Lentiviral hematopoietic stem cell gene therapy in patients with Wiskott-Aldrich syndrome

Abstract

Wiskott-Aldrich syndrome (WAS) is an inherited immunodeficiency caused by mutations in the gene encoding WASP, a protein regulating the cytoskeleton. Hematopoietic stem/progenitor cell (HSPC) transplants can be curative, but, when matched donors are unavailable, infusion of autologous HSPCs modified ex vivo by gene therapy is an alternative approach. We used a lentiviral vector encoding functional WASP to genetically correct HSPCs from three WAS patients and reinfused the cells after a reduced-intensity conditioning regimen. All three patients showed stable engraftment of WASP-expressing cells and improvements in platelet counts, immune functions, and clinical scores. Vector integration analyses revealed highly polyclonal and multilineage haematopoiesis resulting from the gene-corrected HSPCs. Lentiviral gene therapy did not induce selection of integrations near oncogenes, and no aberrant clonal expansion was observed after 20 to 32 months. Although extended clinical observation is required to establish long-term safety, lentiviral gene therapy represents a promising treatment for WAS.

Trial registration: ClinicalTrials.gov NCT01515462.

Figures

Fig. 1. Engraftment of transduced cells and WASP expression after gene therapy

Vector copy number (VCN) per genome was evaluated by qPCR at different time points (up to 2.5 years) after gene therapy (GT) in CD15+ granulocytes, CD19+ B cells, CD4+ and CD8+ T cells, CD14+ monocytes, CD34+ progenitors and CD61+ (megakaryocytic lineage), purified either from peripheral blood (A) or bone marrow (B) in Patient 1 (left), 2 (center) and 3 (right). (C) Percentage of vector-positive bone marrow colony-forming cells (BM CFC) evaluated by PCR analyses on individual colonies derived from ex vivo purified CD34+ cells after gene therapy. (D) WAS protein expression measured by cytofluorimetric analysis at different time points after gene therapy in patient lymphocytes (left) and platelets (right). *WASP expression was measured after transfusion of donor platelets. Transgene expression was confirmed by immunoblot analysis of peripheral blood mononuclear cells, untransformed T-cell lines and a EBV-transformed B cell line (Fig. S3).

Fig. 2. Clinical features and immune function of WAS patients after gene therapy

(A) Platelet counts before and 1 year after gene therapy. Kinetics of platelet counts during the first year of follow-up, analyzed by a mixed linear model applied to the individual repeated counts. Platelet transfusions (T) are indicated by an horizontal bar. (B) Summary of bleeding events. Each of the 3 categories [skin manifestations (petechiae/purpura), epistaxis, GI bleeding] was given an arbitrary score: 0, absent; 1, moderate; 2, severe (with the total score ranging between 0 and 6). Patients were evaluated after gene therapy following discontinuation of platelet transfusions (see Materials and Methods). (C) Disease score (Zhu score) evaluated pre- and post-gene therapy (39). (D) TCR-driven proliferation in PB mononuclear cells from WAS patients (before and 1 year after gene therapy) or healthy controls (HCs) (Boxplot with mean, 1st and 4th quartile, 5th and 95th percentile, n=15); SI. Stimulation index. (E) Treg-mediated suppression of effector T cells pre-gene therapy and 1 year post-gene therapy in Pt1, in comparison to healthy controls (mean ± SD, n=9). Eff: unstimulated effector cells. Eff.(a-CD3): effector cells stimulated with allogeneic accessory cells and soluble anti-CD3 mAb. Treg cells (sorted for CD4+/CD25high/CD127low/neg cells), were added to effector cells at 1:1 ratio and proliferation was measured by 3H-thymidine incorporation. Percentages indicate inhibition of proliferation. (F) Formation of NK immunological synapse. Distance of the microtubule organizing center (MTOC) from the immunological synapses in NK cells contacting K562 target cells. Analyses were performed by confocal microscopy in Pt1, 18 months after gene therapy. Patient NK cells were identified as positive or negative for WASP expression by anti-WASP antibody. (G) NK cell cytotoxic activity. Shown is the percent lysis of K562 human erythroleukemia cells by patient-derived PB mononuclear cells, as measured in a chromium release assay.

