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Record W3118088258 · doi:10.3324/haematol.2020.271619

Epigenetic changes in human model KMT2A leukemias highlight early events during leukemogenesis

2020· article· en· W3118088258 on OpenAlexafffund
Thomas Milan, Magalie Celton, Karine Lagacé, Élodie Roques, Safia Safa-Tahar-Henni, Eva Bresson, Anne Bergeron, Josée Hébert, Soheil Meshinchi, Sonia Cellot, Frédéric Barabé, Brian T. Wilhelm

Bibliographic record

VenueHaematologica · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineHôpital Maisonneuve-RosemontUniversité de MontréalUniversité LavalCentre hospitalier de l'Université LavalHôpital de l'Enfant-JésusInstitute for Research in Immunology and Cancer
FundersUniversité de MontréalCHU Sainte-Justine FoundationMolson Foundation
KeywordsBiologyEpigeneticsEpigenomeGeneticsCancer researchDNA methylationChromatinRegulation of gene expressionEpigenomicsTranscription factorDemethylaseHistoneGene expressionGene

Abstract

fetched live from OpenAlex

Chromosomal translocations involving KMT2A gene are one of the most common genetic alterations found in pediatric acute myeloid leukemias (AML) although the molecular mechanisms that initiate the disease remain incompletely defined. To elucidate these initiating events we have used a human model system of AML driven by the KMT2A-MLLT3 (KM3) fusion. More specifically, we investigated changes in DNA methylation, histone modifications, and chromatin accessibility at each stage of our model system and correlated these with expression changes. We observe the development of a profound hypomethylation phenotype in the early stages of leukemic transformation after KM3 addition along with loss of expression of stem cell associated genes along with skewed expression in other genes such as S100A8/9 implicated in leukemogenesis. In addition, early increases in the expression of the lysine demethylase KDM4B was functionally linked to these expression changes as well as other key transcription factors. Remarkably, our ATAC-seq data showed that there were relatively few leukemiaspecific changes and the vast majority corresponded to open chromatin regions and transcription factor clusters previously observed in other cell types. Integration of the gene expression and epigenetic changes revealed the adenylate cyclase gene ADCY9 as an essential gene in KM3-AML, and suggest the potential for autocrine signalling through the chemokine receptor CCR1 and CCL23 ligand. Together, our results suggest that KM3 induces subtle changes in the epigenome while co-opting the normal transcriptional machinery to drive leukemogenesis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.196
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.055
GPT teacher head0.300
Teacher spread0.245 · 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 teacher head, not a consensus.

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

Citations21
Published2020
Admission routes2
Has abstractyes

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