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Tumor-infiltrating lymphocytes are associated with the response to neoadjuvent chemotherapy and prognosis in breast cancer. However, the distribution, interaction and prognostic value of tumor‑infiltrating T cells, the main component of the tumor microenvironment, have seldom been reported. In the present study, surgical specimens of 72 breast cancer patients were analyzed. Tumor‑infiltrating T cell subsets [cluster of differentiation (CD)4+T, CD8+T and regulatory T cells] and expression of their cytokines [interferon‑γ, interleukin (IL)‑4, and IL‑17] were evaluated by flow cytometry. These parameters together with The Cancer Genome Atlas database were used to demonstrate the distribution, interaction and prognostic value of tumor‑infiltrating T cells in breast cancer. Tumor‑infiltrating lymphocytes were closely associated with histological grade (P=0.03), estrogen receptor status (P=0.006), human epidermal growth factor receptor 2 status (P=0.047) and molecular subtype in breast cancer (P=0.012). The gene expression of CD4, CD8A and forkhead box protein P3 in the tumor was increased compared with healthy breast tissue, and was positively associated with the prognosis of breast cancer patients. HER2+ and triple‑negative breast cancer exhibited a significantly increased percentage of CD4+T cells (P=0.01) and regulatory T cells (P=0.035), and a decreased percentage of CD8+T cells (P=0.006) compared with the luminal subtype. Furthermore, the regulatory T cell number was positively correlated with CD8+T cell number in tumors (R=0.7, P=1.5x10‑162) and significantly inhibited the cytokine secretion of T cells. These results reveal the distribution and interaction of tumor‑infiltrating T cell subsets, and indicate that CD8+T cells and regulatory T cells may be used as reliable predictors of prognosis in breast cancer.
Pubmed ID: 30221739
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A portal that provides visualization, analysis and download of large-scale cancer genomics data sets.
View all literature mentionsSoftware for single-cell flow cytometry analysis. Its functions include management, display, manipulation, analysis and publication of the data stream produced by flow and mass cytometers.
View all literature mentionsWeb server for cancer and normal gene expression profiling and interactive analyses. Interactive web server for analyzing RNA sequencing expression data of tumors and normal samples from TCGA and GTEx projects, using standard processing pipeline. Provides customizable functions such as tumor or normal differential expression analysis, profiling according to cancer types or pathological stages, patient survival analysis, similar gene detection, correlation analysis and dimensionality reduction analysis.
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