Human pregnancy levels of estrogen and progesterone contribute to humoral immunity by activating TFH /B cell axis.

Circulating TFH (cTFH ) cells express CXCR5, PD-1, and, when activated, ICOS, and release IL-21. According to the production of IFN-γ, IL-4, and IL-17 and expression of FoxP3, these cells are also classified as cTFH 1, cTFH 2, cTFH 17, and cTFR cells, respectively. This CD4+ T-cell subset is pivotal to efficient humoral immunity, and pregnancy appears to favor IgG production. Here, not only pregnancy amplified the in vivo production of anti-HBsAg IgG in HBV immunized women, but the frequency of cTFH cells was directly correlated with estradiol levels. In vitro, pregnancy-related dose of 17-ß-estradiol (E2) directly increased the percentage of different cTFH subsets. While E2 and progesterone (P4) increased the proportion of differentiated TFH cells derived from naïve CD4+ T-cells, only E2 amplified the release of IL-21 in those cell cultures. In addition, E2 and P4 increased the proportion of memory B cells and plasma cells, respectively. In SEB-activated B/TFH cell co-cultures, E2, in the presence of P4, increased the production of total IgG. Finally, among the hormones, P4 was stronger in upregulating the percentage of IL-10+ TFR cells. Collectively, our findings suggested that E2 and P4 cooperate in the humoral immune response by favoring the expansion of different cTFH and B cell subsets.

Immune cell infiltration features and related marker genes in lung cancer based on single-cell RNA-seq.

PURPOSE: Immune cells in the immune microenvironment of lung cancer have a great impact on the development of lung cancer. Our purpose was to analyze the immune cell infiltration features and related marker genes for lung cancer. METHODS: Single cell RNA sequencing data of 11,485 lung cancer cells were retrieved from the Gene Expression Omnibus. After quality control and data normalization, cell clustering was performed using the Seurat package. Based on the marker genes of each cell type from the CellMarker database, each cell was divided into G1, G2M, and S phases. Then, differential expression and functional enrichment analyses were performed. CIBERSORT was used to reconstruct immune cell types. RESULTS: Following cell filtering, highly variable genes were identified for all cells. 14 cell types were clustered. Among them, CD4 + T cell, B cell, plasma cell, natural killer cell and cancer stem cell were the top five cell types. Up-regulated genes were mainly enriched in immune-related biological processes and pathways. Using CIBERSORT, we identified the significantly higher fractions of naïve B cell, memory CD4 + T cell, T follicular helper cell, T regulatory helper cell and M1 macrophage in lung cancer tissues compared to normal tissues. Furthermore, the fractions of resting NK cell, monocyte, M0 macrophage, resting mast cell, eosinophil and neutrophil were significantly lower in tumor tissues than normal tissues. CONCLUSION: Our findings dissected the immune cell infiltration features and related marker genes for lung cancer, which might provide novel insights for the immunotherapy of lung cancer.