Fig. 3. Long-term polyclonal engraftment of gene-corrected HSPC, assessed by longitudinal integration site profiling

(A) Distribution of sequence reads in different lineages at different timepoints. Each boxplot shows the distribution of sequence reads in two WAS patients in the different lineages. Percentages of sequence reads for each IS are calculated over the total number of sequence reads from the same source (BM or PB) and timepoint. X-axis indicates months after gene therapy, Y-axis percentage of sequence reads. IS outliers (over 95 percentile of ISs dataset from same timepoint) are shown as dots. The total number of ISs is shown on top of each boxplot for the relative lineage and timepoint. Genes proximal to IS representing more than 5% of sequence reads from same source and timepoint are reported on top of outlier dots. (B) Top contributing ISs inside each lineage in BM CD34+ cells, PB Myeloid B and T cells in two WAS patients. Percentages of sequence reads for each IS are calculated over the total number of sequence reads from the same lineage. Top IS shown in the heatmaps account for more than 5% of sequence reads from their lineage. Each column corresponds to a timepoint (months after gene therapy), and each row to a given top ISs based on sequence reads. Color intensity on the heatmaps represents for each IS the percentages of relative sequence reads on total sequence reads from same lineage and timepoint, ranging from white (IS not detected at that timepoint) to gray (IS detected at percentages lower than 5% of sequence reads from that given timepoint) to gradient of colors (IS detected at more than 5% of sequence reads from that given timepoint). (C) Diversity of ISs in different lineages and timepoint. For each ISs dataset from the same lineages and timepoints of panel A and B a Shannon diversity index was calculated and plotted.

Fig. 4. Multi-lineage engraftment and activity of gene-corrected HSPC

(A) Multi-lineage detection of identical IS. Venn diagram show overlaps among CD34+, myeloid, lymphoid cells and CFCs ISs datasets from Pt1. Column graphs show percentage of CD34+ cells and CFC ISs from Pt1 shared with myeloid\lymphoid lineages (red and blue portion of column respectively) at different months after gene therapy. (B) Detection of shared ISs over time. Heatmaps show CD34+ cells and CFCs ISs at different timepoint shared with the 4 lineages of panel A–C. Each column shows a lineage and a timepoint and each row a shared ISs belonging to CD34+ cells (red) or CFCs (blue). The intensity of colors indicates degree of ISs detection in multiple lineages and timepoints from highly shared ISs (high intensity of red and blue) to ISs shared with a single lineage and timepoint (light red or blue)

Fig. 5. Comparative analysis of vector integration sites in patients treated by gene therapy with lentiviral or γ-retroviral vectors

(A) Genomic distribution of ISs from five patients with WAS, treated by lentiviral (n=3) or γ-retroviral (n=2) vectors. Chromosome names are reported on top of the graph. Refseq Genes and ISs frequency distributions are shown in bins of 1Mbp (grey, colored/red columns respectively). (B) Chromatin modifications surrounding ISs. Probability density distributions of histone modifications mapped on CD34+ cells in a +/−45kb window surrounding IS are shown as heatmaps. Color intensity show under (blue) or over (yellow) representation of each given histone modification as compared to random in silico generated reference. Each row represents an in vitro or in vivo ISs dataset from the patients treated with lentiviral or γ-retroviral vectors. (C) Gene Ontology of genes proximal to ISs. Biological process and Diseases significantly associated to the functions of genes proximal to ISs in lentiviral and γ-retro gene therapy are represented as blue and red bars, respectively. The values on y-axis show the fold enrichment scale for gene ontology categories.

Fig. 6. Common insertion sites and oncogenic hits in lentiviral vs γ-retroviral gene therapy

(A) Overlaps among CIS genes in lentiviral and γ-retroviral gene therapy. Genes proximal to CIS of order >10 are reported in the overlapping circles for lentiviral and γ-retro gene therapy (blue and red, respectively). Word clouds show the intensity of ISs clustering in each of the CIS gene (the bigger the gene name the higher the number of ISs inside or in the proximity of that gene). The names of the 6 CIS genes detected in both gene therapy trials are reported on the right at the intersection between the circles. (B) Incidence of ISs at two oncogenes in patients treated with lentiviral or γ-retroviral gene therapy. The comparative frequency distributions of insertions from lentiviral and γ-retroviral gene therapy in bins of 2kb are shown for chromosome 3 (left panel) and 11 (right panel). Mirror graph shows for each bin more frequent insertions in γ-retroviral gene therapy (columns above X-axis) and more frequent insertions in lentiviral gene therapy (columns below X-axis) (*p<0.05 Fisher exact test). Light grey columns on top show transcriptional units frequency for the same bins. Boxes on bottom show a detail of MECOM and LMO2 loci where ISs from the three lentiviral and two retroviral gene therapy patients are shown as sticks below the gene transcript. Raw IS data from the patients treated with the γ-retroviral vector were generated by Boztug et al (12) and re-processed through our informatic pipeline (Table SOM3).