Identification of Potential Biomarkers and Metabolic Changes in the Serum of Breast Lump Patients Among Kelantanese Based on 1H NMR Metabolomics

This case-control study, conducted at the Hospital USM BestARi unit, aimed to identify the serum metabolic fingerprint among individuals with breast lumps and healthy controls, and to discover potential biomarkers. Serum samples from healthy controls, benign breast lump patients, and malignant breast lump patients were analyzed using proton nuclear magnetic resonance spectroscopy (1H NMR). A multivariate data analysis approach was employed, with the OPLS-DA and clustered heat map techniques effectively differentiating between the three groups. The study revealed significant metabolite variations across the groups and proposed D-glucose, glycerol, and glycine as potential biomarkers for breast cancer diagnosis. Metabolic pathways such as alanine, aspartate, glutamate metabolism, and glycine, serine, and threonine metabolism were implicated. The metabolomics approach coupled with multivariate analysis successfully identified key metabolites leading to group separation and suggested altered metabolic pathways. However, further research and integration with other ‘omics’ technologies are necessary for clinical translation.