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Record W4280492129 · doi:10.1073/pnas.2114324119

H3K9 methylation drives resistance to androgen receptor–antagonist therapy in prostate cancer

2022· article· en· W4280492129 on OpenAlexaff
Mehdi Baratchian, Ritika Tiwari, Sirvan Khalighi, Ankur Chakravarthy, Wei Yuan, Michael Berk, Jianneng Li, Amy Guerinot, Johann S. de Bono, Vladimir Makarov, Timothy A. Chan, Robert H. Silverman, George R. Stark, Vinay Varadan, Daniel D. De Carvalho, Abhishek A. Chakraborty, Nima Sharifi

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthNational Cancer InstituteMedical Research CouncilNational Institute for Health and Care ResearchU.S. Department of Defense
KeywordsProstate cancerAntiandrogensCancer researchAntiandrogenVorinostatGene silencingAndrogen receptorEpigeneticsFlutamideEpigenetic therapyBiologyCancerMedicineInternal medicineHistoneDNA methylationGene expressionGeneticsHistone deacetylase

Abstract

fetched live from OpenAlex

Antiandrogen strategies remain the prostate cancer treatment backbone, but drug resistance develops. We show that androgen blockade in prostate cancer leads to derepression of retroelements (REs) followed by a double-stranded RNA (dsRNA)-stimulated interferon response that blocks tumor growth. A forward genetic approach identified H3K9 trimethylation (H3K9me3) as an essential epigenetic adaptation to antiandrogens, which enabled transcriptional silencing of REs that otherwise stimulate interferon signaling and glucocorticoid receptor expression. Elevated expression of terminal H3K9me3 writers was associated with poor patient hormonal therapy outcomes. Forced expression of H3K9me3 writers conferred resistance, whereas inhibiting H3K9-trimethylation writers and readers restored RE expression, blocking antiandrogen resistance. Our work reveals a drug resistance axis that integrates multiple cellular signaling elements and identifies potential pharmacologic vulnerabilities.

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 score0.012
Threshold uncertainty score0.244

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 science0.0010.000
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 head0.026
GPT teacher head0.330
Teacher spread0.304 · 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

Citations50
Published2022
Admission routes1
Has abstractyes

Explore more

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