MétaCan
Menu
Back to cohort
Record W4387736032 · doi:10.21203/rs.3.rs-3443273/v1

Small molecule STAT3/5 inhibitors exhibit therapeutic potential in acute myeloid leukemia and extra-nodal natural killer/T cell lymphoma

2023· preprint· en· W4387736032 on OpenAlexaff
Daniel Pölöske, Helena Sorger, Anna Schönbichler, Elvin D. de Araujo, Heidi A. Neubauer, Anna Orlova, Sanna Timonen, Diaaeldin I. Abdallah, Aleksandr Ianevski, Heikki Kuusanmäki, Marta Surbek, Christina Wagner, Tobias Suske, Martin Metzelder, Michael Bergmann, Maik Dahlhoff, Florian Grebien, Roman Fleck, Christine Pirker, Walter Berger, Emir Hadzijusufovic, Wolfgang R. Sperr, Lukas Kenner, Peter Valent, Tero Aittokallio, Marco Herling, Satu Mustjoki, Patrick T. Gunning, Richard Moriggl

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsUniversity of Toronto
FundersAustrian Science FundEuropean Commission
KeywordsCancer researchBiologyTyrosine kinaseMyeloidMyeloid leukemiaViability assaySTAT3PIM1OncogeneCell cycleCellSignal transductionCell biologyGeneticsPhosphorylation

Abstract

fetched live from OpenAlex

Abstract Background: The oncogenic transcription factors STAT3, STAT5A and STAT5B are essential to steer hematopoiesis and immunity, but their enhanced expression and activation drives the development or progression of blood cancers, such as AML and NKCL. Current therapeutic strategies to inhibit STAT3/5 activity focus on blocking upstream tyrosine kinases, but frequently occurring resistance often leads to disease relapse, emphasizing the need for new STAT3/5 targeted therapies. Methods: Cytotoxicity assays were used to assess the impact of our STAT3/5 inhibitors JPX-0700/JPX-0750 on cell viability alone, or in combination with approved antineoplastic agents, in NKCL or AML cancer cell lines and primary AML patient samples. To identify genetic abnormalities of cell lines, we utilized array comparative genome hybridization. Western blotting and flow cytometry were employed to elucidate the mechanisms of the inhibitors on cell viability, cell cycle and STAT3/5 downstream signaling. In order to evaluate the effectiveness and safety of these compounds in vivo, we established AML and NKCL mouse xenografts and administered daily intraperitoneal injections of the inhibitors. Results: Our STAT3/5 degraders selectively reduced STAT3/5 activation and total protein levels, as well as downstream target oncogene expression, exhibiting nanomolar to low micromolar efficacy in inducing cell death in AML/NKCL cell lines and AML patient samples. We found that both AML/NKCL cells hijack STAT3/5 signaling through either upstream activating mutations in tyrosine kinases, activating gain-of-function mutations in STAT3, mutational loss of negative STAT regulators, or genetic gains in anti-apoptotic, pro-proliferative or epigenetic-modifying STAT3/5 targets, emphasizing STAT3/5 as valid targets in these diseases. JPX-0700/-0750 treatment reduced leukemic cell growth in human AML or NKCL xenograft mouse models, without adverse side effects. Additionally, we observed synergistic cell death induced by JPX-0700/-0750 upon combinatorial use with approved chemotherapeutics in AML/NKCL cell lines and AML patient blasts. Conclusion: We demonstrate the effectiveness of dual pharmacologic inhibition of phospho- and total STAT3/5 by JPX inhibitors in AML and NKCL, emphasizing their essential roles in initiating and driving these cancers. These potent small molecule degraders of STAT3/5 could propel further clinical development and may emerge as highly effective combinatorial partners for the treatment of AML and NKCL patients.

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 score0.004
Threshold uncertainty score0.012

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)0.0040.001

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 head0.051
GPT teacher head0.343
Teacher spread0.292 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueResearch SquareSame topicMyeloproliferative Neoplasms: Diagnosis and TreatmentFrench-language works237,207