Bulletin of the American Physical Society
2018 Joint Fall Meeting of the Texas Sections of APS, AAPT and Zone 13 of the SPS
Volume 63, Number 18
Friday–Saturday, October 19–20, 2018; University of Houston, Houston, Texas
Session P04: Biophysics and Soft Matter III
2:10 PM–3:22 PM,
Saturday, October 20, 2018
Science and Engineering Classroom (SEC) Room: 102
Chair: Lloyd Lumata, University of Texas, Dallas
Abstract ID: BAPS.2018.TSF.P04.1
Abstract: P04.00001 : Modularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinoma*
2:10 PM–2:22 PM
(The Jackson Laboratory)
Abnormal metabolism is an emerging hallmark of cancer. Cancer cells utilize both aerobic glycolysis and oxidative phosphorylation for energy production and biomass synthesis. 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. Furthermore, we developed metrics to calculate individual modularity, which was shown to be predictive of cancer recurrence and patients’ 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.
*Fengdan Ye and Michael Deem are supported by NSF grant PHY-1427654. Dongya Jia is supported by PHY-1427654, DMS-1361411 and PHY-1605817. Herbert Levine is supported by PHY-1427654, DMS-1361411, PHY-1605817 and CPRIT grants R1111. Mingyang Lu is supported by the National Cancer Institute of the National Institutes of Health grant P30CA034196.
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.TSF.P04.1
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