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. 2022 Nov 2;3(6):554-567.
doi: 10.1158/2643-3230.BCD-21-0220.

Targeting the EIF2AK1 Signaling Pathway Rescues Red Blood Cell Production in SF3B1-Mutant Myelodysplastic Syndromes With Ringed Sideroblasts

Vera Adema #  1 , Feiyang Ma #  2 , Rashmi Kanagal-Shamanna  3 , Natthakan Thongon  1 , Guillermo Montalban-Bravo  1 , Hui Yang  1 , Scott A Peslak  4   5 , Feng Wang  6 , Pamela Acha  7 , Francesc Sole  7 , Pamela Lockyer  1 , Margherita Cassari  8 , Jaroslaw P Maciejewski  9 , Valeria Visconte  9 , Irene Gañán-Gómez  1 , Yuanbin Song  10 , Carlos Bueso-Ramos  3 , Matteo Pellegrini  11 , Tuyet M Tan  12 , Rafael Bejar  12 , Jennifer S Carew  13 , Stephanie Halene  14 , Valeria Santini  8 , Gheath Al-Atrash  15 , Karen Clise-Dwyer  15 , Guillermo Garcia-Manero  1 , Gerd A Blobel  5 , Simona Colla  1
Affiliations

Targeting the EIF2AK1 Signaling Pathway Rescues Red Blood Cell Production in SF3B1-Mutant Myelodysplastic Syndromes With Ringed Sideroblasts

Vera Adema et al. Blood Cancer Discov. .

Abstract

SF3B1 mutations, which occur in 20% of patients with myelodysplastic syndromes (MDS), are the hallmarks of a specific MDS subtype, MDS with ringed sideroblasts (MDS-RS), which is characterized by the accumulation of erythroid precursors in the bone marrow and primarily affects the elderly population. Here, using single-cell technologies and functional validation studies of primary SF3B1-mutant MDS-RS samples, we show that SF3B1 mutations lead to the activation of the EIF2AK1 pathway in response to heme deficiency and that targeting this pathway rescues aberrant erythroid differentiation and enables the red blood cell maturation of MDS-RS erythroblasts. These data support the development of EIF2AK1 inhibitors to overcome transfusion dependency in patients with SF3B1-mutant MDS-RS with impaired red blood cell production.

Significance: MDS-RS are characterized by significant anemia. Patients with MDS-RS die from a shortage of red blood cells and the side effects of iron overload due to their constant need for transfusions. Our study has implications for the development of therapies to achieve long-lasting hematologic responses. This article is highlighted in the In This Issue feature, p. 476.

