Understanding Pre-Leukemia in Trisomy 21 Human HSC and Modeling Progression Towards Down Syndrome Associated Leukemia Using CRISPR/Cas9 at Single Cell Resolution
Notice bibliographique
Résumé
Leukemia is the most common cancer in children. Sequencing data from identical twins suggests that the first genetic alterations in childhood leukemia occur in utero. Children with Down syndrome (Trisomy 21, T21) have an increased risk of childhood leukemia. In 30% of newborns with Down syndrome, a transient pre-leukemia disease occurs, which is characterized by a clonal proliferation of immature megakaryocytes carrying somatic mutations in the GATA1 transcription factor. These acquired GATA1 mutations lead to the expression of an N-terminal truncated protein (GATA1-Short). In 20% of the cases, acute megakaryoblastic leukemia (AMKL) evolves from the pre-leukemia by acquisition of additional genetic mutations in the transient leukemia clone, predominantly in genes of the cohesin complex. It is hypothesized that this represents a multi-step process of leukemogenesis with three distinct genetic events: T21, GATA1-Short and additional cohesin mutations. Yet, it remains unclear how an extra copy of chromosome 21 predisposes towards leukemia, the mechanisms of leukemic transformation and the interplay between each genetic component. Therefore, we wanted to establish a tractable human model system to investigate the initiation and evolution of transient leukemia and AMKL using CRISPR/Cas9 genome editing in primary human hematopoietic stem cells (HSCs). To model the initiation of Down syndrome associated pre-leukemia, we utilized both neonatal cord blood and fetal liver derived LT-HSCs and other progenitor populations to express either the short or long isoform of GATA1 (GATA1-Short or GATA1-Long). This was carried out using an improved methodology that permits the in vitro and in vivo functional interrogation of CRISPR/Cas9 edited human LT-HSCs at the single cell level (Wagenblast et al., bioRxiv 609040). Importantly, in this case, expression of either GATA1 isoform remained under the regulatory control of the endogenous promoter. Culture of single LT-HSC, short-term (ST-HSC) and myelo-erythroid progenitors (MEP) revealed a drastic shift towards megakaryocytic lineage output upon exclusive expression of GATA1-Short compared to control or GATA1-Long, regardless of the developmental source of the derived cells. To investigate the functional consequences of exclusive GATA1-Short expression in LT-HSCs in vivo, we performed near-clonal xenotransplantation assays in NSG and NSGW41 mice. Strikingly, GATA1-Short edited LT-HSCs injected mice displayed a higher percentage of human CD41+CD45- megakaryocytic lineage derived cells and a decrease in human GlyA+CD45- erythroid cells compared to control. Morphological analysis revealed more immature forms of erythroid cells and fewer enucleated erythrocytes in GATA1-Short edited LT-HSCs injected mice. In order to add an additional genetic determinant to our model, we utilized T21 fetal liver derived LT-HSCs. Un-manipulated T21 LT-HSCs and other progenitor populations showed a bias towards erythroid, myeloid and megakaryocytic lineages at the expense of lymphoid fates. In vitro, the combination of T21 and CRISPR/Cas9-mediated GATA1-Short in LT-HSCs led to an increase in megakaryocytic lineage output, while decreasing erythroid output. This phenotype was similar to what was observed in normal karyotype fetal liver derived LT-HSCs. However, near clonal transplantation of GATA1-Short edited T21 LT-HSCs in NSG mice generated exclusive CD33+ myeloid grafts with disproportionate high levels of CD41+CD45- megakaryocytic lineage derived cells compared to T21 control. In addition a distinct CD34+CD41+CD71+CD45+ population was present. Thus, this phenotype is reminiscent of Down Syndrome associated transient leukemia. In summary, by using an improved CRISPR/Cas9 single cell methodology we show how GATA1 regulates lineage fate in normal and T21 LT-HSCs and other progenitor populations. Importantly, we show for the first time a humanized mouse model of Down syndrome associated transient leukemia, which was induced from T21 human fetal liver derived LT-HSCs engineered to express GATA1-Short. Current studies focus on adding additional mutations of the cohesin complex to progress transient leukemia to AMKL. Disclosures No relevant conflicts of interest to declare.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».