Abstract
Background
Children with Down syndrome (DS) have a high risk for acute myeloid leukemia (DS-ML). Genomic characterization of DS-ML blasts showed the presence of unique mutations in GATA1, an essential hematopoietic transcription factor, leading to the production of a truncated from of GATA1 (GATA1s). GATA1s together with trisomy 21 is sufficient to develop a pre-leukemic condition called transient abnormal myelopoiesis (TAM). Approximately thirty percent of these cases progress into DS-ML by acquisition of additional somatic mutations in a step-wise manner. We previously developed a model for TAM by introducing disease-specific GATA1 mutation in trisomy 21 induced pluripotent stem cells (iPSCs) leading to the production of N-terminally truncated short form of GATA1 (GATA1s) (Barwe et al., 2021). In this study, we introduced co-operating mutation in STAG2, a member of the cohesin complex recurrently mutated in DS-ML but not in TAM, and evaluated its effect on hematopoietic differentiation.
Methods
Two different iPSC lines with trisomy 21 with or without GATA1 mutation as described in Barwe et al., 2021, were used. CRISPR/Cas9 gene editing was performed to introduce STAG2 mutation to generate a knockout of STAG2. Hematopoietic differentiation of these iPSC lines was performed using STEMdiff Differentiation kit. ProteinSimple Wes system was used for western blot analysis. Multi-dimensional flow cytometry was used for immunophenotypic analysis of megakaryoblasts cultured in lineage expansion media for 5 days. Multi-lineage colony forming potential was assessed by Methocult colony forming assay using day 10 hematopoietic stem progenitor cells (HSPCs).
Results
Hematopoietic differentiation of GATA1 and STAG2 double mutants in two independent trisomy 21 iPSC lines confirmed GATA1s expression and the loss of functional STAG2 protein (Fig. 1A). GATA1s expressing HSPCs collected on day 12 post differentiation showed reduced erythroid (CD71+CD235+) and increased megakaryoid (CD34+CD41+ within CD41+ compartment) and myeloid (CD18+CD45+) population compared to disomy 21 HSPCs with wild-type GATA1, consistent with our previous study (Fig. 2B). STAG2 knockout HSPCs showed higher erythroid population (P=0.033 and 0.016 in T21-1S and T21-2S respectively) and reduced myeloid population while it had no significant effect on the megakaryoid population in both iPSC lines. The GATA1s/STAG2 knockout HSPCs showed reduced erythroid, but higher megakaryoid and myeloid population compared to wild-type HSPCs. Strikingly, the immature megakaryoid population was significantly higher in the double mutant HSPCs compared to single mutant alone in both iPSC lines (P=0.005 and 0.004 for T21-1GS and T21-2GS respectively), indicating that the STAG2knockout co-operated with GATA1s for increasing megakaryoid population.
The trisomy 21 iPSC line with wild-type GATA1 developed CFU-GEMM (colony-forming unit granulocyte erythroid macrophage megakaryocyte), CFU-GM (CUF granulocyte-macrophage) and BFU-E (burst-forming unit erythroid) colonies in Methocult. GATA1 mutation, unlike STAG2 mutation, inhibited the formation of CUF-GEMM and BFU-E colonies. The number of CFU-GM colonies in T21-2GS was significantly reduced compared to T21-2G (Fig. 1C, p=0.002). Lineage expansion and immunophenotyping of these HSPCs in megakaryocyte-specific media showed that these cells expressed markers closely resembling DS-ML immunophenotype. Of note, the myeloid markers, CD13 and CD11b are the only two markers expressed on majority of DS-ML blasts compared to TAM blasts (Karandikar et al., 2001) (Yumura-Yagi et al., 1992). The percentage of CD13 and CD11b expressing cells was higher in megakaryoblasts expanded from iPSC lines with STAG2 GATA1 double mutant (Fig. 1D). The number of cells expressing CD117, a stem cell marker shown recently to be involved in DS-ML progression, were highest in T21-1GS and T21-2GS lines when compared to their respective isogenic family of GATA1 mutant lines.
Conclusion
GATA1s and STAG2 knockout co-operated to increase the megakaryoid population and the percentage of cells expressing DS-ML markers. We have developed a model system representing DS-ML, which can be used for understanding the individual and synergistic contribution of these gene mutations in disease initiation and progression.
Barwe: Prelude Therapeutics: Research Funding. Gopalakrishnapillai: Geron: Research Funding.