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Figures

Figure 1. SF3B1MT do not impair erythropoiesis at the level of HSPCs. A, UMAP plots of scRNA-seq data displaying pooled single Lin-CD34+ cells isolated from two HD (n = 2,324) and five SF3B1-mutant MDS-RS (n = 5,544) samples. Each dot represents one cell. Different colors represent the sample origin (top) and cluster identity (bottom). B, Distribution of HD (left) and MDS-RS (right) Lin-CD34+ cells among the clusters shown in A defined by distinct lineage differentiation profiles. Prolif, proliferative. C, Pathway enrichment analysis of the genes that were significantly upregulated in the MDS-RS Ery/Mk clusters as compared with the HD Ery/Mk clusters shown in A (adjusted P ≤ 0.05). The top 10 Hallmark gene sets are shown. D, UMAP plots of scATAC-seq data for pooled Lin-CD34+ cells isolated from 2 HD (n = 1,844) and 3 SF3B1-mutant MDS-RS (n = 5,203) samples. Each dot represents one cell. Different colors represent the sample origin (left) and cluster identity (right). E, Violin plots showing the activities of the TFs GATA1, GATA2, and GATA3 across the 8 clusters shown in D. F, Pathway enrichment analysis of the genes whose distal elements were enriched in open chromatin regions in HD cells from cluster 2 shown in D as compared with those of MDS-RS cells (adjusted P ≤ 0.05). The top 10 Reactome gene sets are shown. Baso, basophilic; DC, dendritic cell; Ery/Mk, erythroid/megakaryocytic; Granulo, granulocytic; HSC, hematopoietic stem cells; Mono, monocytic; MPP, multipotent progenitors; Myelo, myeloid; Prog, progenitors; UMAP, uniform manifold approximation and projection.
Figure 1.
SF3B1 MT do not impair erythropoiesis at the level of HSPCs. A, UMAP plots of scRNA-seq data displaying pooled single Lin−CD34+ cells isolated from two HD (n = 2,324) and five SF3B1-mutant MDS-RS (n = 5,544) samples. Each dot represents one cell. Different colors represent the sample origin (top) and cluster identity (bottom). B, Distribution of HD (left) and MDS-RS (right) Lin−CD34+ cells among the clusters shown in A defined by distinct lineage differentiation profiles. Prolif, proliferative. C, Pathway enrichment analysis of the genes that were significantly upregulated in the MDS-RS Ery/Mk clusters as compared with the HD Ery/Mk clusters shown in A (adjusted P ≤ 0.05). The top 10 Hallmark gene sets are shown. D, UMAP plots of scATAC-seq data for pooled Lin−CD34+ cells isolated from 2 HD (n = 1,844) and 3 SF3B1-mutant MDS-RS (n = 5,203) samples. Each dot represents one cell. Different colors represent the sample origin (left) and cluster identity (right). E, Violin plots showing the activities of the TFs GATA1, GATA2, and GATA3 across the 8 clusters shown in D. F, Pathway enrichment analysis of the genes whose distal elements were enriched in open chromatin regions in HD cells from cluster 2 shown in D as compared with those of MDS-RS cells (adjusted P ≤ 0.05). The top 10 Reactome gene sets are shown. Baso, basophilic; DC, dendritic cell; Ery/Mk, erythroid/megakaryocytic; Granulo, granulocytic; HSC, hematopoietic stem cells; Mono, monocytic; MPP, multipotent progenitors; Myelo, myeloid; Prog, progenitors; UMAP, uniform manifold approximation and projection.
Figure 2. SF3B1MT arrest erythroid terminal differentiation and activate the EIF2AK1-induced response pathway to heme deficiency. A, UMAP plots of scRNA-seq data for pooled single MNCs isolated from two HD (n = 5,049) and five SF3B1-mutant MDS-RS (n = 16,212) samples. Each dot represents one cell. Different colors represent the sample origin (left) and cluster identity (right). B, UMAP plot of scRNA-seq data from A showing the 7 different stages of erythroid differentiation in the total erythroblast population. C, Distribution of the 7 stages of erythroid differentiation in the HD (top) and MDS-RS (bottom) erythroblast populations shown in A. Arrows indicate the terminal steps of erythroid differentiation. D, Pathway enrichment analyses of the genes that were significantly upregulated in Pro-E (top), Baso-E (middle), Poly-E (bottom) from MDS-RS samples