Abstract
BACKGROUND: Aromatase inhibitors-related musculoskeletal syndrome (AIMSS) is a common side effect experienced by early breast cancer patients undergoing endocrine therapy. This condition can result in medication discontinuation and a diminished quality of life. The objective of this study was to characterize AIMSS, investigate its pathogenesis, and identify potential biomarkers at both the protein and metabolic levels. METHODS: We collected peripheral blood samples from 60 women diagnosed with breast cancer undergoing aromatase inhibitor therapy, of whom 30 had AIMSS and 30 did not. The samples were analyzed using four-dimensional data-independent acquisition (DIA)-based proteomics and untargeted metabolomics, employing liquid chromatography-mass spectrometry (LC-MS) on the latest platform. RESULTS: The mean age of participants was 49.2 (11.3) years in the AIMSS group and 50.1 (11.5) years in the non-AIMSS group. There were no statistically significant differences between the two groups in terms of age, BMI, education level, clinical stage, and treatment. In total, we identified 3473 proteins and 1247 metabolites in the samples. The chemokine signaling pathway (p = 0.015), cytokine-cytokine receptor interaction (p = 0.015), complement and coagulation cascades (p = 0.004), neuroactive ligand-receptor interaction (p = 0.004), and the estrogen signaling pathway (p = 0.004) were significant enriched in differentially expressed proteins (DEPs). GnRH secretion (p < 0.001), sphingolipid signaling pathways (p < 0.001), endocrine resistance (p < 0.001), the estrogen signaling pathway (p = 0.001), endocrine and other factor-regulated calcium reabsorption (p = 0.001), dopaminergic synapse (p = 0.003), regulation of lipolysis in adipocytes (p = 0.004), biosynthesis of cofactors (p = 0.004), thyroid hormone synthesis (p = 0.008), aldosterone synthesis and secretion (p = 0.001), taurine and hypotaurine metabolism (p = 0.011), ovarian steroidogenesis (p = 0.011), and the cAMP signaling pathway (p = 0.011) were significantly enriched in differentially expressed metabolites (DEMs). Complement C3 (p = 0.004), platelet factor 4 (p = 0.015), KRT10 (p = 0.004), KRT14 (p = 0.004), beta-estradiol (p = 0.019), testosterone (p = 0.023), sphingosine (p < 0.001), and 1-stearoyl-2-arachidonoyl-sn-glycerol (p = 0.039) could be the monitoring and therapeutic targets for AIMSS. CONCLUSIONS: This study offered new insights into the mechanisms underlying musculoskeletal symptoms associated with aromatase inhibitors. It also highlighted potential biomarkers for predicting and addressing these symptoms in breast cancer patients, paving the way for improved intervention strategies.