Fig 2: Percentage of Th1, Th2, Treg, and Th17 cells in the healthy control and patients with or without aGVHD. The percentages of Th cells in total CD4+T cell numbers were determined by flow cytometry. (A) Representative flow cytometry results. (B) Percentage of CD4+T cell subsets. (C) Cytokines changes in the healthy control and patients with or without aGVHD. Serum levels of Galectin‐9, IFN‐γ, IL‐4, TGF‐β, and IL‐17 were detected with ELISA or CBA. (D) Th1/Th2 and Treg/Th17 ratios. *p < .05; **p < .01. (E) Ratios of TGF‐β/IL‐17 and IFN‐γ/IL‐4. *p < .05, **p < .01. aGVHD, acute graft‐versus‐host disease; CBA, cytometric bead array; ELISA, enzyme‐linked immunosorbent assay; IFN‐γ, interferon‐gamma; IL, interleukin; TGF‐transforming growth factor.

Fig 3: Dynamic alterations in peripheral blood CD4+T cell subsets in patients without aGVHD after transplantation. Percentage of Th1, Th2, Treg, and Th17 cells in patients without aGVHD. The percentages of Th1, Th2, Treg, and Th17 cells in total CD4+T cells were determined by flow cytometry. (A and B) Gating strategy. Treg cell was defined as CD4+CD25hi CD127low. Th1 was defined as CD4+CXCR3+ CCR6−. Th2 was defined as CD4+CXCR3−CCR6−. Th17 was defined as CD4+ CXCR3−CCR6+. (C) Comparisons of the percentages of Th1, Th2, Treg, and Th17 cells in the peripheral blood of the HC, and patients after transplantation. The comparison was performed using a one‐way analysis of variance. Haplo‐HSCT, related HLA‐haploidentical peripheral blood hematopoietic stem cell transplantation; HC, healthy controls. *p < .05; ** p < .01. (D) Serum cytokine levels in patients without aGVHD after transplantation. Serum levels of IFN‐γ, IL‐4, TGF‐β, IL‐17, and Galectin‐9 in the patients from the Haplo‐HSCT group (on Days 30, 45, 60, and 90 after transplantation), as well as in the healthy control (HC) subjects, were detected with ELISA or CBA. *p < .05; ** p < .01. aGVHD, acute graft‐versus‐host disease; CBA, cytometric bead array; ELISA, enzyme‐linked immunosorbent assay; IFN‐γ, interferon‐gamma; IL, interleukin; TGF‐transforming growth factor.

Fig 4: Gene expression profiles, functional analysis, and expression analysis of key proteins in PI3K/AKT/mTOR pathway in CD4+T cell subsets. (A) Volcano plot of differentially expressed genes between patients with or without aGVHD. (B) GO analysis of differentially expressed genes. (C) KEGG analysis of differentially expressed genes. (D) Gene Set Enrichment Analysis (GSEA) was used to analyze the signaling pathways (PI3K/AKT/mTOR signaling pathway) enrichment in different groups. (E) PI3K/AKT/mTOR pathway protein expression in the peripheral blood was measured by western blot. Compared with the control group, *p < .05, **p < .01; Compared with aGVHD(+) group, & p < .05, && p < .01. (F) Correlation analysis in patients without aGVHD. Data were analyzed with Spearman correlation analysis. (G) Galectin‐9 downregulates p‐PI3K in the Tim‐3+CD4+T cells in vitro. Tim‐3+CD4+T cells from patients with aGVHD were treated with or without rhGalectin‐9 for 48 h. The levels of p‐PI3K were determined by western blot. Compared with the PBS group, *p < .05, **p < .01. Compared with the Galectin‐9 + IgG group, △p < .05, △△p < .01; Compared with Galectin‐9 + RAPA group, & p < .05, & & p < .01. (H) Analysis of IFN‐γ, IL‐4, IL‐17, and TGF‐β secretion by Tim‐3+CD4+T cells in vitro. Levels of IFN‐γ, IL‐4, IL‐17, and TGF‐β in culture supernatant were detected by ELISA. Compared with the PBS group, *p < .05, **p < .01. Compared with the Galectin‐9 + IgG group, △p < .05, △△p < .01; Compared with the Galectin‐9 + RAPA group, & p < .05, & & p < .01. aGVHD, acute graft‐versus‐host disease; CBA, cytometric bead array; ELISA, enzyme‐linked immunosorbent assay; GO, Gene Ontology; IFN‐γ, interferon‐gamma; IL, interleukin; KEGG, Kyoto Encyclopedia of Genes and Genomes; PBS, phosphate‐buffered saline; TGF‐transforming growth factor.

Fig 5: Identification of galectin-3 as a target of mast cell Sirt6.a, b mRNA levels (a, n = 6 per group) in EAT tissues and protein levels (b, n = 6 per group) in plasma for galectin-1, galectin-3 and galectin-9 in WT and KO mice. c Heatmap displaying the ligand-receptor signaling network of the galectin pathway between immune cell types from WT and KO mice. Each cell in the heatmap represents the predicted communication probability from a sender to a receiver cell type. The bar plot above the heatmap quantifies the total outgoing signaling strength of each cell type, while the bar plot to the right reflects the total incoming signaling strength. TCP, total communication probability. d Bone marrow-derived mast cells (BMMCs) were transfected with control siRNA (siCtrl) or Sirt6 siRNA (siSirt6). Successful Sirt6 silencing was confirmed by qPCR and western blotting (n = 6 per group). e–i Lgals3 and Lgals9 mRNA levels (e, n = 6 per group), RELA (p65 subunit of NF-κB) binding to the promoters of Lgals3 and Lgals9 (f, n = 5 per group), Sirt6 binding to the promoters of Lgals3 and Lgasl9 (g, n = 5 per group), enrichment of Ac-H3K9 on the Lgals3 and Lgals9 promoters (h, n = 4 per group), and acetylation of H3K9 (i, n = 3 per group) were compared between control and Sirt6 silenced BMMCs. j, k. Plasma levels of galectin-3 and galectin-9 in human subjects were measured by ELISA (n = 24 for lean, n = 14 for overweight, n = 6 for obese). A scatter plot was created to examine the correlation between mast cell Sirt6 protein levels and plasma galectin-3 and galectin-9 levels. Values are presented as mean ± SD. Unpaired two-tailed t test between the two groups (a, b, d, e, i), one-way ANOVA followed by Sidak’s multiple comparisons analysis (j, k) and two-way ANOVA followed by Bonferroni’s post hoc analysis were conducted for statistical analyses (f–h). Pearson correlation coefficients were calculated between continuous variables in two-sided distributions (j, k). Source data are provided as a Source Data file.