[Identification and significance of myeloid-derived suppressor cells in peripheral blood of breast cancer patients].

To investigate the presence, biological features, and clinical significance of myeloid-derived suppressor cells (MDSCs) in breast cancer patients.Eighty-four cases of breast cancer, 37 cases of benign breast tumor and 21 cases of healthy individuals were included in this study. Samples of peripheral blood (2 ml) were collected, and in the breast cancer patients, blood samples were taken both before and after treatment. Flow cytometry using anti-CD11b, CD33, CD14 and HLA-DR antibody was conducted to identify the unique membrane markers of MDSCs, and statistical analysis was performed to explore the relationship between MDSCs and clinical factors. Cell isolation and in vitro assay were used to test T cell function.CD11b(+) CD33(+) CD14(-) MDSCs were present in the blood of breast cancer patients, and these MDSCs were histologically of mononuclear cells. Cell proliferation assay confirmed that MDSCs inhibited proliferation of homologous T cells in vitro. MDSCs levels in patients with breast cancer, benign disease and the health control were (15.93±3.17)%, (8.92±4.42)% and (5.02±2.75)%, respectively, with a statistically significant difference (P<0.001) between breast cancer patients and the other subjects (patients with benign lesions and healthy controls). The expression level of MDSCs in patients with breast cancer was associated with surgical treatment, but not with age, disease stage, lymph node metastasis, ER or PR expression. MDSCs levels were significantly lower in post-operative patients[(7.83±3.78) %] than the (15.37±2.49) % in patients before surgery (P<0.001).The results of this study demonstrate that MDSCs are present in the peripheral blood of breast cancer patients and the level of MDSCs is associated with surgical treatment. Our findings suggest that CD11b(+) CD33(+) CD14(-) MDSCs are likely involved in breast cancer initiation and development, and may become a novel biomarker to facilitate diagnosis and to predict clinical outcomes of breast cancer.