Exome profiling of primary, metastatic and recurrent ovarian carcinomas in a BRCA1-positive patient
Bibliographic record
Abstract
BACKGROUND: Ovarian carcinoma is a common, and often deadly, gynecological cancer. Mutations in BRCA1 and BRCA2 genes are present in at least a fifth of patients. Uncovering other genes that become mutated subsequent to BRCA1/BRCA2 inactivation during cancer development will be helpful for more effective treatments. METHODS: We performed exome sequencing on the blood, primary tumor, omental metastasis and recurrence following therapy with carboplatin and paclitaxel, from a patient carrying a BRCA1 S1841R mutation. RESULTS: We observed loss of heterozygosity in the BRCA1 mutation in the primary and subsequent tumors, and somatic mutations in the TP53 and NF1 genes were identified, suggesting their role along with BRCA1 driving the tumor development. Notably, we show that exome sequencing is effective in detecting large chromosomal rearrangements such as deletions and amplifications in cancer. We found that a large deletion was present in the three tumors in the regions containing BRCA1, TP53, and NF1 mutations, and an amplification in the regions containing MYC. We did not observe the emergence of any new mutations among tumors from diagnosis to relapse after chemotherapy, suggesting that mutations already present in the primary tumor contributed to metastases and chemotherapy resistance. CONCLUSIONS: Our findings suggest that exome sequencing of matched samples from one patient is a powerful method of detecting somatic mutations and prioritizing their potential role in the development of the disease.
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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".