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Record W2795460644 · doi:10.1158/1078-0432.ccr-18-0101

Cell-Free DNA Modification Dynamics in Abiraterone Acetate-Treated Prostate Cancer Patients

2018· article· en· W2795460644 on OpenAlexaff
Juozas Gordevičius, Algimantas Kriščiūnas, Daniel E. Groot, Steven Yip, Miki Susic, Andrew Kwan, Rafal Kustra, Anthony M. Joshua, Kim N., Artūras Petronis, Gabriel Oh

Bibliographic record

VenueClinical Cancer Research · 2018
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British ColumbiaPrincess Margaret Cancer CentrePublic Health OntarioBC Cancer AgencyCentre for Addiction and Mental Health
FundersLietuvos Mokslo Taryba
KeywordsProstate cancerAbiraterone acetateInternal medicineOncologyMedicineCancerDNA methylationAbirateroneCancer researchBiologyGeneticsGeneAndrogen deprivation therapyAndrogen receptorGene expression

Abstract

fetched live from OpenAlex

Abstract Purpose: Primary resistance to abiraterone acetate (AA), a key medication for the treatment of metastatic castration-resistant prostate cancer, occurs in 20% to 40% of patients. We aim to identify predictive biomarkers for AA-treatment response and understand the mechanisms related to treatment resistance. Experimental Design: We used the Infinium Human Methylation 450K BeadChip to monitor modification profiles of cell-free circulating DNA (cfDNA) in 108 plasma samples collected from 33 AA-treated patients. Results: Thirty cytosines showed significant modification differences (FDR Q < 0.05) between AA-sensitive and AA-resistant patients during the treatment, of which 21 cytosines were differentially modified prior to treatment. In addition, AA-sensitive patients, but not AA-resistant patients, lost interindividual variation of cfDNA modification shortly after starting AA treatment, but such variation returned to initial levels in the later phases of treatment. Conclusions: Our findings provide a list of potential biomarkers for predicting AA-treatment response, highlight the prognostic value of using cytosine modification variance as biomarkers, and shed new insights into the mechanisms of prostate cancer relapse in AA-sensitive patients. Clin Cancer Res; 24(14); 3317–24. ©2018 AACR.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.172
GPT teacher head0.507
Teacher spread0.336 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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