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Biomarker robustness reveals the PDGF network as driving disease outcome in ovarian cancer patients in multiple studies
BACKGROUND: Ovarian cancer causes more deaths than any other gynecological cancer. Identifying the molecular mechanisms that drive disease progress in ovarian cancer is a critical step in providing therapeutics, improving diagnostics, and affiliating clinical behavior with disease etiology. Identifi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3298526/ https://www.ncbi.nlm.nih.gov/pubmed/22236809 http://dx.doi.org/10.1186/1752-0509-6-3 |
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author | Ben-Hamo, Rotem Efroni, Sol |
author_facet | Ben-Hamo, Rotem Efroni, Sol |
author_sort | Ben-Hamo, Rotem |
collection | PubMed |
description | BACKGROUND: Ovarian cancer causes more deaths than any other gynecological cancer. Identifying the molecular mechanisms that drive disease progress in ovarian cancer is a critical step in providing therapeutics, improving diagnostics, and affiliating clinical behavior with disease etiology. Identification of molecular interactions that stratify prognosis is key in facilitating a clinical-molecular perspective. RESULTS: The Cancer Genome Atlas has recently made available the molecular characteristics of more than 500 patients. We used the TCGA multi-analysis study, and two additional datasets and a set of computational algorithms that we developed. The computational algorithms are based on methods that identify network alterations and quantify network behavior through gene expression. We identify a network biomarker that significantly stratifies survival rates in ovarian cancer patients. Interestingly, expression levels of single or sets of genes do not explain the prognostic stratification. The discovered biomarker is composed of the network around the PDGF pathway. The biomarker enables prognosis stratification. CONCLUSION: The work presented here demonstrates, through the power of gene-expression networks, the criticality of the PDGF network in driving disease course. In uncovering the specific interactions within the network, that drive the phenotype, we catalyze targeted treatment, facilitate prognosis and offer a novel perspective into hidden disease heterogeneity. |
format | Online Article Text |
id | pubmed-3298526 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32985262012-03-12 Biomarker robustness reveals the PDGF network as driving disease outcome in ovarian cancer patients in multiple studies Ben-Hamo, Rotem Efroni, Sol BMC Syst Biol Research Article BACKGROUND: Ovarian cancer causes more deaths than any other gynecological cancer. Identifying the molecular mechanisms that drive disease progress in ovarian cancer is a critical step in providing therapeutics, improving diagnostics, and affiliating clinical behavior with disease etiology. Identification of molecular interactions that stratify prognosis is key in facilitating a clinical-molecular perspective. RESULTS: The Cancer Genome Atlas has recently made available the molecular characteristics of more than 500 patients. We used the TCGA multi-analysis study, and two additional datasets and a set of computational algorithms that we developed. The computational algorithms are based on methods that identify network alterations and quantify network behavior through gene expression. We identify a network biomarker that significantly stratifies survival rates in ovarian cancer patients. Interestingly, expression levels of single or sets of genes do not explain the prognostic stratification. The discovered biomarker is composed of the network around the PDGF pathway. The biomarker enables prognosis stratification. CONCLUSION: The work presented here demonstrates, through the power of gene-expression networks, the criticality of the PDGF network in driving disease course. In uncovering the specific interactions within the network, that drive the phenotype, we catalyze targeted treatment, facilitate prognosis and offer a novel perspective into hidden disease heterogeneity. BioMed Central 2012-01-11 /pmc/articles/PMC3298526/ /pubmed/22236809 http://dx.doi.org/10.1186/1752-0509-6-3 Text en Copyright ©2012 Ben-Hamo and Efroni; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ben-Hamo, Rotem Efroni, Sol Biomarker robustness reveals the PDGF network as driving disease outcome in ovarian cancer patients in multiple studies |
title | Biomarker robustness reveals the PDGF network as driving disease outcome in ovarian cancer patients in multiple studies |
title_full | Biomarker robustness reveals the PDGF network as driving disease outcome in ovarian cancer patients in multiple studies |
title_fullStr | Biomarker robustness reveals the PDGF network as driving disease outcome in ovarian cancer patients in multiple studies |
title_full_unstemmed | Biomarker robustness reveals the PDGF network as driving disease outcome in ovarian cancer patients in multiple studies |
title_short | Biomarker robustness reveals the PDGF network as driving disease outcome in ovarian cancer patients in multiple studies |
title_sort | biomarker robustness reveals the pdgf network as driving disease outcome in ovarian cancer patients in multiple studies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3298526/ https://www.ncbi.nlm.nih.gov/pubmed/22236809 http://dx.doi.org/10.1186/1752-0509-6-3 |
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