Elevated profiles of peripheral Th22, Th17, Th2 cells, and decreased percentage of Th1 cells in breast cancer patients

BACKGROUND: Th22 subset is a particular type of CD4(+) T helper cells subset. Our study aimed to explore the expression level of circulating Th22, Th17, Th1, and Th2 cells and the possible mechanism of these cells in breast cancer (BC) with different pathological features. METHODS: Our study enrolled 43 newly diagnosed BC patients and 30 healthy controls. Frequencies of peripheral Th22, Th17, Th1, and Th2 cells were tested by flow cytometry. Concentrations of IL‐22 cytokine in plasma were examined by enzyme‐linked immunosorbent assay (ELISA). Real‐time PCR was done to test aromatic hydrocarbon receptor (AHR) and RAR‐associated orphan receptor C (RORC) gene expression. RESULTS: Frequencies of Th22, Th17, Th2 subsets, and the plasma IL‐22 level was obviously higher in the BC patients. A positive correlation between Th22 frequency and IL‐22 concentration in plasma was detected in BC patients. Furthermore, the percentage of Th22, Th2 subsets in peripheral blood of HER2 positive BC was higher than that in HER2 negative BC patients. A negative correlation between Th1 subset and Ki‐67% as well as a positive correlation between Th2 subset and Ki‐67% was found in BC patients. The proportion of Th1 cells in BC patients was significantly lower than that of the control group. Expression of AHR and RORC transcription factors were also observed to be upregulated in the BC patients. Furthermore, Th22 cells were positively correlated with BC tumor stage and clinical outcomes. The BC patients with a higher percentage of Th22, Th17, Th1 cells or a lower percentage of Th1 cells showed a decreased trend of survival rate. CONCLUSION: Th22, Th17, Th1, and Th2 subsets may play an essential role in BC patients. Th22, Th17, Th1, and Th2 cells may have potential significance to be used as clinical markers in BC patients with different molecular classification. Th22 cells may have potential value in BC patients’ outcomes prediction, providing clinical value.