Low BRCA1 and ERCC1 mRNA expression correlates with improved survival in ovarian cancer patients
Bibliographic record
Abstract
A199 The poor prognosis of advanced-stage ovarian cancer is marked by early recurrences and resistance to platinum-based chemotherapy. Elevated levels of the DNA repair proteins, Breast Cancer 1 (BRCA1) and excision repair cross complementation group 1 (ERCC1) have been associated with increased resistance to cisplatinum in various malignancies including ovarian cancer. Purpose: The aim of this study was to analyze BRCA1 and ERCC1 mRNA expression as markers of recurrence and prognosis in ovarian cancer. Experimental procedures: Clinicopathologic data was collected on 22 patients who underwent surgical staging and adjuvant chemotherapy at The Ottawa Hospital between 2000 and 2005. RNA was extracted from frozen tissue in the Ottawa Ovarian Tissue Bank and mRNA expression was determined by quantitative, real-time, reverse-transcriptase PCR (Q-PCR). Kaplan-Meier survival curves and regression analyses were determined using Prism software. The A2780s ovarian cell line, which has high expression of both BRCA1 and ERCC1, was exposed to a number of drugs including chemotherapy and molecular inhibitors and analyzed by the MTT cell viability assay. Results: Linear regression analysis demonstrated that both low BRCA1 and ERCC1 expression were associated with improved survival ( P=0.048 and P=0.033) but only low BRCA1 correlated with a longer TTP (P=0.047 and P=0.122, respectively). Patients were classified into relative high and low mRNA expression levels for BRCA1. There was no significant difference between the two groups with respect to the distribution of independent variables, age, stage, residual disease status, grade and p53 IHC score. The median OS by Kaplan-Meier estimates for BRCA1-low was 51 months, and for BRCA1-high was 37 months, illustrating a trend that patients with decreased BRCA1 expression have a more favorable survival (P=0.079). The median TTP was 20.5 months in BRCA1-low and 12.5 months in BRCA1-high, but the distribution between groups was not significantly different in this patient cohort (P=0.384). Exposure of the A2780s cell line to a number of therapeutic agents either alone or in combination, resulted in differential drug sensitivity. Conclusions: Low BRCA1 and ERCC1 expression correlates with improved survival and may be useful to tailor chemotherapeutic approaches in the treatment of ovarian cancer.
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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 | 0.000 |
| 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) | 0.001 | 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".