Comprehensive untargeted serum metabolomics identifies biomarkers and metabolic pathways in breast cancer

Abstract

Background The surge in breast cancer incidence worldwide highlights the urgency of improving diagnostic methods to accurately assess disease progression. This study aimed to elucidate the metabolic characteristics of breast cancer serum and identify differential metabolites for diagnosing breast cancer and assessing its severity, thereby providing a reference for clinical practice. Methods Serum samples from patients with benign and malignant breast lesions and healthy subjects were analyzed using GC-MS. OPLS-DA identified key metabolites distinguishing breast cancer from benign lesions and advanced from early-stage cancer. Spearman's ρ revealed correlations between metabolite levels and disease stages, while the AUC demonstrated the discriminatory capability of key metabolites. Results Amino acid metabolism was significantly altered in breast cancer patients, particularly in alanine, aspartate, and glutamate metabolism. Glutamic acid and lactic acid levels were significantly elevated in breast cancer patients compared to those with benign masses, while fructose levels were markedly reduced. The AUCs for distinguishing benign lesions from breast cancer using glutamic acid, lactic acid, and fructose were 0.9771, 0.9608, and 1.000, respectively. Comparative metabolomic analysis revealed significant differences between early-stage and late-stage malignant breast lesions. Glutamic acid levels increased progressively from healthy individuals to those with benign tumors, early-stage breast cancer, and advanced cancer, showing a strong positive correlation (ρ = 0.937, P < 0.001) with breast cancer progression, and an AUC of 0.9571 for distinguishing late-stage from early-stage breast cancer. Conclusions Our findings demonstrate the relationship between serum metabolite levels and breast cancer occurrence and progression. Further investigations are warranted to elucidate the precise roles of these metabolites.