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CRISPR–Cas9-mediated gene editing of the BCL11A enhancer for pediatric β00 transfusion-dependent β-thalassemia

Abstract

Gene editing to disrupt the GATA1-binding site at the +58 BCL11A erythroid enhancer could induce γ-globin expression, which is a promising therapeutic strategy to alleviate β-hemoglobinopathy caused by HBB gene mutation. In the present study, we report the preliminary results of an ongoing phase 1/2 trial (NCT04211480) evaluating safety and efficacy of gene editing therapy in children with blood transfusion-dependent β-thalassemia (TDT). We transplanted BCL11A enhancer-edited, autologous, hematopoietic stem and progenitor cells into two children, one carrying the β00 genotype, classified as the most severe type of TDT. Primary endpoints included engraftment, overall survival and incidence of adverse events (AEs). Both patients were clinically well with multilineage engraftment, and all AEs to date were considered unrelated to gene editing and resolved after treatment. Secondary endpoints included achieving transfusion independence, editing rate in bone marrow cells and change in hemoglobin (Hb) concentration. Both patients achieved transfusion independence for >18 months after treatment, and their Hb increased from 8.2 and 10.8 g dl−1 at screening to 15.0 and 14.0 g dl−1 at the last visit, respectively, with 85.46% and 89.48% editing persistence in bone marrow cells. Exploratory analysis of single-cell transcriptome and indel patterns in edited peripheral blood mononuclear cells showed no notable side effects of the therapy.

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Fig. 1: Hematological data before and after transplantation.
Fig. 2: Key laboratory values of clinical outcomes.
Fig. 3: Gene-editing efficiency and outcome analysis.
Fig. 4: Transcriptional impact of BCL11A enhancer editing in PBMCs from treated patients at single-cell resolution.

Data availability

All amplicon deep-sequencing data generated in this article can be found at the National Center for Biotechnology Information’s Sequence Read Archive (accession no. PRJNA839164). Single-cell transcriptome data generated in this article can be found at the Gene Expression Omnibus database with accession no. GSE204688. A shared dataset used in this article for 10,000 PBMC single-cell transcriptome data from a healthy donor can be downloaded from: https://cf.10xgenomics.com/samples/cell-exp/4.0.0/SC3_v3_NextGem_SI_PBMC_10K/SC3_v3_NextGem_SI_PBMC_10K_raw_feature_bc_matrix.tar.gz.

Individual participant data (IPD) that underlie the results reported in published article will be shared, after de-identification (text, tables, figures and appendices). Other available documents include the study protocol. IPD sharing will start at 6 months and end at 36 months after article publication. IPD will be shared with investigators for individual data meta-analysis, after their proposed use of the data has been approved by an independent review committee. Proposals should be directed to yxwu@bio.ecnu.edu.cn and fu.bin@csu.edu.cn. To gain access, data requestors will need to sign a data access agreement. Source data are provided with this paper.

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Acknowledgements

We thank all the patients and their families for their participation in the present study and the staff at Xiangya Hopital for their contributions to the care of the patients. This trial was sponsored by Shanghai Bioray Laboratories Inc. The sponsor was involved in clinical protocol design, data analysis, hematopoietic stem cell collection and cell production. We thank current and previous employees of Shanghai Bioray Laboratories Inc. and East China Normal University for helpful discussions. We thank S. Siwko for scientific editing and comments. We also thank D. E. Bauer for helpful suggestions to enhance our manuscript. We appreciate the support of grants from National Key R&D Program of China (grant nos. 2019YFA0802800, 2019YFA0110803, 2019YFA0109900 and 2019YFA0109901 to Y.W. and 2019YFA0802802 to M.L.), the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning (no. 11300-412214-20009 to Y.W.), the Innovation program of Shanghai Municipal Education Commission (no. 2019-01-07-00-05-E00054 to D.L.) and the Shanghai pujiang program (no. 11300-412213-19B08 to Y.W.).

Author information

Authors and Affiliations

Authors

Contributions

B.F., D.L., M.L. and Y.W. designed and led the study. B.F. was site principal investigator. J.L. and S.C. conducted experiments and analyzed data with the help of W.L., Q.W., F.Y., S.H., Y.J. and L.W. B.F., J.H. and F.C. were involved in patient care, testing and data presentation. B.F., J.L., S.C. and Y.W. wrote the manuscript. All authors contributed to the manuscript and approved its final version.

