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

Betancourt, Lazaro Hiram LU ; Pawłowski, Krzysztof LU ; Eriksson, Jonatan LU ; Szasz, A. Marcell LU ; Mitra, Shamik LU ; Pla, Indira LU ; Welinder, Charlotte LU ; Ekedahl, Henrik LU ; Broberg, Per LU and Appelqvist, Roger LU , et al. (2019) In Scientific Reports 9(1).
Abstract

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... (More)

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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Scientific Reports
volume
9
issue
1
publisher
Nature Publishing Group
external identifiers
  • scopus:85063494011
ISSN
2045-2322
DOI
10.1038/s41598-019-41625-z
language
English
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yes
id
e2298e78-7a9c-4979-8670-07c0a2968b0c
date added to LUP
2019-04-05 09:58:42
date last changed
2019-04-30 04:10:19
@article{e2298e78-7a9c-4979-8670-07c0a2968b0c,
  abstract     = {<p>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.</p>},
  articleno    = {5154},
  author       = {Betancourt, Lazaro Hiram and Pawłowski, Krzysztof and Eriksson, Jonatan and Szasz, A. Marcell and Mitra, Shamik and Pla, Indira and Welinder, Charlotte and Ekedahl, Henrik and Broberg, Per and Appelqvist, Roger and Yakovleva, Maria and Sugihara, Yutaka and Miharada, Kenichi and Ingvar, Christian and Lundgren, Lotta and Baldetorp, Bo and Olsson, Håkan and Rezeli, Melinda and Wieslander, Elisabet and Horvatovich, Peter and Malm, Johan and Jönsson, Göran and Marko-Varga, György},
  issn         = {2045-2322},
  language     = {eng},
  month        = {03},
  number       = {1},
  publisher    = {Nature Publishing Group},
  series       = {Scientific Reports},
  title        = {Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data},
  url          = {http://dx.doi.org/10.1038/s41598-019-41625-z},
  volume       = {9},
  year         = {2019},
}