Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis
BACKGROUND: Redox metabolism is often considered a potential target for cancer treatment, but a systematic examination of redox responses in hepatocellular carcinoma (HCC) is missing. METHODS: Here, we employed systems biology and biological network analyses to reveal key roles of genes associated w...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412169/ https://www.ncbi.nlm.nih.gov/pubmed/30606699 http://dx.doi.org/10.1016/j.ebiom.2018.12.057 |
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author | Benfeitas, Rui Bidkhori, Gholamreza Mukhopadhyay, Bani Klevstig, Martina Arif, Muhammad Zhang, Cheng Lee, Sunjae Cinar, Resat Nielsen, Jens Uhlen, Mathias Boren, Jan Kunos, George Mardinoglu, Adil |
author_facet | Benfeitas, Rui Bidkhori, Gholamreza Mukhopadhyay, Bani Klevstig, Martina Arif, Muhammad Zhang, Cheng Lee, Sunjae Cinar, Resat Nielsen, Jens Uhlen, Mathias Boren, Jan Kunos, George Mardinoglu, Adil |
author_sort | Benfeitas, Rui |
collection | PubMed |
description | BACKGROUND: Redox metabolism is often considered a potential target for cancer treatment, but a systematic examination of redox responses in hepatocellular carcinoma (HCC) is missing. METHODS: Here, we employed systems biology and biological network analyses to reveal key roles of genes associated with redox metabolism in HCC by integrating multi-omics data. FINDINGS: We found that several redox genes, including 25 novel potential prognostic genes, are significantly co-expressed with liver-specific genes and genes associated with immunity and inflammation. Based on an integrative analysis, we found that HCC tumors display antagonistic behaviors in redox responses. The two HCC groups are associated with altered fatty acid, amino acid, drug and hormone metabolism, differentiation, proliferation, and NADPH-independent vs -dependent antioxidant defenses. Redox behavior varies with known tumor subtypes and progression, affecting patient survival. These antagonistic responses are also displayed at the protein and metabolite level and were validated in several independent cohorts. We finally showed the differential redox behavior using mice transcriptomics in HCC and noncancerous tissues and associated with hypoxic features of the two redox gene groups. INTERPRETATION: Our integrative approaches highlighted mechanistic differences among tumors and allowed the identification of a survival signature and several potential therapeutic targets for the treatment of HCC. |
format | Online Article Text |
id | pubmed-6412169 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-64121692019-03-21 Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis Benfeitas, Rui Bidkhori, Gholamreza Mukhopadhyay, Bani Klevstig, Martina Arif, Muhammad Zhang, Cheng Lee, Sunjae Cinar, Resat Nielsen, Jens Uhlen, Mathias Boren, Jan Kunos, George Mardinoglu, Adil EBioMedicine Research paper BACKGROUND: Redox metabolism is often considered a potential target for cancer treatment, but a systematic examination of redox responses in hepatocellular carcinoma (HCC) is missing. METHODS: Here, we employed systems biology and biological network analyses to reveal key roles of genes associated with redox metabolism in HCC by integrating multi-omics data. FINDINGS: We found that several redox genes, including 25 novel potential prognostic genes, are significantly co-expressed with liver-specific genes and genes associated with immunity and inflammation. Based on an integrative analysis, we found that HCC tumors display antagonistic behaviors in redox responses. The two HCC groups are associated with altered fatty acid, amino acid, drug and hormone metabolism, differentiation, proliferation, and NADPH-independent vs -dependent antioxidant defenses. Redox behavior varies with known tumor subtypes and progression, affecting patient survival. These antagonistic responses are also displayed at the protein and metabolite level and were validated in several independent cohorts. We finally showed the differential redox behavior using mice transcriptomics in HCC and noncancerous tissues and associated with hypoxic features of the two redox gene groups. INTERPRETATION: Our integrative approaches highlighted mechanistic differences among tumors and allowed the identification of a survival signature and several potential therapeutic targets for the treatment of HCC. Elsevier 2018-12-31 /pmc/articles/PMC6412169/ /pubmed/30606699 http://dx.doi.org/10.1016/j.ebiom.2018.12.057 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research paper Benfeitas, Rui Bidkhori, Gholamreza Mukhopadhyay, Bani Klevstig, Martina Arif, Muhammad Zhang, Cheng Lee, Sunjae Cinar, Resat Nielsen, Jens Uhlen, Mathias Boren, Jan Kunos, George Mardinoglu, Adil Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis |
title | Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis |
title_full | Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis |
title_fullStr | Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis |
title_full_unstemmed | Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis |
title_short | Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis |
title_sort | characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis |
topic | Research paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412169/ https://www.ncbi.nlm.nih.gov/pubmed/30606699 http://dx.doi.org/10.1016/j.ebiom.2018.12.057 |
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