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Record W4387458316 · doi:10.3390/genes14101916

The Small-Molecule E26-Transformation-Specific Inhibitor TK216 Attenuates the Oncogenic Properties of Pediatric Leukemia

2023· article· en· W4387458316 on OpenAlexaff
Ritul Sharma, Chunfen Zhang, Aru Narendran

Bibliographic record

VenueGenes · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLeukemiaCytotoxic T cellCancer researchMyeloid leukemiaHaematopoiesisLymphoid leukemiaApoptosisPriming (agriculture)VenetoclaxMyeloidBone marrowBiologyImmunologyChemistryCell biologyStem cellBiochemistryChronic lymphocytic leukemiaIn vitro

Abstract

fetched live from OpenAlex

The E26-transformation-specific (ETS) transcription factors regulate multiple aspects of the normal hematopoietic system. There is an increasing body of evidence suggesting aberrant ETS activity and its contribution to leukemia initiation and progression. In this study, we evaluated the small-molecule ETS inhibitor TK216 and demonstrated its anti-tumor activity in pediatric leukemia. We found TK216 induced growth inhibition, cell cycle arrest and apoptosis and inhibited the migratory capability of leukemic cells, without significantly inhibiting the cell viability of normal blood mononuclear cells. Priming the leukemic cells with 5-Azacitidine enhanced the cytotoxic effects of TK216 on pediatric leukemia cells. Importantly, we found purine-rich box1 (PU.1) to be a potential target of TK216 in myeloid and B-lymphoid leukemic cells. In addition, TK216 sharply decreased Mcl-1 protein levels in a dose-dependent manner. Consistent with this, TK216 also potentiated the cytotoxic effects of Bcl-2 inhibition in venetoclax-resistant cells. The sustained survival benefit provided to leukemic cells in the presence of bone-marrow-derived conditioned media is also found to be modulated by TK216. Taken together, our data indicates that TK216 could be a promising targeted therapeutic agent for the treatment of acute myeloid and B-lymphoid leukemia.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.047
GPT teacher head0.271
Teacher spread0.224 · 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 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

Citations4
Published2023
Admission routes1
Has abstractyes

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