Targeting Subtype-Specific Metabolic Preferences in Nucleotide Biosynthesis Inhibits Tumor Growth in a Breast Cancer Model

Investigating metabolic rewiring in cancer can lead to the discovery of new treatment strategies for breast cancer subtypes that currently lack targeted therapies. In this study, we used MMTV-Myc-driven tumors to model breast cancer heterogeneity, investigating the metabolic differences between two histologic subtypes, the epithelial-mesenchymal transition (EMT) and the papillary subtypes. A combination of genomic and metabolomic techniques identified differences in nucleotide metabolism between EMT and papillary subtypes. EMT tumors preferentially used the nucleotide salvage pathway, whereas papillary tumors preferred de novo nucleotide biosynthesis. CRISPR/Cas9 gene editing and mass spectmmetry-based methods revealed that targeting the preferred pathway in each subtype resulted in greater metabolic impact than targeting the nonpreferred pathway. Knocking out the preferred nucleotide pathway in each subtype has a deleterious effect on in vivo tumor growth, whereas knocking out the nonpreferred pathway has a lesser effect or may even result in increased tumor growth. Collectively, these data suggest that significant differences in metabolic pathway utilization distinguish EMT and papillary subtypes of breast cancer and identify said pathways as a means to enhance subtype-specific diagnoses and treatment strategies. Significance: These findings uncover differences in nucleotide salvage and de novo biosynthesis using a histologically heterogeneous breast cancer model, highlighting metabolic vulnerabilities in these pathways as promising targets for breast cancer subtypes.

Automated summary

This study investigated metabolic differences between histologic subtypes of breast cancer, identifying preferences for different nucleotide metabolism pathways. Targeting the preferred pathways in each subtype had a greater impact on tumor growth, highlighting the potential for subtype-specific treatment strategies based on metabolic vulnerabilities.