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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
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.
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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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