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Record W4401744308 · doi:10.1002/hem3.116

RNA binding protein‐directed control of leukemic stem cell evolution and function

2024· review· en· W4401744308 on OpenAlexafffund
Pratik Joshi, Ava Keyvani Chahi, Lina Liu, Steven Moreira, Ana Vujovic, Kristin J. Hope

Bibliographic record

VenueHemaSphere · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersOntario Institute for Cancer ResearchPrincess Margaret Cancer Foundation
KeywordsHaematopoiesisStem cellBiologyMyeloid leukemiaRNA-binding proteinMyeloidHematopoietic stem cellLeukemiaFunction (biology)DiseaseTranscriptomeRNAComputational biologyCancer researchImmunologyGeneGene expressionGeneticsMedicineInternal medicine

Abstract

fetched live from OpenAlex

Strict control over hematopoietic stem cell decision making is essential for healthy life-long blood production and underpins the origins of hematopoietic diseases. Acute myeloid leukemia (AML) in particular is a devastating hematopoietic malignancy that arises from the clonal evolution of disease-initiating primitive cells which acquire compounding genetic changes over time and culminate in the generation of leukemic stem cells (LSCs). Understanding the molecular underpinnings of these driver cells throughout their development will be instrumental in the interception of leukemia, the enabling of effective treatment of pre-leukemic conditions, as well as the development of strategies to target frank AML disease. To this point, a number of precancerous myeloid disorders and age-related alterations are proving as instructive models to gain insights into the initiation of LSCs. Here, we explore this myeloid dysregulation at the level of post-transcriptional control, where RNA-binding proteins (RBPs) function as core effectors. Through regulating the interplay of a myriad of RNA metabolic processes, RBPs orchestrate transcript fates to govern gene expression in health and disease. We describe the expanding appreciation of the role of RBPs and their post-transcriptional networks in sustaining healthy hematopoiesis and their dysregulation in the pathogenesis of clonal myeloid disorders and AML, with a particular emphasis on findings described in human stem cells. Lastly, we discuss key breakthroughs that highlight RBPs and post-transcriptional control as actionable targets for precision therapy of AML.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score0.811

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.271
Teacher spread0.254 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2024
Admission routes2
Has abstractyes

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