MétaCan
Menu
Back to cohort
Record W2982748530 · doi:10.1182/blood-2019-129259

Understanding Pre-Leukemia in Trisomy 21 Human HSC and Modeling Progression Towards Down Syndrome Associated Leukemia Using CRISPR/Cas9 at Single Cell Resolution

2019· article· en· W2982748530 on OpenAlexaff
Elvin Wagenblast, Olga I. Gan, Maria Azkanaz, Sabrina Smith, Joana Araújo, Lorien Shakib, Jessica McLeod, Gabriela Krivdova, Johann Hitzler, Eric R. Lechman, John E. Dick

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsUniversity of TorontoHospital for Sick ChildrenPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsGATA1LeukemiaBiologyAcute megakaryoblastic leukemiaCancer researchHaematopoiesisTrisomyChildhood leukemiaDown syndromeGeneticsStem cell

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.269
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueBloodSame topicRenal and related cancersFrench-language works237,207