Screening of metabolic markers related to molecular typing of breast cancer based on 1H NMR metabonomics

BACKGROUND: Breast cancer (BC) is a heterogeneous disease classified into 4 molecular subtypes, each with distinct molecular characteristics that influence treatment strategies, clinical outcomes and prognosis. These subtypes are associated with specific changes in cellular metabolism, which may play a crucial role in tumor development and progression. OBJECTIVES: To identify distinctive serum metabolic biomarkers for each molecular BC subtype and to evaluate their associations with estrogen receptor (ER) and human epidermal growth factor 2 (HER2) receptor status, thereby refining molecular classification and informing personalized treatment strategies. MATERIAL AND METHODS: The study utilized the proton nuclear magnetic resonance (1H NMR) metabolomics method to collect serum metabolic profiles from BC patients. Pattern recognition analysis was employed to analyze the metabolic data. Metabolic markers specific to each molecular subtype were selected, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was employed to explore serum metabolic pathway heterogeneity. RESULTS: Distinct metabolic markers were identified for each molecular subtype, demonstrating strong discriminatory power. Additionally, we identified specific serum metabolites whose levels correlate with ER and HER2 expression profiles. The KEGG pathway analysis revealed significant heterogeneity in serum metabolic pathways across different subtypes. CONCLUSIONS: This study demonstrates pronounced metabolic differences across BC subtypes that mirror their distinct molecular profiles and may underlie variations in therapeutic response. These metabolomic insights hold promise for refining tumor classification, improving diagnostic accuracy and guiding more personalized treatment strategies.