P1-14-1 腹膜中皮腫と卵巣癌の鑑別診断におけるp16/CDKN2A FISHの有用性の検討(Group 14 卵巣腫瘍・基礎1,一般演題,公益社団法人日本産科婦人科学会第66回学術講演会)
Bibliographic record
Abstract
Primary resistance to androgen receptor (AR)-directed therapies in metastatic castration-resistant prostate cancer (mCRPC) is poorly understood. We randomized 202 patients with treatment-naïve mCRPC to abiraterone or enzalutamide and performed whole-exome and deep targeted 72-gene sequencing of plasma cell-free DNA prior to therapy. For these agents, which have never been directly compared, time to progression was similar. Defects in <i>BRCA2</i> and <i>ATM</i> were strongly associated with poor clinical outcomes independently of clinical prognostic factors and circulating tumor DNA abundance. Somatic alterations in <i>TP53</i>, previously linked to reduced tumor dependency on AR signaling, were also independently associated with rapid resistance. Although detection of <i>AR</i> amplifications did not outperform standard prognostic biomarkers, <i>AR</i> gene structural rearrangements truncating the ligand binding domain were identified in several patients with primary resistance. These findings establish genomic drivers of resistance to first-line AR-directed therapy in mCRPC and identify potential minimally invasive biomarkers.<b>Significance:</b> Leveraging plasma specimens collected in a large randomized phase II trial, we report the relative impact of common circulating tumor DNA alterations on patient response to the most widely used therapies for advanced prostate cancer. Our findings suggest that liquid biopsy analysis can guide the use of AR-targeted therapy in general practice. <i>Cancer Discov; 8(4); 444-57. ©2018 AACR.</i><i>See related commentary by Jayaram et al., p. 392</i><i>This article is highlighted in the In This Issue feature, p. 371</i>.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".