Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis
Journal article, 2019

© 2019 The Authors 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.

Systems biology

Precision medicine

Hepatocellular carcinoma

Redox metabolism

Liver cancer




Rui Benfeitas

Royal Institute of Technology (KTH)

G. Bidkhori

Royal Institute of Technology (KTH)

B. Mukhopadhyay


M. Klevstig

Sahlgrenska University Hospital

Muhammad Arif

Royal Institute of Technology (KTH)

C. Zhang

Royal Institute of Technology (KTH)

Sunjae Lee

Royal Institute of Technology (KTH)

R. Cinar


Jens B Nielsen

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Mathias Uhlen

Royal Institute of Technology (KTH)

Jan Borén

Sahlgrenska University Hospital

G. Kunos


Adil Mardinoglu

Royal Institute of Technology (KTH)

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

King's College London


2352-3964 (eISSN)

Vol. 40 471-487

Subject Categories

Medical Genetics

Bioinformatics and Systems Biology

Cancer and Oncology





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