Pathogenic role of B-cell receptor signaling and canonical NF-κB activation in mantle cell lymphoma

Abstract

To interrogate signaling pathways activated in mantle cell lymphoma (MCL) in vivo, we contrasted gene expression profiles of 55 tumor samples isolated from blood and lymph nodes from 43 previously untreated patients with active disease. In addition to lymph nodes, MCL often involves blood, bone marrow, and spleen and is incurable for most patients. Recently, the Bruton tyrosine kinase (BTK) inhibitor ibrutinib demonstrated important clinical activity in MCL. However, the role of specific signaling pathways in the lymphomagenesis of MCL and the biologic basis for ibrutinib sensitivity of these tumors are unknown. Here, we demonstrate activation of B-cell receptor (BCR) and canonical NF-κB signaling specifically in MCL cells in the lymph node. Quantification of BCR signaling strength, reflected in the expression of BCR regulated genes, identified a subset of patients with inferior survival after cytotoxic therapy. Tumor proliferation was highest in the lymph node and correlated with the degree of BCR activation. A subset of leukemic tumors showed active BCR and NF-κB signaling apparently independent of microenvironmental support. In one of these samples, we identified a novel somatic mutation in RELA (E39Q). This sample was resistant to ibrutinib-mediated inhibition of NF-κB and apoptosis. In addition, we identified germ line variants in genes encoding regulators of the BCR and NF-κB pathway previously implicated in lymphomagenesis. In conclusion, BCR signaling, activated in the lymph node microenvironment in vivo, appears to promote tumor proliferation and survival and may explain the sensitivity of this lymphoma to BTK inhibitors.

Figures

Figure 1

Gene expression differs between MCL cells in PB and LN due to activation of signaling pathways in the LN. (A) Heat map of 130 genes that were differentially expressed in purified MCL cells obtained from PB (PBT, n = 17) and LN (LNT, n = 4) in 18 patients (>2-fold change, FDR < 0.2). Gene expression data were median-centered. Relative expression is indicated by the color scale. (B and C) GSEA identified a large number of upregulated gene sets in LNT compared with PBT. Accordingly, 166 relevant gene sets were selected having FDR ≤ 0.01, NES ≥1.80, and ≥10 “leading edge genes” (the genes of a given gene set most significantly differentially expressed in the experimental data), then grouped into 4 categories based on their functional similarities (supplemental Table 3). Two of these 4 categories are displayed: (B) “Signaling and interaction with the microenvironment” and (C) “Proliferation/malignancy”. Within each subcategory, the “signature score” of the gene set with the highest NES was calculated and displayed. This signature score was computed as the average of the mRNA expression level of the leading edge genes of a given gene set. The signature scores were compared between PBT and LNT samples using unpaired Student t test. AKT, protein kinase B; APRIL, a proliferation inducing ligand; BAFF, B-cell activating factor; E2F, E2F transcription factor; ERK, extracellular signal regulated kinase; GSK3, glycogen synthase kinase 3; IL, interleukin; LNT, purified tumor cells from LN; MAPK, mitogen-activated protein kinase; mTOR, mammalian target of rapamycin; MYC, v-myc avian myelocytomatosis viral oncogene homolog; PBT, purified tumor cells from PB; PG, prostaglandin; PI3K, phosphatidylinositol 3-kinase; Rb, retinoblastoma; TGFβ, transforming growth factor-β. ***P < .001; **P < .01.

Figure 2

Activation of BCR and NF-κB signaling and tumor proliferation in LN-resident cells. (A) Twenty-seven genes comprising a previously validated BCR gene signature are depicted in a heat map. Gene expression data were median-centered and scaled as indicated. Each column represents a patient’s sample; each row represents a gene. Genes are vertically arranged in the corresponding table, following the same order as in the heat map. (B) The BCR signature score was computed by averaging the mRNA expression level of all signature genes. Signature scores between PBT and LNM groups were compared using unpaired Student t test (left panel). BCR scores in matched MCL PBT/LNM (n = 8) and LNT/LNM (n = 4) samples were compared using paired Student t test (right panels). Matched samples were concomitantly collected from the same patient and are connected with a line. (C) Heat map of 18 genes representing the canonical NF-κB pathway (NF-κB signature) generated after a supervised clustering of the samples. Patients’ samples and gene names are arranged in columns and rows, respectively. Genes are vertically arranged in the corresponding table, following the same order as in the heat map. (D) The NF-κB signature scores of MCL PBT, LNM, and LNT were compared as in (B). (E) Heat map of 28 genes representing the alternative NF-κB pathway (NIK signature) generated after a supervised clustering of the samples. Patients’ samples and gene names are arranged in columns and rows, respectively. Genes are vertically arranged in the corresponding table, following the same order as in the heat map. (F) The NIK signature scores of MCL PBT, LNM, and LNT were compared as in (B). LNM, whole lymph node biopsy.

