MétaCan
Menu
← Back to cohort

Single Cell-Resolution Analysis of HSC Dysfunction in <i>Mir-146a</i> knockout Mice

2017· article· en· W2972879138 on OpenAlexaff
Jennifer M. Grants, Joanna Węgrzyn, David J. H. F. Knapp, Tony Hui, Kieran O’Neill, Jeremy Parker, Deborah Deng, Mark Boldin, Martin Hirst, Connie J. Eaves, Aly Karsan

Bibliographic record

VenueBlood · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity of British ColumbiaCanada's Michael Smith Genome Sciences CentreBC Cancer AgencyTerry Fox Research Institute
Fundersnot available
KeywordsStem cellBiologyHaematopoiesisHematopoietic stem cellProgenitor cellPopulationCancer researchTransplantationImmunologyMyeloidCell biologyInternal medicineMedicine

Abstract

fetched live from OpenAlex

Abstract MicroRNA miR-146a is frequently depleted in myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Loss of miR-146a may be an initiating event in tumorigenesis, as miR-146a loss in mouse models is sufficient to cause features of MDS and eventual progression to AML. To define how miR-146a loss initiates tumorigenesis, we analyzed hematopoietic stem cell (HSC) function from miR-146a knockout (KO) mice prior to onset of an overt malignant phenotype. Tracking cell division kinetics, proliferation, and differentiation of single long-term HSC (LT-HSC; EPCR+CD45+CD48-CD150+) in culture, we found evidence that miR-146a KOreduces HSC quiescence and promotes differentiating cell divisions. Our data show that miR-146a KO HSC dysfunction may stem from loss of a CD150-bright EPCR-bright sub-population, which has previously been associated with robust HSC activity. In line with this, single cell DNA methylation profiling revealed a reduction in a primitive sub-population of LT-HSCs in miR-146a KO animals. In addition, single cell LT-HSC transplants revealed a myeloid repopulation bias. As reduced HSC cell cycle quiescence has been linked to impaired HSC self-renewal upon hematopoietic stress, such as serial transplantation, we assessed the frequency of serially transplantable HSCs by performing secondary transplants with limiting dilution. Serially transplantable HSC frequency was reduced in miR-146a KO compared to wild type, suggesting impaired HSC self-renewal. Transcriptome profiling of miR-146a KO hematopoietic stem and progenitor cells identified tumor necrosis factor (TNF) signaling activation as a potential driver of HSC dysfunction. LT-HSC cell cycle quiescence and the CD150-bright EPCR-bright LT-HSC sub-population were restored in miR-146a/TNF double KO mice, suggesting that aberrant TNF signaling activation drives HSC dysfunction upon loss of miR-146a. Gene expression levels in the TNF signaling network are inversely correlated with miR-146a levels in human AML, implying that TNF signaling may similarly disrupt HSC function in miR-146a- depleted myeloid malignancies. Overall, our findings suggest that miR-146a promotes HSC cell cycle quiescence and inhibits differentiation by antagonizing TNF signaling, in order to maintain a primitive sub-population of long-term self-renewing HSCs. Disclosures Eaves: Experimental Hematology: Other: Editor of journal; StemCell Technologies Inc: Other: Wife of owner.

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 score0.002
Threshold uncertainty score0.008

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueBlood→Same topicMicroRNA in disease regulation→French-language works237,207→