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A multiomics analysis of S100 protein family in breast cancer
The S100 gene family is the largest subfamily of calcium binding proteins of EF-hand type, expressed in tissue and cell-specific manner, acting both as intracellular regulators and extracellular mediators. There is a growing interest in the S100 proteins and their relationships with different cancer...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6044374/ https://www.ncbi.nlm.nih.gov/pubmed/30018736 http://dx.doi.org/10.18632/oncotarget.25561 |
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author | Cancemi, Patrizia Buttacavoli, Miriam Di Cara, Gianluca Albanese, Nadia Ninfa Bivona, Serena Pucci-Minafra, Ida Feo, Salvatore |
author_facet | Cancemi, Patrizia Buttacavoli, Miriam Di Cara, Gianluca Albanese, Nadia Ninfa Bivona, Serena Pucci-Minafra, Ida Feo, Salvatore |
author_sort | Cancemi, Patrizia |
collection | PubMed |
description | The S100 gene family is the largest subfamily of calcium binding proteins of EF-hand type, expressed in tissue and cell-specific manner, acting both as intracellular regulators and extracellular mediators. There is a growing interest in the S100 proteins and their relationships with different cancers because of their involvement in a variety of biological events closely related to tumorigenesis and cancer progression. However, the collective role and the possible coordination of this group of proteins, as well as the functional implications of their expression in breast cancer (BC) is still poorly known. We previously reported a large-scale proteomic investigation performed on BC patients for the screening of multiple forms of S100 proteins. Present study was aimed to assess the functional correlation between protein and gene expression patterns and the prognostic values of the S100 family members in BC. By using data mining, we showed that S100 members were collectively deregulated in BC, and their elevated expression levels were correlated with shorter survival and more aggressive phenotypes of BC (basal like, HER2 enriched, ER-negative and high grading). Moreover a multi-omics functional network analysis highlighted the regulatory effects of S100 members on several cellular pathways associated with cancer and cancer progression, expecially immune response and inflammation. Interestingly, for the first time, a pathway analysis was successfully applied on different omics data (transcriptomics and proteomics) revealing a good convergence between pathways affected by S100 in BC. Our data confirm S100 members as a promising panel of biomarkers for BC prognosis. |
format | Online Article Text |
id | pubmed-6044374 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-60443742018-07-17 A multiomics analysis of S100 protein family in breast cancer Cancemi, Patrizia Buttacavoli, Miriam Di Cara, Gianluca Albanese, Nadia Ninfa Bivona, Serena Pucci-Minafra, Ida Feo, Salvatore Oncotarget Research Paper The S100 gene family is the largest subfamily of calcium binding proteins of EF-hand type, expressed in tissue and cell-specific manner, acting both as intracellular regulators and extracellular mediators. There is a growing interest in the S100 proteins and their relationships with different cancers because of their involvement in a variety of biological events closely related to tumorigenesis and cancer progression. However, the collective role and the possible coordination of this group of proteins, as well as the functional implications of their expression in breast cancer (BC) is still poorly known. We previously reported a large-scale proteomic investigation performed on BC patients for the screening of multiple forms of S100 proteins. Present study was aimed to assess the functional correlation between protein and gene expression patterns and the prognostic values of the S100 family members in BC. By using data mining, we showed that S100 members were collectively deregulated in BC, and their elevated expression levels were correlated with shorter survival and more aggressive phenotypes of BC (basal like, HER2 enriched, ER-negative and high grading). Moreover a multi-omics functional network analysis highlighted the regulatory effects of S100 members on several cellular pathways associated with cancer and cancer progression, expecially immune response and inflammation. Interestingly, for the first time, a pathway analysis was successfully applied on different omics data (transcriptomics and proteomics) revealing a good convergence between pathways affected by S100 in BC. Our data confirm S100 members as a promising panel of biomarkers for BC prognosis. Impact Journals LLC 2018-06-26 /pmc/articles/PMC6044374/ /pubmed/30018736 http://dx.doi.org/10.18632/oncotarget.25561 Text en Copyright: © 2018 Cancemi et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Cancemi, Patrizia Buttacavoli, Miriam Di Cara, Gianluca Albanese, Nadia Ninfa Bivona, Serena Pucci-Minafra, Ida Feo, Salvatore A multiomics analysis of S100 protein family in breast cancer |
title | A multiomics analysis of S100 protein family in breast cancer |
title_full | A multiomics analysis of S100 protein family in breast cancer |
title_fullStr | A multiomics analysis of S100 protein family in breast cancer |
title_full_unstemmed | A multiomics analysis of S100 protein family in breast cancer |
title_short | A multiomics analysis of S100 protein family in breast cancer |
title_sort | multiomics analysis of s100 protein family in breast cancer |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6044374/ https://www.ncbi.nlm.nih.gov/pubmed/30018736 http://dx.doi.org/10.18632/oncotarget.25561 |
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