Additional file 1 of Low expression of ALOX15B modulates immunosuppressive tumor microenvironment in diffuse large B-cell lymphoma via the TAP1/MHC-I axis

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Authors: Li Wang, Jiaying Liu, Yucui Shang, Lanxin Zhang, Muchen Zhang, Di Fu, Siyao Cheng, Pengpeng Xu, Eurydice Anegeli, Guilhem Bousquet, Ying Fang, Ying Liu
+1 more Wei-Li Zhao
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Abstract

Supplementary Material 1: Supplementary Figure S1. Flowchart of patient selection and analysis. This flowchart outlines the process of patient selection and analysis in the study. A total of 360 patients with bulk-RNA sequencing data were included. These patients were categorized into two groups based on their treatment regimen: R-CHOP cohort (n=329) and CR-CHOP cohort (n=31). Supplementary Figure S2. Analysis of genes located on the 17p.13 region. (A) Scatter plot showing the relationship between gene expression levels and PFS for 195 genes located on the 17p.13 region. The genes ALOX15B, TAX1BP3, MYH8, KIF1C, and PITPNM3 are highlighted in red, indicating that their low expression levels are significantly associated with PFS, based on the log2 (fold change) and −log10 (p-value). (B) Table presenting the area under the curve (AUC) values for the genes ALOX15B, TAX1BP3, MYH8, PITPNM3, and KIF1C, along with standard error and asymptotic significance. (C) Box plot comparing the mRNA expression levels of ALOX15B in patients with and without the 17p deletion (17p-). The expression levels of ALOX15B are shown for 17p- (n=21) and non-17p- (n=332) groups, with no significant difference (p=0.583). Supplementary Figure S3. Identification of distinct cell types within the tumor microenvironment of patients with diffuse large B-cell lymphoma. (A) Density plot depicting the expression of marker genes across different cell types. (B) Proportions of each cell type in patients grouped by different ALOX15B expression levels. (C) t-SNE plot showing the distribution of B cells across various samples. (D) Heatmap representing copy number variations (CNVs) for each B cell subcluster (reference: cluster B11; red indicates amplifications, blue indicates deletions). (E) Proportion of malignant B cells within the total B cell population across patients with different ALOX15B groups. Supplementary Figure S4. Analysis of T cells and myeloid cells in the tumor microenvironment. (A) t-SNE plot illustrating the distribution of T cells across different subclusters. (B) Dot plot showing the expression of marker genes for T cell subclusters. (C) Proportions of CD4+ and CD8+ T cell subclusters in patients classified by different ALOX15B expression levels. (D) t-SNE plot depicting the distribution of myeloid cells across various subclusters. (E) Density plot of marker gene expression in different myeloid subclusters. (F) Proportions of myeloid subclusters in patients with different ALOX15B groups. Supplementary Figure S5. Analysis of TAP1 expression and its correlation with MHC-I expression in CD8+ T cells. (A) Box plot showing the mRNA expression of TAP1 in patients with low and high ALOX15B expression. (B) Correlation analysis between TAP1 expression in malignant B cells and MHC-I expression in CD8+ T cells for three HLA subtypes: (left) HLA-A, (middle) HLA-B, and (right) HLA-C. Supplementary Figure S6. Immune cell identification and analysis of TAP1 regulation. (A) Dot plot showing the normalized expression of various genes across different cell types. The size of the dots indicates the percentage of cells expressing each gene, while the color intensity represents the normalized expression level of each gene. (B) Stacked bar plot showing the relative abundance of different cell types in shRen and shAlox15b conditions. (C) Dot plot showing the expression of various genes across subtypes of CD8 T cells, CD4 T cells, Th17 cells, and other immune cells. The size of the dots indicates the percentage of cells expressing each gene, and the color represents the average expression level. (D) UMAP (Uniform Manifold Approximation and Projection) plot showing the clustering of different T cell subtypes, including CD4 and CD8 subsets, Th17, and CD4 Treg cells. (E) Violin plot showing the mRNA expression of Tap1 in Ren and shAlox15b murine models. (F) Bar chart depicting the relative luciferase activity of the TAP1 promoter in DB and U2932 cell lines with either a vector or siALOX15B. (G) Violin plots showing MHC-I expression in CD8+ T cells for following subtypes: H2-Q4, H2-Q6, and H2-Q7 in Ren and shAlox15b groups. (H) ChIP-seq analysis from a public Gene Expression Omnibus data (GSE137666) showing Hdac1 and Hdac2 binding at the Alox15b locus, with input control shown at the bottom. (I) Stacked bar plot showing the relative abundance of different cell types in vehicle and Tuci-treated groups. (J) Violin plot showing the mRNA expression of TAP1 in shAlox15b murine models under Tuci trearment. Supplementary Figure S7. Tucidinostat restores ALOX15B expression and enhances the Tap1/MHC-I axis both in vitro and in vivo. (A) qRT-PCR analysis of TAP1, HLA-A, HLA-B, and HLA-C mRNA expression in lymphoma cell lines DB and U2932 treated with Tuci or untreated control. (B) Immunoblot analysis showing increased TAP1 and HLA-ABC protein levels following Tuci treatment in siALOX15B lymphoma cell lines DB and U2932. (C-D) Immunoblot analysis of TAP1 and HLA-ABC expression in subcutaneous tumor tissues from xenograft models in the indicated groups (shRen, shAlox15b, and shAlox15b + Tuci), with three replicates per group. (E) qRT-PCR and immunoblot showing increased ALOX15B expression in lymphoma cell lines DB and U2932 following Tuci treatment. (F) qRT-PCR and immunohistochemical staining demonstrating upregulation of ALOX15B in tumor tissues from PDX models treated with Tuci compared with untreated controls (n = 10 per group). Scale bar, 50 μm. Data are presented as mean ± SEM. Supplementary Figure S8. Survival analysis of ALOX15B expression in CR-CHOP cohort. (A-B) PFS (A) and OS (B) of patients in the CR-CHOP cohort categorized by high (n = 19) and low (n = 12) ALOX15B expression.

Fields of Study & Subjects

Lymphoma Diagnosis and Treatment T-cell and B-cell Immunology Cancer Immunotherapy and Biomarkers

Publication details

Journal / source
Figshare
Publication date
1 January 2026
Language
EN