Modeling, Targeting Acetyl-CoA Metabolism in Breast Cancer
Creators: name: University Of California Office Of The President
Publisher: name: University of California Office of the President
publisherIdentifier: https://ror.org/00dmfq477
publisherIdentifierScheme: ROR
Year: 2024

description: Tumor cell metabolism is distinct from that of normal cells. Unlike non-transformed cells,
 
 tumor cells stimulate growth through increased glycolysis despite low pH and hypoxic conditions. Hypoxia precipitates overexpression of many genes of glycolysis, ultimately
 
 stimulating key metabolites that may be used as tumor markers. For example, glycolysis drives fatty acid synthesis though a central metabolic precursor, acetyl-CoA.
 
 Increased levels of fatty acid synthase (FAS) in breast cancer tissues indicate poor prognosis and implicate FAS as a possible drug target. Quantitative modeling of the acetyl-CoA metabolic sub-network will elucidate further fundamental distinctions between mammary epithelia and mammary carcinoma regulation and identify novel therapeutic targets in breast cancer.
 
 
 
 
 
 
 
 We propose that hypoxic exposure leads to an increased rate of glycolysis through sequential, quantifiable stimulation of associated enzymes and transcription factors.
 
 Consequently, comprehensive quantification of metabolic flux from glycolysis to fatty acid synthesis in hypoxic mammary carcinoma cells could reveal unexplored critical control points suitable for clinical breast cancer drug development. 
 
 
 
 
 
 
 
 Our aims are:
 
 
 
 #1. Assess metabolic pathways, individual reactions and enzymes, whichcomprise an acetyl-CoA subnetwork in mammary carcinoma cells.
 
 
 
 #2. Build a quantitative metabolic model of the acetyl-CoA sub-network tointerpret and reconcile cancer specific alterations of metabolism in terms ofrespective metabolic fluxes.
 
 
 
 #3. Predict, prioritize, and validate potential therapeutic targets based on acetyl-CoA network modeling.
 
 
 
 
 
 
 
 Mammary carcinoma cell lines will be fed 13C-labeled glucose to construct a flux model of cellular carbon flow. Using both 2D NMR and GC/LC-MS, we will characterize labeling patterns, fluxes and pools of key metabolites involved in up to 50 biochemical reactions spanning the range of glycolysis to fatty acid synthesis. Experimental data will
 
 be coordinated with functional genomics techniques to construct an accurate quantitative model of carbon flux and identify cancer-specific metabolic aberrations. We will select 10–15 potential drug targets based on key distinctions between mammary epithelia and mammary carcinoma metabolic flux. RNAi knockdown will validate potential targets and measure subsequent effects on metabolic flux, growth rate, and cell death.
 
 
 
 
 
 
 
 Discovering molecular marker–based targets is crucial to developing individualized, less toxic breast cancer treatment. This integrative study will be the first to identify novel therapeutic breast cancer targets using 2D NMR and GC/LC-MS techniques to measure metabolite fluxes associated with the hypoxia and glycolytic shift. We propose that unique control points in hypoxia-adapted cells, resulting from increased glycolytic rate through sequential quantifiable stimulation of associated enzymes and transcription factors in the acetyl-CoA pathway, can be identified and validated for therapeutic benefit.