The hematopoietic stem cell marker VNN2 is associated with chemoresistance in pediatric B-cell precursor ALL

Abstract

Most relapses of acute lymphoblastic leukemia (ALL) occur in patients with a medium risk (MR) for relapse on the Associazione Italiana di Ematologia e Oncologia Pediatrica and Berlin-Frankfurt-Münster (AIEOP-BFM) ALL protocol, based on persistence of minimal residual disease (MRD). New insights into biological features that are associated with MRD are needed. Here, we identify the glycosylphosphatidylinositol-anchored cell surface protein vanin-2 (VNN2; GPI-80) by charting the cell surface proteome of MRD very high-risk (HR) B-cell precursor (BCP) ALL using a chemoproteomics strategy. The correlation between VNN2 transcript and surface protein expression enabled a retrospective analysis (ALL-BFM 2000; N = 770 cases) using quantitative polymerase chain reaction to confirm the association of VNN2 with MRD and independent prediction of worse outcome. Using flow cytometry, we detected VNN2 expression in 2 waves, in human adult bone marrow stem and progenitor cells and in the mature myeloid compartment, in line with proposed roles for fetal hematopoietic stem cells and inflammation. Prospective validation by flow cytometry in the ongoing clinical trial (AIEOP-BFM 2009) identified 10% (103/1069) of VNN2+ BCP ALL patients at first diagnosis, primarily in the MRD MR (48/103, 47%) and HR (37/103, 36%) groups, across various cytogenetic subtypes. We also detected frequent mutations in epigenetic regulators in VNN2+ ALLs, including histone H3 methyltransferases MLL2, SETD2, and EZH2 and demethylase KDM6A. Inactivation of the VNN2 gene did not impair leukemia repopulation capacity in xenografts. Taken together, VNN2 marks a cellular state of increased resistance to chemotherapy that warrants further investigations. Therefore, this marker should be included in diagnostic flow cytometry panels.

Graphical abstract

Figure 1.

VNN2 expression is associated with an increased risk for relapse in BCP ALL. (A) VNN2 mRNA expression by q-PCR correlates with detection of VNN2 at the cell surface by FCM. PDXs from patients included in the ALL-BFM-2000 study were used for correlation. The percentage of VNN2⁺ cells by FCM with respect to the fluorescence-minus-one control is plotted on the y-axis against the mRNA levels by q-PCR as logarithmic value of 2^-ΔCT (ΔCT = CT_VNN2 − CT_SDHA) on the x-axis. MRD-based risk stratification in ALL-BFM-2000 is indicated as SR, eMR, and HR. Patients with the translocation t(17;19) leading to TCF3-HLF are highlighted as TCF3-HLF ⁺. (B) Five-year pEFS (upper part of the panel) and probability of cumulative incidence of relapse (pCIR; lower part of the panel) of 476 patients (test set) treated on the ALL-BFM 2000 study stratified according to VNN2 positivity by q-PCR. The cutoff for positivity was set to 1.13 ΔCT, as described in Materials and methods. (C-E) Five-year pEFS (upper part of the panel) and pCIR (lower part of the panel) of the same 476 patients in a subgroup analysis based on their risk stratification [SR (C), MR (D), and HR (E) for relapse] in the ALL-BFM-2000 study. A statistically significant difference was observed for pEFS and pCIR in VNN2⁺ vs VNN2⁻ patients in the MR group (P < .01). (F) Retrospective analysis of VNN2 expression by FCM on available archived samples from VNN2⁺ ALL patients based on q-PCR. Sample selection is described in supplemental Figure 1. Twenty-two of 40 positive samples by q-PCR were confirmed VNN2⁺ by FCM. Cutoff for VNN2 positivity by FCM > 10% (Materials and methods). pEFS of 22 VNN2⁺ patients based on FCM is plotted in comparison with pEFS of 615 VNN2⁻ patients based on q-PCR from the total retrospective cohort. P < .0001, log-rank test.

Figure 2.