Corresponding authors

Correspondence to Bin Fu, Dali Li, Mingyao Liu or Yuxuan Wu.

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Competing interests

The authors declare the following competing interests: W.L., F.Y., D.L., M.L. and Y.W. are employees of Bioray Laboratories. The remaining authors declare no competing interests.

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Peer review information

Nature Medicine thanks Matthew Porteus, Martin Steinberg and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling editor: Anna Maria Ranzoni, in collaboration with the Nature Medicine team

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Extended data

Extended Data Fig. 1 Representative blood cell subtype cytometry analysis.

Representative blood cell subtype cytometry analysis. The gating strategy for blood cell subtype analysis is as shown. Lymphocytes were gated from a single cell population with CD45 high, SSC low. T cells are gated from the CD45+/CD3+ population. B cells are gated from the CD45+/CD3-/CD19+ population. NK cells are gated from the CD45+/CD3-/CD16/56+ population.

Extended Data Fig. 2 RP-HPLC analysis of globin chains in treated patients.

RP-HPLC analysis of globin chains in healthy donor and two patients (at Month 9, 15 and 18). RP-HPLC chromatograms are reported together with the non–α: α ratio (in brackets). The various globin chains detected were labeled on top and their respective peak shape ranges were marked with a gray background. Gamma globin chains were robustly induced in both patients. The expression of a common AγT chain variant was detected in samples derived from Patient 2. After treatment, the two patients had equal amounts of alpha and non-alpha chains in their blood after treatment as that of healthy donor.

Source data

Extended Data Fig. 3 Representative indel tables of two patients’ edited cells.

Summary of most frequent indels by deep sequencing of the genome from input CD34+ cells, PBMCs Mo7 after transplantation, and PBMCs Mo15 after transplantation from study patients. The reference sequence at the top of the figure is part of the BCL11A enhancer DNase I hypersensitive site (DHS) + 58 functional core. Gata1 motif marked with green box, and the sgRNA targets the complementary strand of the gata1 motif sequence.

Extended Data Fig. 4 Representative indel tables of two patients’ engrafted cells.

Summary of most frequent indels by deep sequencing result of T cells, B cells, NK cells, Monocytes and Neutrophils sorted from peripheral blood at Mo15 post transplantation from study patients. The reference sequence at the top of the figure is part of the BCL11A enhancer DNase I hypersensitive site (DHS) + 58 functional core. Gata1 motif marked with green box, and the sgRNA targets the complementary strand of the gata1 motif sequence.

Extended Data Fig. 5 Genotyping analysis of patient single CD34+ cell expansions.

CD34 + cells were sorted by MACS from bone marrow cells of patients 9 months after transplantation, and their single-cell expansions were analyzed for genotype by sanger sequencing. It was found that 88.3% (n=77) and 79.8% (n=104) of the CD34+ cells of the two patients were biallelic editing.

Source data

Extended Data Fig. 6 Representative cytoflow analysis for F-cells proportion in patient RBCs after treatment.

The proportion of F-cells in peripheral red blood cells was measured by FACS at 15 months after transplantation in both patients, blood sample from healthy people as control. After treatment, both patients showed robust HBF expression in peripheral red blood cells.

Extended Data Fig. 7 Sc-RNA seq analysis of edited and unedited patient PBMCs.

a, Marker gene expression for subtypes from PBMCs. b, UMAP plots representing 13 color-coded cell clusters identified in single-cell transcriptomes of PBMCs from 2 heathy donors, 1 patient sample before treatment and 3 patient samples at different time points after treatment. c, Violin plots showing BCL11A expression (log transformed) for B cell cluster from each sample. Wilcox two-tailed test, with each p-value, is indicated above the comparison group.

Extended Data Table 1 Summary of Adverse Events for Patient 1 (TDT)
Extended Data Table 2 Summary of Adverse Events for Patient 2 (TDT)
Extended Data Table 3 Medication History of iron chelation for two patients

Supplementary information

Supplementary Information

Supplementary Tables 1–5, Clinical research protocol.

Reporting summary

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Fu, B., Liao, J., Chen, S. et al. CRISPR–Cas9-mediated gene editing of the BCL11A enhancer for pediatric β00 transfusion-dependent β-thalassemia. Nat Med (2022). https://doi.org/10.1038/s41591-022-01906-z

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