as compared with those from HD samples (P ≤ 0.01) The top 10 Reactome gene sets are shown. E, Pathway enrichment analysis of the genes that were significantly upregulated in Ortho-E from MDS-RS samples as compared with those from HD samples (P ≤ 0.01) The top 10 Reactome gene sets are shown. F, Left, the number of autophagic vesicles per cell in SF3B1WT and SF3B1-mutant erythroblasts from one representative SF3B1WT and one SF3B1-mutant sample. Statistically significant differences were detected using a two-tailed Student t test. Right, representative transmission electron microscopy images of erythroblasts from the BM sections of one SF3B1WT and one SF3B1-mutant MDS sample. Scale bars, 500 nm. Baso-E, basophilic erythroblasts; BFU-E, burst-forming unit-erythroid cells; B-Lympho, B-lymphocytes; CFU-E, colony formation unit-erythroid cells; DC, dendritic cells; Ery, erythroblasts; HSPC, hematopoietic stem and progenitor cells; Myelo, myeloid cells; Ortho-E, orthochromatic erythroblasts; Poly-E, polychromatophilic erythroblasts; Pre-E, pre-erythrocytes; Pro-E, pro-erythroblasts; T-Lympho/NK, T-lymphocytes, and natural killer cells; UMAP, uniform manifold approximation and projection.
Figure 2.
SF3B1 MT arrest erythroid terminal differentiation and activate the EIF2AK1-induced response pathway to heme deficiency. A, UMAP plots of scRNA-seq data for pooled single MNCs isolated from two HD (n = 5,049) and five SF3B1-mutant MDS-RS (n = 16,212) samples. Each dot represents one cell. Different colors represent the sample origin (left) and cluster identity (right). B, UMAP plot of scRNA-seq data from A showing the 7 different stages of erythroid differentiation in the total erythroblast population. C, Distribution of the 7 stages of erythroid differentiation in the HD (top) and MDS-RS (bottom) erythroblast populations shown in A. Arrows indicate the terminal steps of erythroid differentiation. D, Pathway enrichment analyses of the genes that were significantly upregulated in Pro-E (top), Baso-E (middle), Poly-E (bottom) from MDS-RS samples as compared with those from HD samples (P ≤ 0.01) The top 10 Reactome gene sets are shown. E, Pathway enrichment analysis of the genes that were significantly upregulated in Ortho-E from MDS-RS samples as compared with those from HD samples (P ≤ 0.01) The top 10 Reactome gene sets are shown. F, Left, the number of autophagic vesicles per cell in SF3B1WT and SF3B1-mutant erythroblasts from one representative SF3B1WT and one SF3B1-mutant sample. Statistically significant differences were detected using a two-tailed Student t test. Right, representative transmission electron microscopy images of erythroblasts from the BM sections of one SF3B1WT and one SF3B1-mutant MDS sample. Scale bars, 500 nm. Baso-E, basophilic erythroblasts; BFU-E, burst-forming unit-erythroid cells; B-Lympho, B-lymphocytes; CFU-E, colony formation unit-erythroid cells; DC, dendritic cells; Ery, erythroblasts; HSPC, hematopoietic stem and progenitor cells; Myelo, myeloid cells; Ortho-E, orthochromatic erythroblasts; Poly-E, polychromatophilic erythroblasts; Pre-E, pre-erythrocytes; Pro-E, pro-erythroblasts; T-Lympho/NK, T-lymphocytes, and natural killer cells; UMAP, uniform manifold approximation and projection.
Figure 3. Hypomethylating agent therapy inhibits the EIF2AK1-induced response pathway to heme deficiency in terminally differentiated cells in patients who became transfusion independent. A, UMAP plots of scRNA-seq data for pooled single Lin-CD34+ cells isolated from two SF3B1-mutant MDS-RS patients at the time of diagnosis (n = 2,372) and at the time of response to HMA therapy (n = 1,551). Each dot represents one cell. Different colors represent the sample origin (left) and cluster identity (right). B, UMAP plots of scRNA-seq data for pooled single MNCs isolated from three SF3B1-mutant MDS-RS patients at the time of diagnosis (n = 6,089) and response to HMA therapy (n = 6,156). Each dot represents one cell. Different colors represent the sample origin (left) and cluster identity (right). C, Distribution of the stages of erythroid differentiation