Figure 3

Activation of signal transduction components of the BCR and downstream pathways. Phosphorylation of SYK, PLCγ, ERK, AKT, and p65 was assessed by flow cytometry in CD5+/CD19+ MCL cells from the PB and LN. (A) Comparison of the BCR and NF-κB signature scores between PBT and LNT samples concomitantly isolated from 2 patients providing matched cell samples. (B) Flow plots of PB and LN samples from a representative patient are shown. (C) Summary of phosphoprotein analysis (tested in duplicate) for matched PB and LN samples from the 2 patients shown in (A). (D) Pearson correlation r was used to measure the relationship of the percent tumor cells with detectable p-SYK and the corresponding BCR signature score in MCL-PBT (n = 14).

Figure 4

The LN microenvironment promotes tumor activation and proliferation. (A) The MCL-proliferation score was compared between PBT and LNM groups using unpaired Student t test (left panel). MCL-proliferation scores in matched MCL PBT/LNM (n = 8) samples were compared using paired Student t test (right panel). (B) Representative PBT and LNT samples from 2 patients with MCL were tested for Ki67 using flow cytometry. (C) Comparison of Ki67-positive cells between PBT and LNM (n = 5) samples concomitantly collected from the same patient. (D) The activation markers CD69 and CD80 were measured using flow cytometry in CD5+/CD19+-gated cells of matched PBT and LNT from 3 patients with MCL. Pearson correlations of the (E) proliferation score in LN biopsies (LNM, n = 34) and (F) the percent Ki67-positive cells in LNM (n = 32) quantified by immunohistochemistry, with the corresponding BCR signature score.

Figure 5

BCR score predicts for PFS and OS in MCL. Probabilities of PFS and OS were compared in subgroups dichotomized by BCR score measured in the LN samples using the log-rank test. The median OS or PFS time was calculated as the smallest survival time when the survival probability is ≤50%. (A) The median PFS time for patients with BCR score within the upper tercile was 2.0 years and was 2.9 years for the remaining patients. (B) At the median follow-up of 7.5 years, the estimated OS for patients with BCR score in the upper tercile was 68% and was 96% for the remaining patients. The median OS time for patients dichotomized by BCR score was (C) in an independent validation set 1.5 years and 3.2 years, respectively, and (D) in both sets combined (n = 126) 3.1 and 5.5 years, respectively.

Figure 6

Mutations in signal transduction components, BCR signaling, and sensitivity to BTK inhibition. (A) Nonsynonymous mutations predicted to have a significant effect on the protein by at least 2 software programs were considered “relevant mutations.” Sixteen leukemic MCL samples were subject to RNA sequencing. A set of 137 genes representing the BCR and NF-κB (canonical and alternative) pathways (supplemental Table 4) was tested for point mutations using the following filters: minimum number of reads: 8; minimum percent of mutated reads: 20; duplicate reads excluded; synonymous mutations and mutations listed in the SNP137 database excluded. Samples are displayed according to their ascending BCR signature score and divided in 2 groups: (1) BCR-low, n = 9; and (2) BCR-high, n = 7, based on the BCR score mean. Allele frequency is median-centered and scaled as indicated. Each column represents a patient sample and each row represents a gene. (B) The BCR signature score, and the levels of p-p65 and p-SYK (expressed as log2 of the percent positive cells among CD5+/CD19+-gated cells) were median-centered and displayed according to the color scale. Each column represents a patient’s sample. Leukemic samples are arranged according to their BCR signature score. Suspension cells obtained from LN are shown on the far right for comparison (LNT). (C) Change in p-p65 MFI of 4 samples after exposure to ibrutinib, tested by flow cytometry. Each data point represents the mean of duplicates from 2 separate experiments. (D) MTS assay of samples as in (C) tested in triplicate against increasing concentrations of ibrutinib, the MALT1 inhibitor MI-2, and the IKK inhibitor PS1145 for 48 hours.