Genomic instability and copy‐number heterogeneity of chromosome 19q, including the kallikrein locus, in ovarian carcinomas
Bibliographic record
Abstract
Many tissue kallikrein (KLK) genes and proteins are candidate diagnostic, prognostic and predictive biomarkers for ovarian cancer (OCa). We previously demonstrated that the KLK locus (19q13.3/4) is subject to copy-number gains and structural rearrangements in a pilot study of cell lines and ovarian cancer primary tissues, shown to overexpress KLK gene family members. To determine the overall frequency of genomic instability and copy-number changes, a retrospective study was conducted using formalin-fixed paraffin embedded (FFPE) tissues. Eighty-one chemotherapy naïve serous OCas were examined using 3-colour fluorescence in situ hybridization (FISH) to identify structural and numerical changes on 19q, including the KLK locus; in addition to immunohistochemistry (IHC) for KLK6, which has been shown to be overexpressed in OCa. The KLK locus was subject to copy-number changes in ∼83% of cases: net gain in 51%, net loss in 30% and amplified in 2%; and found to be chromosomally unstable (p < 0.001). All cases showed a wide range of immuoreactivity for KLK6 by IHC. Although no strong correlation could be found with copy-number, the latter was contributing factor to the observed KLK6 protein overexpression. Moreover, univariate and multivariate analyses showed an association between the net loss of the KLK locus and longer disease-free survival. Interestingly, FISH analyses indicated that chromosome 19q was subjected to structural rearrangement in 62% of cases and was significantly correlated to tumor grade (p < 0.001). We conclude that numerical and structural aberrations of chromosome 19q, affect genes including the KLK gene members, may contribute to ovarian carcinoma progression and aggressiveness.
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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 | 0.001 | 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".