Cancer recurrence and omics: metabolic signatures of cancer dormancy revealed by transcriptome mapping of genome-scale networks

Kutay, Merve and Gözüaçık, Devrim and Çakır, Tunahan (2022) Cancer recurrence and omics: metabolic signatures of cancer dormancy revealed by transcriptome mapping of genome-scale networks. OMICS A Journal of Integrative Biology, 26 (5). pp. 270-279. ISSN 1536-2310 (Print) 1557-8100 (Online)

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A major problem in medicine and oncology is cancer recurrence through the activation of dormant cancer cells. A system scale examination of metabolic dysregulations associated with the cancer dormancy offers promise for the discovery of novel molecular targets for cancer precision medicine, and importantly, for the prevention of cancer recurrence. In this study, we mapped the total mRNA sequencing-based transcriptomic data from dormant cancer cell lines and nondormant cancer controls onto a human genome-scale metabolic network by using a graph-based approach, and two mass balance-based approaches with one based on reaction activity/inactivity and the other one on flux changes. The gene expression datasets were accessed from Gene Expression Omnibus (GSE83142 and GSE114012). This analysis included two diverse cancer types, a liquid and a solid cancer, namely, acute lymphoblastic leukemia and colorectal cancer. For the dormant cancer state, we observed changes in major adenosine triphosphate-producing pathways, including the citric acid cycle, oxidative phosphorylation, and glycolysis/gluconeogenesis, indicating a reprogramming in the metabolism of dormant cells away from Warburg-based energy metabolism. All three computational approaches unanimously predicted that folate metabolism, pyruvate metabolism, and glutamate metabolism, as well as valine/leucine/isoleucine metabolism are likely dysregulated in cancer dormancy. These findings provide new insights and molecular pathway targets on cancer dormancy, comprehensively catalog dormancy-associated metabolic pathways, and inform future research aimed at prevention of cancer recurrence in particular.
Item Type: Article
Uncontrolled Keywords: bioinformatics; cancer dormancy; cancer drug discovery; metabolic network models; preventive medicine; transcriptome
Divisions: Sabancı University Nanotechnology Research and Application Center
Depositing User: Devrim Gözüaçık
Date Deposited: 22 Aug 2022 13:27
Last Modified: 22 Aug 2022 13:27

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