in the total erythroblast population shown in B at the time of diagnosis (left) and at the time of response to HMA therapy (right). Arrows indicate Ortho-E. D, Pathway enrichment analysis of the genes in the MDS-RS Pro-E, Baso-E, and Poly-E clusters shown B that were significantly downregulated at the time of response to HMA therapy as compared with the time of diagnosis (adjusted P ≤ 0.05). The top 10 Reactome gene sets are shown. E, Pathway enrichment analysis of the genes in the MDS-RS Ortho-E shown in B that were significantly downregulated at the time of response to HMA therapy as compared with the time of diagnosis (P ≤ 0.01). The top 10 Reactome gene sets are shown. Baso-E, basophilic erythroblasts; BFU-E, burst-forming unit-erythroid cells; B-Lympho, B-lymphocytes; CFU-E, colony formation unit-erythroid cells; Ery/Mk, erythroid/megakaryocytic; HSC, hematopoietic stem cells; HSPC, hematopoietic stem and progenitor cells; Lympho, lymphoid; Mk, megakaryocytic; Mono, monocytes; MPP, multipotent progenitors; Myelo, myeloid; NK, natural killer cells; Ortho-E, orthochromatic erythroblasts; PC, plasma cells; Poly-E, polychromatophilic erythroblasts; Pre-E, pre-erythrocytes; Pro-E, pro-erythroblasts; Prog, progenitors; T-Lympho, T-lymphocytes; UMAP, uniform manifold approximation and projection.
Figure 3.
Hypomethylating agent therapy inhibits the EIF2AK1-induced response pathway to heme deficiency in terminally differentiated cells in patients who became transfusion independent. A, UMAP plots of scRNA-seq data for pooled single Lin-CD34+ cells isolated from two SF3B1-mutant MDS-RS patients at the time of diagnosis (n = 2,372) and at the time of response to HMA therapy (n = 1,551). Each dot represents one cell. Different colors represent the sample origin (left) and cluster identity (right). B, UMAP plots of scRNA-seq data for pooled single MNCs isolated from three SF3B1-mutant MDS-RS patients at the time of diagnosis (n = 6,089) and response to HMA therapy (n = 6,156). Each dot represents one cell. Different colors represent the sample origin (left) and cluster identity (right). C, Distribution of the stages of erythroid differentiation in the total erythroblast population shown in B at the time of diagnosis (left) and at the time of response to HMA therapy (right). Arrows indicate Ortho-E. D, Pathway enrichment analysis of the genes in the MDS-RS Pro-E, Baso-E, and Poly-E clusters shown B that were significantly downregulated at the time of response to HMA therapy as compared with the time of diagnosis (adjusted P ≤ 0.05). The top 10 Reactome gene sets are shown. E, Pathway enrichment analysis of the genes in the MDS-RS Ortho-E shown in B that were significantly downregulated at the time of response to HMA therapy as compared with the time of diagnosis (P ≤ 0.01). The top 10 Reactome gene sets are shown. Baso-E, basophilic erythroblasts; BFU-E, burst-forming unit-erythroid cells; B-Lympho, B-lymphocytes; CFU-E, colony formation unit-erythroid cells; Ery/Mk, erythroid/megakaryocytic; HSC, hematopoietic stem cells; HSPC, hematopoietic stem and progenitor cells; Lympho, lymphoid; Mk, megakaryocytic; Mono, monocytes; MPP, multipotent progenitors; Myelo, myeloid; NK, natural killer cells; Ortho-E, orthochromatic erythroblasts; PC, plasma cells; Poly-E, polychromatophilic erythroblasts; Pre-E, pre-erythrocytes; Pro-E, pro-erythroblasts; Prog, progenitors; T-Lympho, T-lymphocytes; UMAP, uniform manifold approximation and projection.
Figure 4. Inhibition of EIF2AK1 overcomes the accumulation of RS and enables red blood cell production. A, Representative western blot analysis of EIF2AK1, phospho-EIF2S1, and LC3B in nontargeting (NT) sgRNA– and EIF2AK1 sgRNA–treated SF3B1-mutant MDS-RS cells at day 13 of culture. Vinculin was used as a loading control. B, Frequencies of CD71+CD235a− (left), CD71+CD235a+ (middle), and CD71−CD235a+ (right) erythroblasts in NT sgRNA– or EIF2AK1 sgRNA–treated MDS-RS samples (n = 6) at day 13 of culture. Each symbol represents one sample; lines connect paired samples. Statistical significance was calculated using paired