FOXP1 suppresses immune response signatures and MHC class II expression in activated B-cell-like diffuse large B-cell lymphomas

Abstract

The FOXP1 (forkhead box P1) transcription factor is a marker of poor prognosis in diffuse large B-cell lymphoma (DLBCL). Here microarray analysis of FOXP1-silenced DLBCL cell lines identified differential regulation of immune response signatures and major histocompatibility complex class II (MHC II) genes as some of the most significant differences between germinal center B-cell (GCB)-like DLBCL with full-length FOXP1 protein expression versus activated B-cell (ABC)-like DLBCL expressing predominantly short FOXP1 isoforms. In an independent primary DLBCL microarray data set, multiple MHC II genes, including human leukocyte antigen DR alpha chain (HLA-DRA), were inversely correlated with FOXP1 transcript expression (P<0.05). FOXP1 knockdown in ABC-DLBCL cells led to increased cell-surface expression of HLA-DRA and CD74. In R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone)-treated DLBCL patients (n=150), reduced HLA-DRA (<90% frequency) expression correlated with inferior overall survival (P=0.0003) and progression-free survival (P=0.0012) and with non-GCB subtype stratified by the Hans, Choi or Visco-Young algorithms (all P<0.01). In non-GCB DLBCL cases with <90% HLA-DRA, there was an inverse correlation with the frequency (P=0.0456) and intensity (P=0.0349) of FOXP1 expression. We propose that FOXP1 represents a novel regulator of genes targeted by the class II MHC transactivator CIITA (MHC II and CD74) and therapeutically targeting the FOXP1 pathway may improve antigen presentation and immune surveillance in high-risk DLBCL patients.

Figure 1

FOXP1 depletion and microarray target gene validation in GCB- and ABC-DLBCL cell lines. (a) Venn diagram of the number of genes with ⩾2-fold repression or induction after 48 h FOXP1 silencing in four DLBCL lines. (b) qRT-PCR validation of target gene regulation in an extended panel of FOXP1-silenced DLBCL lines (DB, K422 (Karpas 422), MIEU, SUDHL4, OCI-Ly3, HBL-1, RIVA and U2932), n=3 biological replicates. (c) ChIP assays of FOXP1 binding to CHAC1, LPP, NEIL1 and VNN2 promoter sequences. Anti-FOXP1 antibodies used are as follows: ms Ab, mouse JC12; rb Ab, rabbit Ab16645 (Abcam).

Figure 2

GO enrichment analysis of the biological processes influenced by FOXP1 silencing in GCB- and ABC-DLBCL cells. (a) GO terms enriched in FOXP1-repressed gene sets (that is, genes upregulated by FOXP1 depletion). GO terms significantly enriched in ABC-DLBCL, but not in GCB-DLBCL, cells include MHC II complexes, regulation of immune responses and leukocyte activation. (b) GO terms enriched in FOXP1-induced gene sets (that is, genes downregulated by FOXP1 depletion). Both GCB- and ABC-DLBCL cells share GOs related to cell movement. The graphs were plotted on a negative log₁₀ scale (higher −log₁₀ value denotes more significant false discovery rate (FDR) value) and the actual linear FDR values are shown next to each bar.

Figure 3

Heat maps and scatter plots illustrating differential expression of MHC class II and other genes in FOXP1-depleted DLBCL cell lines. (a) Heat map showing differential expression of genes between ABC- and GCB-DLBCL cells involved in the MHC II protein complex and immune response (upregulated in FOXP1-depleted ABC-DLBCL cells) or metabolic processes, neuron projection and apoptosis (upregulated in FOXP1-depleted GCB-DLBCL cells). Each column in the heat map represents the fold-change in gene expression between the siRNA control and the FOXP1 targeting siRNA for two independent FOXP1 siRNAs (labeled si #1 and si #2) in each DLBCL cell line. Rows show individual genes. (b) Scatter plot analysis of gene expression profiling (n=41 000 probes) for FOXP1-silenced DB (x axis) versus K422 (Karpas 422) (y axis) cell lines. The cutoff on the positive or negative scale on both x and y axis corresponds to ±1.41-fold cutoff change. Individual MHC II genes were not significantly upregulated but are illustrated because of the importance of the overall pathway. (c) Scatter plot analysis of gene expression profiling (n=41 000 probes) for FOXP1-silenced OCI-Ly3 (x axis) versus HBL-1 (y axis) cell lines with ±1.41-fold as cutoff values for both x and y axis. Codes used to generate Figures 3b and c are available on request (by e-mail).

Figure 4

FOXP1 silencing increases HLA-DRA expression in ABC-DLBCL while FOXP1 transcripts are inversely correlated with antigen processing/presentation and with individual MHC II genes in primary DLBCL. (a) Knockdown of FOXP1 in OCI-Ly3 cells increased HLA-DRA and CD74 protein expression on the cell surface. Flow cytometry plots shown are representative of three independent experiments. (b) Gene Set Enrichment Analysis of primary DLBCL cases (n=414; GSE10846) for gene sets associated with FOXP1 transcript expression; the 'antigen processing and presentation' signature was significantly enriched according to four independent FOXP1 probes (P<0.05; false discovery rate <0.25). (c) Significant (P<0.05) inverse correlations between FOXP1 (223287_s_at) and selected MHC II transcripts (HLA-DRA, 210982_s_at; HLA-DMB, 217478_s_at and HLA-DQB1, 212999_x_at) in primary ABC-DLBCL (n=167) and GCB-DLBCL (n=183) cases derived from data set GSE10846.

Figure 5

HLA-DRA expression and its relationship with FOXP1, COO and clinical outcome in primary DLBCL patients. (a) Representative DLBCL cases with inverse FOXP1 and HLA-DRA expression patterns by immunohistochemical labeling and photographed at × 200 magnification. DLBCL-1 biopsy was scored 100% for HLA-DRA positivity and 0% for FOXP1-positive cells. DLBCL-2 biopsy was scored 0% and 90% for HLA-DRA and FOXP1 labeling, respectively. (b) Frequency of HLA-DRA positivity in GCB- and non-GCB-DLBCL cases is significantly different (P<0.05), as classified by Hans, Choi and Visco–Young algorithms. (c) Kaplan–Meier curves of OS (left panel) and PFS (right panel) in high (⩾90%) or low (<90%) HLA-DRA expressing groups of DLBCL patients (n=150) showed worse outcome for patients exhibiting <90% HLA-DRA positivity.

Figure 6

Relationships between the expression of HLA-DRA, FOXP1 and the FOXP1 target HIP1R in primary DLBCL. (a) Qualitative scoring of the intensity of FOXP1 and HLA-DRA labeling identified significant inverse relationships between these molecules. DLBCL with no loss of HLA-DRA expression exhibited a significantly higher number of cases with lower FOXP1 scores (P=0.0373). (b) Significant inverse correlation between FOXP1 and HLA-DRA (<90% frequency expression) in non-GCB DLBCL cases (n=24) was observed in frequency (r=−0.4118; P=0.046) category. (c) Reciprocal expression of FOXP1/HIP1R, used as an indicator of FOXP1_S transcriptional activity, significantly correlated with both qualitative and quantitative HLA-DRA scores.