Correction of β-thalassemia by CRISPR/Cas9 editing of the α-globin locus in human hematopoietic stem cells
β-thalassemias (β-thal) are a group of blood disorders caused by mutations in the β-globin gene (HBB) cluster. β-globin associates with α-globin to form adult hemoglobin (HbA, α2β2), the main oxygen-carrier in erythrocytes. When β-globin chains are absent or limiting, free α-globins precipitate and damage cell membranes, causing hemolysis and ineffective erythropoiesis. Clinical data show that severity of β-thal correlates with the number of inherited α-globin genes (HBA1 and HBA2), with α-globin gene deletions having a beneficial effect for patients. Here, we describe a novel strategy to treat β-thal based on genome editing of the α-globin locus in human hematopoietic stem/progenitor cells (HSPCs). Using CRISPR/Cas9, we combined 2 therapeutic approaches: (1) α-globin downregulation, by deleting the HBA2 gene to recreate an α-thalassemia trait, and (2) β-globin expression, by targeted integration of a β-globin transgene downstream the HBA2 promoter. First, we optimized the CRISPR/Cas9 strategy and corrected the pathological phenotype in a cellular model of β-thalassemia (human erythroid progenitor cell [HUDEP-2] β0). Then, we edited healthy donor HSPCs and demonstrated that they maintained long-term repopulation capacity and multipotency in xenotransplanted mice. To assess the clinical potential of this approach, we next edited β-thal HSPCs and achieved correction of α/β globin imbalance in HSPC-derived erythroblasts. As a safer option for clinical translation, we performed editing in HSPCs using Cas9 nickase showing precise editing with no InDels. Overall, we described an innovative CRISPR/Cas9 approach to improve α/β globin imbalance in thalassemic HSPCs, paving the way for novel therapeutic strategies for β-thal.
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细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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