Fig 2: Representative images for H&E of lungs are shown for control, granuloma, granuloma treated with MIA602 and granuloma treated with methylprednisolone (a). Percentage differences of lung-stained cells for different markers (CD30, CD68, PD-1 and PD-L1) between challenged mice and controls (b). Control mice (three mice) were not challenged, while granuloma (four mice) and MIA602 (three mice) groups were challenged with MAB microparticles. Mice in the MIA602 group received 5 µg MIA602 daily subcutaneous injection, while granuloma and control groups only received saline. The percentage of the involved area of the immunohistochemistry was evaluated by two lung pathologists separately. Data are from one experiment that is representative of three separate experiments.

Fig 3: Pan-cancer analysis of RBCK1 mRNA differential expression and correlation analysis of the tumor immune microenvironment. (A) The expression distribution of RBCK1 in tumor and normal samples from the TCGA database and GTEx Portal, where the horizontal axis represents different tumor tissues, and the vertical axis represents the gene expression distribution using the Wilcoxon test (*p < 0.05, **p < 0.01, ***p < 0.001). (B) Spearman correlation analysis heatmap of immune score and RBCK1 expression in over 13,000 pan-cancer tissues, where the horizontal axis represents different tumor tissues, and the vertical axis represents different immune scores. The stronger the correlation, the darker the color. (C) The heatmap represents the correlation between RBCK1 expression and immune checkpoints (SIGLEC15, IDO1, CD274, HAVCR2, PDCD1, CTLA4, LAG3, and PDCD1LG2) in pan-cancer tissues, where the horizontal axis represents different immune checkpoint genes, and the vertical axis represents different tumor tissues (*p < 0.05, **p < 0.01, ***p < 0.001).

Fig 4: Immunopreventive blockade of IL-1ß modulates the TME to an antitumor immune phenotype.(A) Representative flow cytometry analysis of CD8+ T cells and percentage of CD8+ T cells in the whole lung (n = 5). (B) Representative flow cytometry analysis of CD3+ programmed cell death 1–positive (PD-1+) T cells and percentage of CD3+PD-1+ T cells in the whole lung (n = 3–4). (C) Representative flow cytometry analysis of regulatory Tregs and percentage of Tregs in the whole lung (n = 4–5). (D–F) Relative mRNA expression of (D) Cd8a, (E) Gzmb, and (F) Pdcd1 in the whole lung, normalized to Cd45 or Actb expression (n = 7–9). (G and H) MFI of (G) IFN-? and (H) granzyme B measured by multiplex ELISA in IgG or anti–IL-1ß Ab–treated mice (n = 7–8). (I) Representative photomicrographs and (J) quantification of IF staining with anti-CD8a (red) and DAPI (blue) in tumor lesions (left top and bottom: original magnification, ×20, scale bar: 50 µm; right top and bottom: ×40, scale bar: 20 µm.) n = 7–8. (K) Correlation between IL1B expression and infiltration of CD8+ T cells in LUAD (n = 535). (L) Correlation between IL1B expression and PDCD1 expression in LUAD (n = 535). (M) Correlation between IL1B expression and PDCD1 expression in KM-LUAD (n = 139). Data represent mean ± SEM. *P < 0.5 by unpaired t test. a IL-1ß, anti–IL-1ß; TPM, transcript count per million.

Fig 5: Reduced number of T cells in non-tumoural regions in b16 melanoma bearing Gsk-3b cKO(A–D) Immunohistochemistry of lung tissue sections from B16 tumor bearing mice. Non-tumor areas are shown following staining for (A) CD4+, (B) CD8+, (C) PD1+ and (D) FOXP3+ expression. End panels depict number of positive cells quantified from 5 different areas using ImageScope Software.Data are representative of two independent experiments. Groups compared using unpaired t test. ***p < 0.0001; **p < 0.001; *p < 0.01; ns, no significant difference relative to controls.