Johan
Jönsson, Göran
Marko-Varga, György
Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data
title Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data
title_full Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data
title_fullStr Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data
title_full_unstemmed Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data
title_short Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data
title_sort improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6435712/
https://www.ncbi.nlm.nih.gov/pubmed/30914758
http://dx.doi.org/10.1038/s41598-019-41625-z
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