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Record W2905558559 · doi:10.1182/blood-2018-07-862953

Bruton tyrosine kinase degradation as a therapeutic strategy for cancer

2018· article· en· W2905558559 on OpenAlexfundno aff
Dennis Dobrovolsky, Eric S. Wang, Sara Morrow, Catharine Leahy, T.B. Faust, Radosław P. Nowak, Katherine A. Donovan, Guang Yang, Zhengnian Li, Eric S. Fischer, Steven P. Treon, David M. Weinstock, Nathanael S. Gray

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthHarvard UniversityNational Cancer InstituteDamon Runyon Cancer Research Foundation
KeywordsBruton's tyrosine kinaseIbrutinibMantle cell lymphomaCancer researchTyrosine kinaseB cellLymphomaMedicineBiologyImmunologyChronic lymphocytic leukemiaSignal transductionLeukemiaCell biologyAntibody

Abstract

fetched live from OpenAlex

The covalent Bruton tyrosine kinase (BTK) inhibitor ibrutinib is highly efficacious against multiple B-cell malignancies. However, it is not selective for BTK, and multiple mechanisms of resistance, including the C481S-BTK mutation, can compromise its efficacy. We hypothesized that small-molecule-induced BTK degradation may overcome some of the limitations of traditional enzymatic inhibitors. Here, we demonstrate that BTK degradation results in potent suppression of signaling and proliferation in cancer cells and that BTK degraders efficiently degrade C481S-BTK. Moreover, we discovered DD-03-171, an optimized lead compound that exhibits enhanced antiproliferative effects on mantle cell lymphoma (MCL) cells in vitro by degrading BTK, IKFZ1, and IKFZ3 as well as efficacy against patient-derived xenografts in vivo. Thus, "triple degradation" may be an effective therapeutic approach for treating MCL and overcoming ibrutinib resistance, thereby addressing a major unmet need in the treatment of MCL and other B-cell lymphomas.

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 score0.001
Threshold uncertainty score0.003

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.369
Teacher spread0.315 · 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

Citations169
Published2018
Admission routes1
Has abstractyes

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