Prospective validation of VNN2 by FCM confirms its association with MRD. (A) FCM evaluation of VNN2 in diagnostic samples from 1069 B-cell ALL patients enrolled in the AIEOP-BFM 2009 study. (B) Classification of 72 BFM 2009 VNN2⁺ patients based on cytogenetic information and FCM data. Cytogenetic data were available for 72 of 103 patients identified by FCM. (C) VNN2 expression by FCM identifies TCF3-HLF–rearranged samples. Green dots indicate TCF3-HLF–rearranged samples (patient and PDX), and pink dots indicate TCF3-PBX1–rearranged PDX samples. Arrows indicate matched patient-PDX sample or matched xenograft samples at diagnosis-relapse. Asterisks (*) indicate matched diagnosis-relapsed samples. TCF3-HLF rearranged samples scored positive for VNN2 by FCM (>10%). (D) Analysis of VNN2 in matched samples from 9 patients taken at diagnosis of ALL (day 0) and at day 15 by FCM. (E) Comparison of matched diagnosis (black circles) and relapse (gray rhombus) pairs indicated conservation of VNN2 positivity; in some cases, an increase in VNN2 from diagnosis to relapse could be observed. FCM was used to evaluate VNN2 of matched diagnosis and first relapse of 22 patients with ALL. (F) Ex vivo drug response profiling of 10 VNN2⁺ ALL samples (red circles) compared with 8 VNN2⁻ SR cases (blue circles). Patient samples were tested for dexamethasone (DEX), mitoxantrone (MITOX), bortezomib (BORTEZ), vincristine (VINCR), doxorubicin (DOX), and idarubicin (IDA). **P < .05. BAL, biphenotypic acute leukemia according to EGIL classification; B-ALL, B-cell ALL; dx, diagnosis; FMO, fluorescence-minus-one; IC50, 50% inhibitory concentration; MPAL, mixed phenotype ALL, according to World Health Organization classification; rz, relapse; SE, standard error.

Figure 3.

The signature of VNN2 ⁺ ALL is enriched with myeloid features and functional annotations related to immune response, interferon signaling, cell adhesion, and the JAK-STAT pathway. (A) Heat map with 1061 differentially expressed genes showing the transcriptome signature of 50 B-ALL samples ordered by increasing VNN2 RNA expression (left panel). Using edgeR, a linear model was fitted across the dataset of 50 ALL samples using VNN2 expression as predictor of gene expression. Genes that showed a significant linear relationship with VNN2 expression were selected (false discovery rate [FDR] ≤0.01). Genes were additionally filtered using Spearman correlation (FDR ≤0.04). A total of 549 genes and 512 genes appeared to be positively or negatively correlated with VNN2, respectively. Genes positively correlated with VNN2 include 3 genes that were identified by proteomics in an independent cohort using CSC technology (right panels). (B) Positively correlated genes were grouped by pathways using the online tool and database ConsensusPathDB (FDR ≤0.01). The most significantly overrepresented pathways (according to P value) included the immune system, interferon signaling, β-2 integrin–mediated interactions, and the JAK-STAT signaling pathway. Node size indicates the number of genes contained and the color refers to significance (P value). Two nodes are connected by a line if they share members. The line width reflects the relative overlap between the nodes, whereas the line color represents the number of shared members that are also found in the input. (C) Enrichment plot for the myeloid signature obtained after performing gene set enrichment analysis. (D) Components of the VNN2⁺ ALL signature generated using the Genomatix genome analyzer reveal functional annotations related to myeloid cells and their cellular location (adjusted P ≤ .05; P ≤ .01). Lines between genes indicate a functional association. The line type indicates the evidence level. Dashed lines indicate a functional association based on cocitation or experimental validation. Solid lines indicate a functional association based on expert curation. Diamonds indicate that a gene carries a binding site of the associated transcription factor. Arrows indicate that a gene is altered by the associated gene. Curved lines indicate that a gene alters itself on a transcriptional or protein level. The line type indicates the evidence level. Myeloid_DN, myeloid gene expression signature; NES, normalized enrichment score.

Figure 4.

Whole-exome and transcriptome sequencing identified frequent deletions in PAX5, IKZF1, CDKN2A/B and mutations in epigenetic regulators in VNN2 ⁺ patients. Whole-exome sequencing was performed in 27 VNN2⁺ patient samples (22 diagnosis, 5 relapse), and transcriptome sequencing was performed in 16 VNN2⁺ patient samples (13 diagnosis, 3 relapse). Details about sample selection are described in supplemental Figure 4. Sample identifiers are shown at the bottom of the figure. «V_a» indicates samples at diagnosis, and «V_c» indicates samples at relapse. Samples in which transcriptome sequencing was performed can be identified by an additional «_dx» or «_rz» at the end of the identifier. dx, diagnosis; rz, relapse.