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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2019
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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. |
format | Online Article Text |
id | pubmed-6435712 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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