Genome-Scale Metabolic Modeling Identifies Synergistic Metabolites that Enhance 5-Fluorouracil Efficacy in Colon...

Area of Science:

• Metabolic Engineering
• Cancer Metabolism
• Drug Discovery

Background:

• Colon cancer (CRC) poses a significant mortality risk.
• Standard chemotherapy like 5-FU has limited efficacy due to resistance and toxicity.
• Novel strategies are needed to enhance CRC treatment outcomes.

Purpose of the Study:

• To identify metabolites that can synergize with 5-FU to improve its efficacy in colorectal cancer (CRC).
• To explore the potential of amino acid co-supplementation as a therapeutic strategy for CRC.
• To utilize Genome-scale Metabolic (GEM) modeling for predicting synergistic metabolites.

Main Methods:

• Genome-scale Metabolic (GEM) modeling was applied using the FVSEOF algorithm.
• Context-specific metabolic models were built from TCGA data using ftINIT.
• Candidate metabolites were identified via simulation of Thiamine pyrophosphate (TS) inhibition and validated experimentally in CRC cells and normal fibroblasts.

Main Results:

• Aspartate, lysine, and valine were identified as candidate synergistic metabolites.
• Lysine and valine demonstrated significant synergy with 5-FU in HT-29 CRC cells.
• These amino acids showed reduced effects in normal fibroblasts, indicating targeted efficacy.

Conclusions:

• Amino acid co-supplementation, specifically with lysine and valine, can enhance 5-FU efficacy in CRC.
• This approach offers a potential strategy to improve CRC therapy with reduced toxicity.
• This study is the first to use GEM for systematic prediction of 5-FU synergistic metabolites in CRC.