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Record W2592081749 · doi:10.1182/blood.v120.21.980.980

Dyskerin Is Upregulated During Erythroid Differentiation of Human Hematopoietic Progenitor Cells and Hyperactivates Telomerase in Erythroid Precursor Cells

2012· article· en· W2592081749 on OpenAlexaff
Ashu Kumari, Laura Richards, Georg von Jonquières, Kathy Knezevic, Rosemary O’Brien, Christine E. Napier, Jonathon Marks-Bluth, Hilda A. Pickett, John E. Pimanda, Karen L. MacKenzie

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsOccupational Cancer Research Centre
Fundersnot available
KeywordsTelomeraseTelomerase reverse transcriptaseBiologyTelomereTelomerase RNA componentHaematopoiesisCellular differentiationMolecular biologyMyeloidMyeloid leukemiaStem cellProgenitor cellCD34Cancer researchCell biologyGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Abstract 980 Telomerase is a ribonuclear protein complex that functions to maintain the integrity of chromosomal-end structures (telomeres), and thereby enables continued cell replication. The active telomerase holoenzyme includes telomerase reverse transcriptase (hTERT) as its catalytic core, an RNA component (hTR) that functions as a template for synthesis of telomere repeats and an RNA-modifying protein dyskerin, which stabilizes TERC within the telomerase holoenzyme. While telomerase activity is high in acute myeloid leukemia cells, low levels of telomerase enzyme activity are detected in human CD34+ progenitor cells (HPCs). Telomerase activity is increased by cytokine stimulation of HPCs, then downregulated during myelomonocytic cell differentiation. Data accumulated to date suggest that telomerase enzyme levels are principally determined by Myc-mediated transcriptional regulation of the gene encoding hTERT, although the dyskerin gene (DKC1) is also a known Myc target. Our studies of the regulation and function of telomerase in human myeloid cells utilize cord blood-derived HPCs subject to ex vivo expansion and differentiation along specific myeloid lineages. Our past results revealed for the first time, that in contrast to the repression of telomerase activity observed during granulocytic, monocytic and megakaryocytic differentiation, telomerase activity was upregulated during erythroid differentiation, to reach levels comparable to tumor cell lines in CD34-/Glycophorin A+ erythroid precursor cells (Schuller et al., Leukemia 21: 983–991. 2007). Here we show that the upregulation of telomerase during erythroid differentiation is accompanied by a parallel increase in dyskerin mRNA and protein expression. In contrast to dyskerin expression, but consistent with the pattern of hTERT expression in other myeloid lineages, TERT gene expression was downregulated to a minimally detectable level in erythroid precursor cells. Chromatin-immunoprecipitation revealed that while Myc-binding at the DKC1 promoter decreased, binding of the erythroid-specific transcription factor GATA-1 increased during erythroid differentiation. Overexpression of DKC1 in HPCs confirmed that the upregulation of dyskerin was sufficient to hyperactivate telomerase, while shRNA-mediated depletion of dyskerin from erythroid precursors cells suppressed telomerase activity and decreased expansion of erythroid precursor cells. These data are the first to demonstrate a cellular context in which the upregulation of dyskerin drives telomerase enzyme activity. Further, the results implicate GATA-1 in the regulation of DKC1 transcription and show that high levels of dyskerin are required to sustain proliferation of Glycophorin A+ erythroid precursors. These results have important implications in relation to the pathogenesis of the inherited syndrome dyskeratosis congenita in which the DKC1 gene is mutated, and illustrate a novel mechanism by which telomerase may be reactivated in myeloid leukemia. Disclosures: No relevant conflicts of interest to declare.

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 score0.006

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 integrity0.0000.000
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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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
Published2012
Admission routes1
Has abstractyes

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