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Record W4389243692 · doi:10.1182/blood-2023-189336

Forward Genetic Screen Implicates Drivers of Leukemic Progression in a Novel Model of <i>Trp53 R270H</i> myelodysplastic Syndrome

2023· article· en· W4389243692 on OpenAlexaff
Daniel Chang, Klara E. Noble-Orcutt, Wendy A. Hudson, Aishwarya Iyer, Emily J. Pomeroy, Craig E. Eckfeldt, Aaron L. Sarver, Nuri A. Temiz, Michael A. Linden, Chad L. Myers, David A. Largaespada, Zohar Sachs

Bibliographic record

VenueBlood · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiologyTransposaseGeneticsInsertional mutagenesisSleeping Beauty transposon systemTransposable elementCancer researchMutationMutagenesisMyeloidGeneGenome

Abstract

fetched live from OpenAlex

Myelodysplastic syndrome (MDS) is characterized by bone marrow failure and a highly variable clinical course. The most catastrophic complication of MDS is transformation to secondary acute myeloid leukemia (sAML). Notably, mutations in TP53 confer the single highest risk of transformation to sAML and death. However, some patients with TP53 mutated MDS do not develop sAML, suggesting that additional genetic events cooperate with TP53 mutations to transform MDS to sAML. Understanding the mechanisms of transformation of MDS to sAML could provide targets for therapeutic intervention. To model the genetics of MDS, we crossed mice bearing Trp53 R270H ( Trp53 is the murine TP53 gene) and deletion of genes syntenic with human chromosome 5q (del(5q)). To discover how additional mutations contribute to disease progression, we utilized Sleeping Beauty (SB) transposon mutagenesis in Trp53 R270H/del(5q) mice. SB transposase mobilized SB mutagenic T2/Onc transposons which randomly insert within the genome. T2/Onc transposons are designed to induce gain or loss of function alterations depending on the site and orientation of insertion with respect to targeted genes. We used the Mx1-Cre transgene to activate SB transposase and T2/Onc transposition in hematopoietic progenitors. Trp53 R270H anddel(5q)(or cytogenetically normal, CN) mice were crossed to SB mice to generate donor mice of the following genotypes: Trp53 R270H/del(5q)/ SB, Trp53 R270H/CN /SB, Trp53 WT/del(5q)/ SB, Trp53 WT/CN/ SB mice, and mice without SB transposition, (no transposition, NT: Trp53 R270H/del(5q) /NT). Bone marrow cells were transplanted into recipients, and SB insertional mutagenesis was activated using pI-pC to activate Cre. Mice receiving Trp53 WT/CN/ SB bone marrow developed more frequent T-cell leukemia (n=3/10) than myeloid leukemia (n=1/10). In contrast, mice receiving Trp53 R270H/del(5q)/SB and Trp53 R270H/CN /SB bone marrow developed predominantly myeloid leukemia (n=14/28) more commonly than T-cell leukemia (1/28). Mixed phenotype leukemia was seen in 7/28 of these mice. Together, these data demonstrate a strong bias towards myeloid disease in SB-mutagenized Trp53 R270H bone marrow. To identify genes with SB insertions, we performed RNA sequencing to detect SB T2/Onc transposon-endogenous genefusion transcripts. Among Trp53 WT/CN/ SB leukemias, the most common recurrent SB fusions involved Notch1 and Ikzf1 as has previously reported for SB-associated T-cell leukemias . Among Trp53 R270H/del(5q)/SB and Trp53 R270H/CN /SB leukemias, the most common recurrent SB-fusions involved Erg, Eras and Il2rb with Erg fusions detected 85% of Trp53 R270H leukemias (n=17/20). SB inserted upstream of Erg promoter indicating that these fusions likely upregulate expression of Erg. Indeed, Erg levels are significantly higher in leukemias that express SB-Erg fusions relative to leukemias that do not (p<0.0023). ERG is not recurrently mutated in human AML, but the ERG gene locus is commonly amplified, especially TP53 mutant AML. ERG is known to support normal hematopoietic stem cell self-renewal. Notably, Erg-insertions were also detected in a model of MDS expressing stabilized cyclin E with SB-mediated progression to erythroleukemia (Loeb 2019). Using gene set enrichment analysis, we found that hematopoietic stem cell and leukemic stem cell signatures are enriched in Erg-SB fusion leukemias. In our analyses of two independent data sets (TCGA and BEAT AML), stem cell signatures are also among the most highly enriched pathways in human AMLs expressing high ERG levels. Furthermore, in a human AML single cell RNA sequencing dataset (van Galen 2019), we found that ERG expression is highest in AML cells with the most immature stem and progenitor-like features. Together, these findings implicate a role for ERG as a driver of progression of MDS to AML by enhancing aberrant self-renewal. In summary, we present a novel murine model of Trp53/del(5q) MDS. In this model, Erg upregulation is associated with progression to AML and upregulation of leukemia stem cell gene expression profiles. These data implicate ERG as a major contributor to progression of MDS to secondary AML in the setting of mutant p53. Understanding the mechanisms of disease progression and self-renewal in myeloid malignancies with p53 mutations is critical to define effective therapeutic strategies in these rapidly fatal, treatment resistant diseases.

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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.241
Teacher spread0.230 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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