The analysis of plasma proteomics for hormone receptor-positive HER2-negative breast cancer

Abstract Background Breast cancer (BC) is the prevailing malignancy among women, exhibiting a discernible escalation in incidence within our nation, hormone receptor-positive (HR+) human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most common subtype. In this study, we aimed to search for a non-invasive, specific, blood-based biomarker for the early detection of HR+/HER2- breast cancer through proteomic studies. Methods To explore new potential plasma biomarkers, we applied data independent acquisition (DIA), a technique that combines liquid chromatography with tandem mass spectrometry to quantify breast cancer-associated plasma protein abundance from a small number of plasma samples. Results The proteomes of 30 participants in all cohorts were analyzed using the DIA method, and a total of 517 proteins and 3584 peptides were quantified. We found that there were significant differences in plasma protein expression profiles between breast cancer patients and non-breast cancer patients, and breast cancer was mainly related to lipid metabolism pathways. Finally, the optimal protein combinations for the diagnosis of breast cancer were PON3, IGLV3-10 and IGHV3-73 through multi-model analysis, which had a high prediction accuracy for breast cancer (AUC=0.92), and the model could also distinguish breast cancer from HC (AUC=0.92) and breast cancer from benign breast tumor (AUC=0.91). Conclusions The study revealed proteomic signatures of patients with HR+/HER2- breast cancer, identified multiple differential proteins, and identified three plasma proteins as potential diagnostic biomarkers for breast cancer. It provides a reference for the screening of biomarkers for breast cancer.