Cancer cells adapt their metabolism to achieve the requirements of uncontrolled proliferation, survival, and long-term maintenance. Serine, glycine, and one carbon (SGOC) metabolism integrates nutritional status from amino acids, glucose and vitamins, and generates diverse outputs, such as the biosynthesis, the maintenance of redox status and the substrates for methylation reactions. We have recently found that cancer cells divert a relatively large amount of flux from glucose into de novo serine metabolism leading to the deregulation of one carbon metabolism. Here we will build upon findings we have made that have identified newfound roles for one carbon metabolism in cancer pathogenesis. We will carry out an integrated computational and experimental analysis to investigate the diversity of functions within the metabolic network involving one carbon metabolism in cancer.
In aim 1, we will characterize the serine and one carbon gene expression network in tumor tissues. We reconstruct the network of genes that encode enzymes that metabolize serine. We will overlay TCGA data onto the serine metabolic network to assess its expression in cancer. We will analyze the cancer context of the network by comparing expression of network components across normal tissues, different cancer tissues, histological subtypes, and mutational statuses.
In aim 2, we will carry out a flux analysis and metabolomics of one carbon metabolism in cancer cells. We will capitalize on a metabolomics platform our lab has developed and we have developed a method for 13C serine flux analysis. We will expand on these methods and then exploit these capabilities to measure the diversity of serine flux across different cancer cells.
I aim 3, we will evaluate the relationship between one carbon metabolism and anti-metabolite chemotherapy. We will consolidate our findings and relate them in the context of clinically available pharmacological agents that target enzymes in the SGOC network. We will next model the metabolomics response of cells treated with different agents.

Public Health Relevance

The serine, glycine and one carbon metabolic network (SGOC) integrates inputs in the form of nutrients and outputs diverse metabolic functions ranging from biosynthesis, redox maintenance, and cellular epigenetic maintenance. Aberrant activity of this network is implicated in cancer pathogenesis. We will carry out an integrated genomic and metabolomic analysis to study the contextual dependencies of the metabolic function and targetable liabilities within the network.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA193256-01A1
Application #
8984388
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Knowlton, John R
Project Start
2015-08-14
Project End
2020-07-31
Budget Start
2015-08-14
Budget End
2016-07-31
Support Year
1
Fiscal Year
2015
Total Cost
$358,261
Indirect Cost
$129,511
Name
Duke University
Department
Pharmacology
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Reid, Michael A; Allen, Annamarie E; Liu, Shiyu et al. (2018) Serine synthesis through PHGDH coordinates nucleotide levels by maintaining central carbon metabolism. Nat Commun 9:5442
Liu, Xiaojing; Cooper, Daniel E; Cluntun, Ahmad A et al. (2018) Acetate Production from Glucose and Coupling to Mitochondrial Metabolism in Mammals. Cell 175:502-513.e13
Gao, Xia; Lee, Katie; Reid, Michael A et al. (2018) Serine Availability Influences Mitochondrial Dynamics and Function through Lipid Metabolism. Cell Rep 22:3507-3520
Dai, Ziwei; Mentch, Samantha J; Gao, Xia et al. (2018) Methionine metabolism influences genomic architecture and gene expression through H3K4me3 peak width. Nat Commun 9:1955
Dai, Ziwei; Locasale, Jason W (2018) Thermodynamic constraints on the regulation of metabolic fluxes. J Biol Chem 293:19725-19739
Hwang, Inah; Oh, Hwanhee; Santo, Evan et al. (2018) FOXO protects against age-progressive axonal degeneration. Aging Cell 17:
Mehrmohamadi, Mahya; Jeong, Seong Ho; Locasale, Jason W (2017) Molecular features that predict the response to antimetabolite chemotherapies. Cancer Metab 5:8
Reid, Michael A; Dai, Ziwei; Locasale, Jason W (2017) The impact of cellular metabolism on chromatin dynamics and epigenetics. Nat Cell Biol 19:1298-1306
Salerno Jr, Stephen; Mehrmohamadi, Mahya; Liberti, Maria V et al. (2017) RRmix: A method for simultaneous batch effect correction and analysis of metabolomics data in the absence of internal standards. PLoS One 12:e0179530
Cluntun, Ahmad A; Lukey, Michael J; Cerione, Richard A et al. (2017) Glutamine Metabolism in Cancer: Understanding the Heterogeneity. Trends Cancer 3:169-180

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