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Notch Signaling Represses Mir-223 in T-Cell Acute Lymphoblastic Leukemia

2011· article· en· W2979306928 on OpenAlexaff
Samuel Gusscott, Florian Kuchenbauer, Andrew P. Weng

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsNotch signaling pathwayJurkat cellsBiologymicroRNAHES1Signal transductionCancer researchLeukemiaGene expression profilingCell biologyT cellMolecular biologyGene expressionImmunologyGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Abstract 4630 T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive cancer of immature T cells that often shows aberrant activation of the Notch1 signaling pathway. Several studies have utilized mRNA expression profiling to identify downstream mediators of oncogenic Notch signaling in this context. Since microRNAs (miRNAs) have in recent years been shown to play important roles in hematological maliganancy, we performed a microarray-based screen for Notch-dependent miRNA expression in T-ALL. Jurkat and P12-Ichikawa cell lines were treated with gamma-secretase inhibitor to block Notch signaling vs. DMSO control for 4 days and profiled using Exigon miRCURY LNA miRNA microarrays. Surprisingly few miRNAs were found to be regulated by this approach; however, one of the hits, miR-223, showed consistent upregulation after gamma-secretase treatment in Jurkat cells and 5 additional human T-ALL cell lines assessed by miRNA qPCR. This observation was unique to human T-ALL as murine models of T-ALL showed no evidence for Notch-dependent miR-223 expression. Given that canonical Notch signaling results in transcriptional activation, our observation that Notch signaling is associated with reduced miR-223 expression suggests an intermediary repressor may be involved. miR-223 has been reported to play an important role in normal granulopoiesis, to be expressed relatively highly in T-ALL with myeloid-like gene features, and most recently to accelerate Notch-mediated T-cell leukemogenesis. To explore potential functional consequences for Notch-dependent miR-223 repression in T-ALL, candidate miR-223 targets identified by TargetScan software were analyzed with Ingenuity Pathway Analysis software, which indicated IGF-1, insulin receptor, PTEN, and ERK5 signaling pathways as the top hits. We recently reported IGF1R signaling to be important for growth and viability of bulk T-ALL cells as well as for leukemia-initiating cell activity. Additionally, we reported that Notch signaling directly upregulates IGF1R transcription by binding to an intronic enhancer which is present between exons 21/22 in the human, but not mouse IGF1R locus. As miR-223 has previously been reported to target IGF1R mRNA and reduce its translation, we hypothesized that Notch signaling may also upregulate net IGF1R protein expression by repressing miR-223. To test this hypothesis, we transduced several human T-ALL cell lines with miR-223 retrovirus and observed a modest decrease in total IGF1R protein levels by western blot; however, no significant change was observed in surface IGF1R levels as assessed by flow cytometry. Addtionally, knockdown of miR-223 by lentiviral expression miR-223 target sequences (miR-223 “sponge”) resulted in modestly increased total IGF1R protein levels, but again showed no demonstrable effect on surface IGF1R levels. Of note, we also observed no apparent effect of either overexpression or knockdown of miR-223 on bulk cell growth or viability. We interpret these findings to suggest that Notch signaling does not have major effects on the miR transcriptome, and that up- or down-modulation of miR-223 in established T-ALL cells does not have significant effects on overall cell growth/viability. Further studies will be required to determine if miR-223 may act in concert with other Notch target genes to modulate cell physiology. 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 score0.005

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 head0.042
GPT teacher head0.279
Teacher spread0.238 · 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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Citations2
Published2011
Admission routes1
Has abstractyes

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