Distinct Patterns of Structural and Numerical Chromosomal Instability Characterize Sporadic Ovarian Cancer
Bibliographic record
Abstract
Sporadic ovarian cancer is a particularly aggressive tumor characterized by highly abnormal karyotypes exhibiting many features of genomic instability. More complex genomic changes in tumors arise as a consequence of chromosomal instability (CIN), which can generate both numerical [(N)-CIN] and structural chromosomal instability [(S)-CIN]. In this study, molecular cytogenetic analysis was used to evaluate the relative levels of both (N)-CIN and (S)-CIN. Six tumors had a near-diploid chromosome number, two were near-tetraploid, and two were near-triploid. (N)-CIN levels increased as a function of overall tumor genomic content, with near-diploid tumors exhibiting numerical instability indices ranging from 7.0 to 21.0 and near-tetraploid and triploid tumors exhibiting instability indices ranging from 24.9 to 54.9. In contrast, the extent of (S)-CIN was generally more evident in the diploid tumors compared with the near-tetraploid tumors. To determine whether the associated chromosomal constitution and/or ploidy changes were influenced by mitotic segregation errors, centrosome analyses were performed on all 10 tumors. The near-diploid tumors, with the lowest numerical change, were observed to possess fewer cells with centrosome abnormalities (5.5% to 14.0%), whereas the near-tetraploid tumors possessed much higher levels of (N)-CIN and were characterized by a trend of elevating percentages of cells with abnormal centrosomes (16.0% to 20.5%). These observations suggest that two distinct processes governing genome stability may be disrupted in ovarian cancer: those that impact on numerical segregation and ploidy of chromosomes and those that affect the fidelity of DNA repair and lead to structural aberrations.
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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".