The DNA repair proteins BRCA1 and ERCC1 as predictive markers in sporadic ovarian cancer
Bibliographic record
Abstract
This study compares Breast Cancer 1 (BRCA1) and excision repair cross complementation group 1 (ERCC1) expression as predictive markers and evaluates the in vitro enhancement of platinum sensitivity using targeted agents in sporadic ovarian cancer (OC). A retrospective study was performed of advanced stage OC patients receiving platinum-based chemotherapy. BRCA1 and ERCC1 mRNA expression was determined from frozen tissue of 51 patients. Median overall survival (OS) was longer for patients with lower BRCA1 vs. higher BRCA1 (46 vs.33 months, p = 0.03). High BRCA1 was predictive of poorer OS specifically in patients with residual disease (RD) <2 cm (p = 0.03). There was a non-significant association for patients with lower ERCC1 and RD <2 cm in favor of improved OS and time to progression. Patients who expressed higher levels of both BRCA1 and ERCC1 mRNA had a shorter OS compared to patients with lower levels of either or both transcript (33 vs.46 months, p = 0.04). When Cox proportional modeling was used by representing BRCA1 and ERCC1 mRNA expression as a continuous variable, both emerge as potential predictors of survival. OC cell lines were exposed to chemotherapy in combination with DNA repair pathway inhibitors and cell viability was assessed. In vitro histone deacetylase (HDAC) inhibition increased the sensitivity of A2780s/cp cells to cisplatin and carboplatin but not to taxol, coincident with a significant decrease in BRCA1 and ERCC1 expression, suggesting that this compound directly targets DNA repair. In summary, this study shows that low BRCA1 and ERCC1 expression correlate with improved survival in advanced OC and HDAC inhibition induces synergistic cytotoxicity with platinum in vitro.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".