t tests. C, UMAP plots of scRNA-seq data for single cells from NT sgRNA–treated (n = 30,307) or EIF2AK1 sgRNA–treated (n = 36,825) cells from 3 pooled SF3B1-mutant MDS-RS samples at day 13 of erythroid culture. Each dot represents one cell. Different colors represent the sample origin (left) and cluster identity (right). Dotted lines indicate terminally differentiated erythroblasts. D, Distribution of cells from NT (left) and EIF2AK1 (right) sgRNA–treated SF3B1-mutant MDS-RS samples among the clusters shown in C. Arrows indicate clusters 1 and 7.E, Pathway enrichment analyses of the significantly downregulated genes in EIF2AK1 sgRNA–treated SF3B1-mutant MDS-RS cells from clusters 1 (left) and 7 (right; adjusted P ≤ 0.05). The top 10 Reactome or Hallmark gene sets are shown. F, Pathway enrichment analyses of the significantly upregulated genes in EIF2AK1 sgRNA–treated SF3B1-mutant MDS-RS cells from clusters 1 (left) and 7 (right; adjusted P ≤ 0.05). The top 10 Hallmark gene sets are shown.
Figure 4.
Inhibition of EIF2AK1 overcomes the accumulation of RS and enables red blood cell production. A, Representative western blot analysis of EIF2AK1, phospho-EIF2S1, and LC3B in nontargeting (NT) sgRNA– and EIF2AK1 sgRNA–treated SF3B1-mutant MDS-RS cells at day 13 of culture. Vinculin was used as a loading control. B, Frequencies of CD71+CD235a− (left), CD71+CD235a+ (middle), and CD71−CD235a+ (right) erythroblasts in NT sgRNA– or EIF2AK1 sgRNA–treated MDS-RS samples (n = 6) at day 13 of culture. Each symbol represents one sample; lines connect paired samples. Statistical significance was calculated using paired t tests. C, UMAP plots of scRNA-seq data for single cells from NT sgRNA–treated (n = 30,307) or EIF2AK1 sgRNA–treated (n = 36,825) cells from 3 pooled SF3B1-mutant MDS-RS samples at day 13 of erythroid culture. Each dot represents one cell. Different colors represent the sample origin (left) and cluster identity (right). Dotted lines indicate terminally differentiated erythroblasts. D, Distribution of cells from NT (left) and EIF2AK1 (right) sgRNA–treated SF3B1-mutant MDS-RS samples among the clusters shown in C. Arrows indicate clusters 1 and 7.E, Pathway enrichment analyses of the significantly downregulated genes in EIF2AK1 sgRNA–treated SF3B1-mutant MDS-RS cells from clusters 1 (left) and 7 (right; adjusted P ≤ 0.05). The top 10 Reactome or Hallmark gene sets are shown. F, Pathway enrichment analyses of the significantly upregulated genes in EIF2AK1 sgRNA–treated SF3B1-mutant MDS-RS cells from clusters 1 (left) and 7 (right; adjusted P ≤ 0.05). The top 10 Hallmark gene sets are shown.
Figure 5. Proposed model. Under normal physiologic conditions, heme binds to EIF2AK1 and represses its activation. In conditions that limit heme production, such as those induced by SF3B1MT in terminally differentiated erythroblasts, EIF2AK1 is activated. EIF2AK1 pathway activation promotes RS survival and inhibits erythroid maturation by increasing the expression of ATF4, which in turn upregulates the expression of genes involved in autophagy, transcriptionally inhibits genes involved in heme biosynthesis and mitochondrial iron transport, and translationally inhibits globin production. Targeting EIF2AK1 pathway activation by depleting EIF2AK1 rescues erythroid differentiation and red blood cell production.
Figure 5.
Proposed model. Under normal physiologic conditions, heme binds to EIF2AK1 and represses its activation. In conditions that limit heme production, such as those induced by SF3B1MT in terminally differentiated erythroblasts, EIF2AK1 is activated. EIF2AK1 pathway activation promotes RS survival and inhibits erythroid maturation by increasing the expression of ATF4, which in turn upregulates the expression of genes involved in autophagy, transcriptionally inhibits genes involved in heme biosynthesis and mitochondrial iron transport, and translationally inhibits globin production. Targeting EIF2AK1 pathway activation by depleting EIF2AK1 rescues erythroid differentiation and red blood cell production.
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