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DNMT3a Mutations Define a Pre-Leukemic Stem Cell Reservoir In Human Acute Myeloid Leukemia

2013· article· en· W951605309 on OpenAlexaff
Liran I. Shlush, Sasan Zandi, Amanda Mitchell, Weihsu Claire Chen, McLeod Jessica, Monica Doedens, Medeiros Jessie, René Marke, McPherson J John, Thomas J. Hudson, Brown Andrew, Trinh M Quang, Lincoln Stein, James A. Kennedy, Mark D. Minden, Jean Wang, John E. Dick

Bibliographic record

VenueBlood · 2013
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsOntario Institute for Cancer ResearchPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMyeloid leukemiaNPM1Sanger sequencingLeukemiaBiologyMutationCancer researchHaematopoiesisStem cellMyeloidMolecular biologyImmunologyGeneGeneticsKaryotypeChromosome

Abstract

fetched live from OpenAlex

Abstract Leukemia in humans arises from the multistep accumulation of mutations. However, the identity of the cell of origin, the nature of the first genetic lesion and the order of subsequent mutations remain poorly understood, as most cases of de novo acute myeloid leukemia (AML) are diagnosed without prior observation of a pre-leukemic clonal expansion. As part of studies to examine intra-tumoral genetic heterogeneity in AML, we carried out deep targeted sequencing (read depth 250×) of 101 commonly mutated leukemia genes on samples from 12 patients at diagnosis. Normal T-cells from each sample were expanded in vitro to provide a non-leukemic hematopoietic tissue for comparison. In 3 of 4 patients, we unexpectedly identified DNMT3a mutation not only in AML cells but also in T-cells at a low allele frequency (1-20%). Other genetic alterations such as NPM1 mutation (mutNPM1) were found only in AML cells and not in T-cells, ruling out contaminating AML cells as the source of the DNMT3a signal in cultured T-cells. To investigate the prevalence of T cell involvement, an additional 71 samples from AML patients at diagnosis were screened by Sanger sequencing for DNMT3a mutations. 17 of 71 AML samples (24%) carried R882 codon mutations (mutDNMT3a), and 15 of 17 (88%) also carried mutNPM1. Mutant allele frequency in freshly isolated T-cells was measured by droplet digital PCR (ddPCR). mutDNMT3a with no evidence of mutNPM1 was detected in T-cells of 12 of 17 patients (70.5%), suggesting that DNMT3a mutation occurs before NPM1 mutation in an ancestral stem/progenitor cell that gives rise to both T-cells and the dominant AML clone present at diagnosis. To directly determine whether phenotypic stem/progenitor cells that carried the mutDNMT3a allele could be identified within the non-leukemic hematopoietic compartment of AML blood and bone marrow samples, we undertook genetic analysis of highly-resolved phenotypically-defined normal stem, progenitor and mature lymphoid cell fractions from 10 patient samples. mutDNMT3a without detectable mutNPM1was present in stem cells and all downstream progenitors, with mean allele frequency among multipotent progenitor (MPP), multilymphoid progenitor (MLP) and common myeloid progenitor (CMP) of 31.7%. mutDNMT3a and mutNPM1 were found together only in granulocyte monocyte progenitor (GMP) and CD33+ blasts. Importantly, even for patients in whom mutDNMT3a was not detected in mature lymphoid populations, mutDNMT3a without mutNPM1 was found in MPP, MLP, CMP, providing strong evidence that mutDNMT3a precedes mutNPM1 during leukemogenesis. Analysis of diagnostic and remission samples revealed similar or higher proportion of cells with mutDNMT3a alone at remission compared to diagnosis. Xenotransplantation of cells from the diagnostic samples of 2 patients with mutDNMT3a and mutNPM1generated predominantly non-leukemic multilineage grafts (18 of 19 mice) with predominance of cells bearing mutDNMT3a without mutNPM1 (mean allele frequency 57%), confirming that mutDNMT3a was present in HSC. Kinetic analysis at 8 and 16 weeks revealed increasing mutDNMT3a allele frequency in multilineage xenografts over time, suggesting that mutDNMT3a confers a competitive growth advantage over non-mutated HSC. Collectively, our results are consistent with the clonal expansion in AML patients of mutDNMT3a HSC that survive chemotherapy. These cells may therefore represent a reservoir for further genomic progression leading to relapse. Our findings now offer the possibility of therapeutic intervention during remission to eliminate these surviving pre-leukemic clones and prevent relapse in a large proportion of AML patients carrying mutDNMT3a. As well, our work provides a framework for the identification of other early events in leukemogenesis and examination of how these changes disrupt normal HSC function and lead to leukemia. Disclosures: Wang: Trillium Therapeutics/Stem Cell Therapeutics: Research Funding.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.280
Teacher spread0.262 · 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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Citations4
Published2013
Admission routes1
Has abstractyes

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