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Modulating Androgen Receptor-Driven Transcription in Prostate Cancer with Selective CDK9 Inhibitors

2020· article· en· W3093612331 on OpenAlex
André Richters, Shelby K. Doyle, David B. Freeman, Christina Lee, Becky Leifer, Sajjeev Jagannathan, Florian Kabinger, Jošt Vrabič Koren, Nicholas B. Struntz, Julie Urgiles, Ryan A. Stagg, Brice H. Curtin, Deep Chatterjee, Sebastian Mathea, Peter Mikochik, Tamara D. Hopkins, Hua Gao, Jonathan R. Branch, Hong Xin, Lori Westover, Gilles Bignan, Brent Rupnow, Kristen L. Karlin, Thomas F. Westbrook, Joseph P. Vacca, Chris M. Wilfong, B. Wesley Trotter, Douglas C. Saffran, Norbert Bischofberger, Stefan Knapp, Joshua W. Russo, Ian Hickson, James R. Bischoff, Marco M. Gottardis, Steven P. Balk, Charles Y. Lin, Marius S. Pop, Angela N. Koehler

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCell chemical biology · 2020
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
FundersCongressionally Directed Medical Research ProgramsNational Cancer InstituteNational Institutes of HealthLudwig Center at HarvardDeutsche ForschungsgemeinschaftNovartis PharmaDeutschen Konsortium für Translationale KrebsforschungOno Pharma FoundationCanada Foundation for InnovationOntario Ministry of Economic Development and InnovationEshelman Institute for Innovation, University of North Carolina at Chapel HillBroad InstituteKoch Institute for Integrative Cancer Research, Massachusetts Institute of TechnologyShenzhen Gas CorporationWellcome TrustU.S. Department of DefenseGenome CanadaMerck KGaAMeso Scale DiagnosticsCancer Prevention and Research Institute of TexasTakeda Pharmaceuticals U.S.A.PfizerAlexander and Margaret Stewart TrustBoehringer IngelheimJanssen PharmaceuticalsProstate Cancer FoundationNational Science Foundation
KeywordsAndrogen receptorProstate cancerCancer researchTranscription (linguistics)Transcription factorIn vivoAndrogenBiologyChemistryCancerEndocrinologyGeneHormoneBiochemistryGenetics

Abstract

fetched live from OpenAlex

Castration-resistant prostate cancers (CRPCs) lose sensitivity to androgen-deprivation therapies but frequently remain dependent on oncogenic transcription driven by the androgen receptor (AR) and its splice variants. To discover modulators of AR-variant activity, we used a lysate-based small-molecule microarray assay and identified KI-ARv-03 as an AR-variant complex binder that reduces AR-driven transcription and proliferation in prostate cancer cells. We deduced KI-ARv-03 to be a potent, selective inhibitor of CDK9, an important cofactor for AR, MYC, and other oncogenic transcription factors. Further optimization resulted in KB-0742, an orally bioavailable, selective CDK9 inhibitor with potent anti-tumor activity in CRPC models. In 22Rv1 cells, KB-0742 rapidly downregulates nascent transcription, preferentially depleting short half-life transcripts and AR-driven oncogenic programs. In vivo, oral administration of KB-0742 significantly reduced tumor growth in CRPC, supporting CDK9 inhibition as a promising therapeutic strategy to target AR dependence in CRPC.

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.

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)0.000
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 score0.119
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.022
GPT teacher head0.283
Teacher spread0.261 · 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