Modularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinoma

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dc.citation.firstpage15015
dc.citation.issueNumber19
dc.citation.journalTitleOncotarget
dc.citation.lastpage15026
dc.citation.volumeNumber9
dc.contributor.authorYe, Fengdan
dc.contributor.authorJia, Dongya
dc.contributor.authorLu, Mingyang
dc.contributor.authorLevine, Herbert
dc.contributor.authorDeem, Michael W.
dc.date.accessioned2018-07-16T21:54:26Z
dc.date.available2018-07-16T21:54:26Z
dc.date.issued2018
dc.description.abstractAbnormal metabolism is an emerging hallmark of cancer. Cancer cells utilize both aerobic glycolysis and oxidative phosphorylation (OXPHOS) for energy production and biomass synthesis. Understanding the metabolic reprogramming in cancer can help design therapies to target metabolism and thereby to improve prognosis. We have previously argued that more malignant tumors are usually characterized by a more modular expression pattern of cancer-associated genes. In this work, we analyzed the expression patterns of metabolism genes in terms of modularity for 371 hepatocellular carcinoma (HCC) samples from the Cancer Genome Atlas (TCGA). We found that higher modularity significantly correlated with glycolytic phenotype, later tumor stages, higher metastatic potential, and cancer recurrence, all of which contributed to poorer prognosis. Among patients with recurred tumors, we found the correlation of higher modularity with worse prognosis during early to mid-progression. Furthermore, we developed metrics to calculate individual modularity, which was shown to be predictive of cancer recurrence and patientsﾒ survival and therefore may serve as a prognostic biomarker. Our overall conclusion is that more aggressive HCC tumors, as judged by decreased host survival probability, had more modular expression patterns of metabolic genes. These results may be used to identify cancer driver genes and for drug design.
dc.identifier.citationYe, Fengdan, Jia, Dongya, Lu, Mingyang, et al.. "Modularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinoma." <i>Oncotarget,</i> 9, no. 19 (2018) Impact Journals: 15015-15026. https://doi.org/10.18632/oncotarget.24551.
dc.identifier.doihttps://doi.org/10.18632/oncotarget.24551
dc.identifier.urihttps://hdl.handle.net/1911/102446
dc.language.isoeng
dc.publisherImpact Journals
dc.rightsThis is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/
dc.subject.keywordmodularity
dc.subject.keywordmetabolism
dc.subject.keywordhepatocellular carcinoma
dc.subject.keywordHCC
dc.subject.keywordprognosis
dc.titleModularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinoma
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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