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Record W4417018678 · doi:10.1182/blood-2025-1389

Asxl1 mutant cells suppress Dnmt3a mutant clonal expansion.

2025· article· en· W4417018678 on OpenAlexaff
Apoorva Thatavarty, Marco M. Buttigieg, A. Rosa McDonald, Xiaochen Long, Chen Hu, Zhijian Yu, Katie A. Matatall, Ruoqiong Cao, Brandon Tran, Arushana Maknojia, Belinda Candra, Bryan Bahoua, Arvind Mohan, Marek Kimmel, Michael J. Rauh, Katherine Y. King

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsKingston Health Sciences Centre
Fundersnot available
Keywordsclone (Java method)MutantHaematopoiesisMutationStem cellCellLogistic regressionCell culture

Abstract

fetched live from OpenAlex

Abstract Clonal hematopoiesis (CH) is ubiquitous among people over age 55, and 25% of aged individuals have multiple mutant clones (Fabre, Nature 2022). Most studies of CH have investigated mechanisms of clonal expansion one clone at a time; little is known about how emerging clones impact the expansion of neighboring clones. Prior work showed that HSCs with mutations in DNMT3A, ASXL1 or TET2 (D-A-T), three commonly mutated CH genes, have mutation-specific selective advantage in inflammatory conditions (Florez, Cell Stem Cell 2022). Selective advantage is achieved via enhanced cytokine production paired with mutation-specific mechanisms to survive inflammation, creating a feed-forward loop. We therefore hypothesized that D-A-T mutant clones cooperate to promote each other's expansion. Results Human Genetic Analyses Reveal ASXL1-DNMT3A Antagonism We analyzed co-mutation patterns and clonal dynamics across 4 CH/MDS human cohorts. Contrary to our expectations, across these datasets, we observed a consistent and pronounced mutual exclusivity between DNMT3A and ASXL1 mutations, with the strongest signal in All of Us (observed = 48 vs. expected = 123, p = 6.3×10⁻²⁹, OR = 0.16). DNMT3A-ASXL1 mutual exclusivity ranked among the strongest of all tested driver pairs, including known enriched co-mutations like TET2-JAK2, used to validate our analytic pipeline. Using logistic regression models, we tested whether clone size influenced these dynamics. Increasing ASXL1 VAF was associated with reduced odds of a DNMT3A co-mutation, while increasing DNMT3A VAF had no significant effect on ASXL1 detection. This indicates a directional and dose-dependent suppressive effect. Increased TET2 VAF was positively associated with DNMT3A detection (OR > 1), though these genes rarely co-occurred, hinting at context-dependent interactions. These findings suggest ASXL1 mutant clones suppress DNMT3A clonal expansion, while TET2 may promote it under certain conditions. Murine Models Support Directional Suppression To model these interactions and investigate mechanisms, we generated a 1% mosaic competitive transplant murine model where Dnmt3a-/-, Tet2-/-, and Asxl1-truncation transgene (D-A-T) cells were transplanted alone, pairwise (2x) and all combined (3x). Given most CH murine models use a 10% starting engraftment, we first ascertained whether dynamics differ at a starting engraftment of 1%. We found no difference in the growth curves of D-A-T mutants with a starting clone size of 1% versus 10%, suggesting that mutant clones have a set expansion rate under steady state conditions. In contrast, with chronic inflammatory stress induced by Mycobacterium avium or intermittent low dose LPS, Dnmt3a-/- and Tet2-/-clones, which are reported to have accelerated expansion at a starting engraftment of 10%, did not expand at a 1% starting engraftment. These findings suggest that the power of external inflammatory stimuli to promote clonal expansion is dependent on clone size. Turning to the 2x and 3x transplants, Dnmt3a-/- and Tet2-/- clones promoted each other's expansion when co-occurring as observed in the human data. Notably, Dnmt3a-/- clonal expansion was suppressed in the presence of Asxl1 mutant cells in both the 2x and 3x mosaic models. Statistical modeling revealed a 4% decrease in weekly growth rate for Dnmt3a-/- cells when in competition with Asxl1 mutants. Interestingly, ex vivo competition experiments show Dnmt3a-/- progenitor cells are not directly suppressed by Asxl1 mutant progenitor cells, suggesting terminally differentiated mutant cells likely mediate the suppressive phenotype. In ongoing work, scRNA sequencing data from 1x versus 2x models will identify mechanisms of Asxl1-mediated Dnmt3a suppression. Given known transcriptional differences between these clones (for example, Asxl1-mutant cells survive inflammation by upregulating Socs3a, whereas Dnmt3a mutant cells have lower Socs3a but enhanced p21 to promote survival), we expect to find transcriptional differences that underly this suppressive effect (King, Exp Hem 2021). Conclusion We found that Asxl1 mutant cells suppress Dnmt3a mutant clonal expansion. To our knowledge, this is the first epidemiologic and mechanistic report of intraclonal dynamics that affect early clonal expansion. Given that mutations in DNMT3A account for ~60% of CH, these findings could reveal therapeutic avenues for slowing DNMT3A mutant clonal expansion and reduce overall risk of malignant transformation.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.283
Teacher spread0.271 · 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
Published2025
Admission routes1
Has abstractyes

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