Fig 2: Regulatory T cells accumulate in ovarian cancer ascites. Frequencies of regulatory T cells were analysed by flow cytometry of peripheral blood mononuclear cells (PBMC) and ascites from patients with ovarian cancer (OC) compared to PBMC from healthy donors (HD). Tregs were gated as CD25hi CD127low/neg cells out of total live CD3+ CD4+ T cells. A) Representative dot plots of CD25hi CD127low/neg gating from HD PBMC, OC PBMC and OC Ascites respectively. B) Representative histograms of FoxP3 and CCR4 MFI of Tregs from OC ascites show a higher expression of FoxP3 and CCR4 compared to Tregs from HD PBMC and OC PBMC. C) Percentages of FoxP3+ Tregs and D) percentage of CCR4+ FoxP3+ Tregs in HD, OC PBMC and OC ascites. HD PBMC n = 13, OC PBMC n = 14, OC Ascites n = 13, Unpaired t-test, error bars designate mean with SEM, *P < 0.05, **P < 0.01, *** P < 0.001.

Fig 3: In vivo immunotherapy efficacy of Hb@Hf-Ce6 NPs mediated RT-RDT combined with anti-PD-1 antibody. a) Respective proportion of total macrophages (left column) and M2 phenotype macrophages (right column) in distant tumors. b) Respective proportion of CD4+ T cells (left column) and CD8+ T cells (right column) in distant tumors. c) Representative flow cytometry plots of CD4+ T cells and CD8+ T cells in distant tumors from six groups of mice. d) Respective proportion of regulatory T cells (CD3+, CD4+, Foxp3+) in distant tumors. e) Respective proportion of effector T cells (CD3+, CD8+, IFN? +) in distant tumors. f) Respective proportion of memory T cells (CD3+, CD8+, CD62Llow, CD44high) in spleen. g–k) Cytokine levels of TNF-a, IFN-?, IL-6, IL-12p70, and IL-10 in serum from mice after various treatments. l) Schematic showed the potential mechanism of Hb@Hf-Ce6 NPs mediated RT-RDT-Immunotherapy for immune response activation to inhibit both primary and distant tumors. Briefly, Hb@Hf-Ce6 NPs accumulated at the tumor site through blood circulation. After X-ray irradiation on the primary tumor, Hb@Hf-Ce6 NPs can not only enhance the RT effect but also activate Ce6 with the assistance of radioluminescence by RDT to generate more ROS. The necrosis tumors in situ activated adaptive and innate immunity and caused a significant proinflammatory response. Furthermore, the anti-PD-1 antibody enhanced the immune response. Activated immunotherapy triggered both primary and distant tumor eradication and initiated the memory T cells generation to produce long-term antitumor efficacy. Data are presented as mean values ± SD (n = 4).

Fig 4: Manipulation of colonic microbiota density alters host physiology.(A) Pharmacologic interventions differentially alter microbiota density in SPF C57BL/6J mice. Samples from 3 to 12 (mean = 6) mice per group. (B–E) Antibiotic-induced changes in microbiota density significantly correlate with (B) host cecum size, (C) adiposity, (D) fecal IgA, and (E) colonic lamina propria FoxP3 +T regulatory cells. n = 6 mice per antibiotic group, 9 SPF antibiotic-free controls, and six germ-free controls. In (A), dashed lines represent the IQR of untreated SPF C57BL/6J mice and AVNM = ampicillin, vancomycin, neomycin, metronidazole. Statistical tests performed for individual treatment conditions vs untreated using Kruskal-Wallis with Dunn’s post-test corrected for multiple comparisons with the Bonferonni correction. Bars indicate median. ns = not significant, *p < 0.05, **p < 0.01, and ***p < 0.001. In (B-E) points represent individual mice. Shapes indicate treatment group. Source data available for (A-E). 16S rRNA gene amplicon sequencing data is available for A (see Materials and methods).10.7554/eLife.40553.013Figure 2—source data 1.Microbiota density of mice treated with pharmacologics.Contains source data for Figure 2A. Timepoint in relative terms (not days).10.7554/eLife.40553.014Figure 2—source data 2.Microbiota density and phenotypic changes in antibiotic-treated mice.Contains source data for Figure 2B–2E and Figure 2—figure supplement 3A–3E.10.7554/eLife.40553.015Figure 2—source data 3.Fecal water content of mice diets with varied fiber sources and protein content.Contains source data for Figure 2—figure supplement 4A and C.10.7554/eLife.40553.016Figure 2—source data 4.Fecal water content of mice diets with varied fiber sources and protein content.Contains source data for Figure 2—figure supplement 4B and D.

Fig 5: SRSF1 is essential for survival of Treg cells(A) Plots show gating strategies and CD4+CD25+Foxp3+ Treg cells in spleen, MLN, and PLN from WT and Treg Srsf1-KO mice.(B) Graphs show frequencies of CD4+CD25+Foxp3+ Treg cells (spleen: n = 5 each; MLN and PLN: n = 4 each).(C) Naive CD4 T cells were isolated from pooled spleen and PLN cells from WT and Treg Srsf1-KO mice and cultured under Treg differentiation conditions. Cells were collected and analyzed by flow cytometry on days 1–3. Plots show 7AAD and Annexin V staining.(D) Graph shows the percentage of early apoptotic (7AAD-Annexin V+) cells among CD4 T cells (n = 3–6).*p < 0.05, **p < 0.005, and ***p < 0.0005, unpaired t test (B) or one-way ANOVA with Tukey’s multiple comparisons test (D); mean ± SEM.