Genome-Wide Loss of Heterozygosity and Uniparental Disomy in BRCA1/2-Associated Ovarian Carcinomas
Bibliographic record
Abstract
PURPOSE: The importance of the BRCA gene products in maintaining genomic stability led us to hypothesize that BRCA-associated and sporadic ovarian cancers would have distinctive genetic profiles despite similarities in histologic appearance. EXPERIMENTAL DESIGN: A whole-genome copy number analysis of fresh, frozen, papillary serous ovarian cancer DNA was done using the Affymetrix 50K Xba Mapping Array using each patient's normal genomic DNA as the matched control. Loss of heterozygosity and copy number abnormalities were summarized to define regions of amplification, deletion, or uniparental disomy (UPD), defined as loss of one allele and duplication of the remaining allele. Genomic abnormalities were compared between BRCA-associated and sporadic tumors. RESULTS: We compared 6 BRCA-associated with 14 sporadic papillary serous ovarian carcinomas. Genetic instability, measured by percentage of genome altered, was more pronounced in BRCA-associated tumors (median, 86.6%; range, 54-100%) than sporadic tumors (median, 43.6%; range, 2-83%; P = 0.009). We used frequency plots to show the proportion of cases affected by each type abnormality at each genomic region. BRCA-associated tumors showed genome-wide loss of heterozygosity primarily due to the occurrence of UPD rather than deletion. UPD was found in 100% of the BRCA-associated and 50% of the sporadic tumors profiled. CONCLUSIONS: This study reports on a previously underappreciated genetic phenomenon of UPD, which occurs frequently in ovarian cancer DNA. We observed distinct genetic patterns between BRCA-associated and sporadic ovarian cancers, suggesting that these papillary serous tumors arise from different molecular pathways.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".