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Record W1606487633 · doi:10.18632/oncotarget.4111

Jak3, STAT3, and STAT5 inhibit expression of miR-22, a novel tumor suppressor microRNA, in cutaneous T-Cell lymphoma

2015· article· en· W1606487633 on OpenAlexaffabout
Nina A. Sibbesen, Katharina Kopp, Ivan V. Litvinov, Lars Jønson, Andreas Willerslev-Olsen, Simon Fredholm, David L. Petersen, Claudia Nastasi, Thorbjørn Krejsgaard, Lise M. Lindahl, Robert Gniadecki, Nigel P. Mongan, Denis Sasseville, Mariusz A. Wasik, Lars Iversen, Charlotte M. Bonefeld, Carsten Geisler, Anders Woetmann, Niels Ødum

Bibliographic record

VenueOncotarget · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and Retrovirus Studies
Canadian institutionsMcGill University Health Centre
FundersH. Lundbeck A/SNovo Nordisk FondenLundbeckfondenKræftens Bekæmpelse
KeywordsmicroRNACancer researchSuppressorSTAT5STAT3LymphomaMedicineImmunologyBiologyCell cultureSignal transductionCancerGeneCell biologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

// Nina A. Sibbesen 1 , Katharina L. Kopp 1 , Ivan V. Litvinov 2 , Lars Jønson 3 , Andreas Willerslev-Olsen 1 , Simon Fredholm 1 , David L. Petersen 1 , Claudia Nastasi 1 , Thorbjørn Krejsgaard 1 , Lise M. Lindahl 4 , Robert Gniadecki 5 , Nigel P. Mongan 6 , Denis Sasseville 2 , Mariusz A. Wasik 7 , Lars Iversen 4 , Charlotte M. Bonefeld 1 , Carsten Geisler 1 , Anders Woetmann 1 and Niels Odum 1 1 Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark 2 Division of Dermatology, McGill University Health Centre, Montréal, Quebec, Canada 3 Departmen of Molecular Medicine, Copenhagen University Hospital (Rigshospitalet), Copenhagen, Denmark 4 Department of Dermatology, Aarhus University Hospital, Skejby, Aarhus, Denmark 5 Departmen of Dermatology, Copenhagen University Hospital, Bispebjerg, Copenhagen, Denmark 6 Faculty of Medicine and Health Science, School of Veterinary Medicine and Science, University of Nottingham, Loughborough, United Kingdom 7 Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA Correspondence to: Niels Odum, email: // Keywords : miR-22, cutaneous T-cell lymphoma (CTCL), mycosis fungoides (MF), STAT3, STAT5, JAK3 Received : March 09, 2015 Accepted : April 22, 2015 Published : May 12, 2015 Abstract Aberrant activation of Janus kinase-3 (Jak3) and its key down-stream effectors, Signal Transducer and Activator of Transcription-3 (STAT3) and STAT5, is a key feature of malignant transformation in cutaneous T-cell lymphoma (CTCL). However, it remains only partially understood how Jak3/STAT activation promotes lymphomagenesis. Recently, non-coding microRNAs (miRNAs) have been implicated in the pathogenesis of this malignancy. Here, we show that (i) malignant T cells display a decreased expression of a tumor suppressor miRNA, miR-22, when compared to non-malignant T cells, (ii) STAT5 binds the promoter of the miR-22 host gene, and (iii) inhibition of Jak3, STAT3, and STAT5 triggers increased expression of pri-miR-22 and miR-22. Curcumin, a nutrient with anti-Jak3 activity and histone deacetylase inhibitors (HDACi) also trigger increased expression of pri-miR-22 and miR-22. Transfection of malignant T cells with recombinant miR-22 inhibits the expression of validated miR-22 targets including NCoA1, a transcriptional co-activator in others cancers, as well as HDAC6, MAX, MYCBP, PTEN, and CDK2, which have all been implicated in CTCL pathogenesis. In conclusion, we provide the first evidence that de-regulated Jak3/STAT3/STAT5 signalling in CTCL cells represses the expression of the gene encoding miR-22, a novel tumor suppressor miRNA.

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 communication0.0010.000
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 head0.014
GPT teacher head0.226
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

Citations83
Published2015
Admission routes2
Has abstractyes

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