Fig 2: Effects of the absence of T cell-intrinsic MyD88, IL-1R or IL-18R signaling on the proliferation and phenotype of CD4+ and CD8+spleen T cells from infected mixed BM chimeras.(A, C, G, E and I) Mean frequencies and (B, D, F, H and J) absolute cell numbers of: (A and B) BrdU+CD4+ and (C and D) CCR5+CD4+ cells gated on WT CD45.1+ or KO CD45.2+ CD4+ T cells, as in Figure 5A. (E and F) IFN-γ+CD8+ and (G and H) GzB+CD8+ T cells gated on WT CD45.1+ or KO CD45.2+ CD8+ T cells, as shown in Figure 6—figure supplement 3. (I and J) CD44hiCD4+ T cells, gated on WT or KO CD4+ T cells as in Figure 5A. Bars are the mean of individually analyzed mice from one (C, D, I and J) or two combined independent experiments (A, B, E, F, G and H). (n = 3 to 8); error bars = SEM; ND = not done; ns = non significant; *p≤0.05; **p≤0.01; ***p≤0.001, ****p≤0.0001 (two-tailed Student t-test). Gate strategies and representative dot plots are shown in Figure 6—figure supplements 1–5.

Fig 3: c‐Myb promotes immune escape of EAC cells (FLO‐1 cell line) by upregulating the expression of miR‐145‐5p. (A) c‐Myb, SPOP, and PD‐L1 expression in each group detected by Western blot analysis. (B) The expression of c‐Myb, miR‐145‐5p, SPOP, and PD‐L1 in each group detected using qPCR. (C) Tumor size of EAC tumor models in each group. (D) IHC diagrams of CD3 expression in EAC tissues in each group and statistical analysis of IHC scores. (E) IHC diagrams of Granzymes B expression in EAC tissues in each group and statistical analysis of IHC scores. (F) The expression of Fas and FasL in tumor tissues of each group detected by Western blot analysis. (G) The levels of cytokines secreted by T cells in each group detected using ELISA. (H) The proportion of cytokines secreted by Th1 and Th2 cells in each group detected using specific kits. (I) The proportion of CCR5 and CD4 double positive cells detected using flow cytometry. (J) The proportion of CCR3 and CD4 double positive cells assessed using flow cytometry. (K) The proportion of CCR8 and CD4 double‐positive cells assessed using flow cytometry. *P < .05. Measurement data were expressed as mean ± standard deviation. Data in panels A‐E were analyzed by unpaired t‐test, in panels F‐H were analyzed by one‐way ANOVA, and in panels I‐K were analyzed by two‐way ANOVA and Tukey's post‐hoc test

Fig 4: PP2 improved motor symptoms in mice, inhibited Th17 cell differentiation and reduced LFA-1 expression by inhibiting LCK and ZAP70 activation. (A) The timeline of the mouse treatment regimen. (B) Rotarod test. (C) Pole test. (D–H) After PP2 treatment, flow cytometry and FlowJo software were used to analyze peripheral PBMCs from the mice. The proportions of IL-17A+, IL-17A+ and CCR5+, IL-17A+ and LFA-1+, IL-17A+ and pLCK+, IL-17A+ and pZAP70+ cells among CD4+ cell populations were calculated n = 5 per group. Data are presented as the means ± SEMs. *p < 0.05, **p < 0.01, and ***p < 0.001.

Fig 5: PP2 inhibited Th17 cell differentiation and LFA-1 expression in vitro. Naive CD4+ T cells from the spleens of C57BL/6J mice were purified by magnetic beads in vitro and induced to differentiate into Th17 cells. CCL5 and PP2 were used for treatment. After 3 days, flow cytometry and FlowJo software were used to analyze the cells. The proportions of IL-17A+, IL-17A+ and CCR5+, IL-17A+ and LFA-1+, IL-17A+ and pLCK+, and IL-17A+ and pZAP70+ cells among CD4+ cell populations were calculated n = 3 per group. Data are presented as the means ± SEMs. *p < 0.05 and **p < 0.01.