Cell-Free DNA Modification Dynamics in Abiraterone Acetate-Treated Prostate Cancer Patients
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".