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Record W2616791438 · doi:10.14288/1.0343276

Insights into leukemogenesis in a MN1-induced leukemia model

2017· article· en· W2616791438 on OpenAlexaff
Courteney K. Lai

Bibliographic record

VenuecIRcle (University of British Columbia) · 2017
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLeukemiaComputer scienceMedicineImmunology

Abstract

fetched live from OpenAlex

Acute myeloid leukemia (AML) spans a wide array of distinct clinical entities and likely molecular determinants. Despite early treatment success, many aspects of leukemogenesis remain poorly understood, including determinants of leukemic phenotype and identity, and genes and pathways critical to leukemic stem cell (LSC) function. Meningioma 1 (MN1) is a transcriptional co-factor that is an independent prognostic marker for normal karyotype AML, with high expression linked to poor survival and resistance to treatment by ATRA-induced differentiation. MN1 is also a potent and sufficient oncogene in murine leukemia, able to block differentiation and promote LSC self-renewal through transformation of cells at the common myeloid progenitor level. Using this single-hit oncogenic model, MN1 overexpression was exploited to gain further insight into the leukemic process. The objective of this thesis work was to identify and better understand key regulators in LSC function. Sixteen MN1 structural variants were generated to investigate if the leukemic properties of increased proliferation and self-renewal, arrested hematopoietic differentiation, in vivo leukemogenic activity, and resistance to all-trans retinoic acid-induced differentiation could be localised to specific protein regions. Functional assays revealed that the MN1 C-terminus is critical for blocking myeloid and lymphoid differentiation and ATRA resistance while the N-terminus is essential for leukemogenicity, proliferation and self-renewal, and arrested erythro-megakaryocyte differentiation, demonstrating that these leukemic properties can be attributed to specific and largely distinct regions. To identify key genes and pathways underlying leukemic activity, the phenotypic heterogeneity of MN1 leukemic cells was functionally assessed, revealing leukemic and non-leukemic subsets. Gene expression profiling of these subsets was combined with previously-published datasets comparing wildtype leukemic MN1 and mutant versions with varying leukemogenic activity to identify candidate genes critical to leukemia. Through functional analysis of leukemic properties, Hlf and HoxA9 were identified as critical to in vitro proliferation, self-renewal, and impaired myeloid differentiation in MN1 leukemia. Furthermore, this work identifies Meis2 as a novel player in MN1-induced leukemia, with essential roles in proliferation, self-renewal, differentiation, and apoptosis. Together, these models provide a platform to unravel the basis for dysregulated gene expression associated with leukemia and to probe the cellular and molecular determinants of 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 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 score0.004

Distilled classifier scores by category (both heads)

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

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 head0.021
GPT teacher head0.233
Teacher spread0.212 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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