Copy Number and Expression Alterations of miRNAs in the Ovarian Cancer Cell Line OVCAR-3: Impact on Kallikrein 6 Protein Expression
Bibliographic record
Abstract
BACKGROUND: Kallikrein-related peptidase 6 (KLK6), a member of the serine protease family of kallikrein (KLK) genes, is dysregulated in ovarian carcinomas (OCa) and its overexpression is associated with poor prognosis. Regulation of its expression is poorly understood and is likely to be influenced by multiple mechanisms. The KLK locus is subject to copy number changes and heterogeneity in serous OCas. These copy number imbalances generally correlate with KLK6 protein expression; however, this is not always the case. In this study we explored the role of miRNAs in the posttranscriptional control of KLK6 expression and the contributions of copy numbers, not only of the KLK locus, but also of the miRNAs predicted to regulate it. METHODS AND RESULTS: By miRNA profiling of the KLK6-overexpressing OCa cell line, OVCAR-3, we identified overexpressed and underexpressed miRNAs. Publically available miRNA databases identified the human miRNA lethal 7 (hsa-let-7) family members as putative regulating miRNAs, from which hsa-let-7a was chosen for functional analysis. The transient transfection of hsa-let-7a to OVCAR-3 resulted in a decrease of KLK6 secreted protein. Moreover, such transfection was also able to weakly affect the expression of another member of the KLK gene family, KLK10 (kallikrein-related peptidase 10). Cytogenomic analysis, including array comparative genomic hybridization, fluorescence in situ hybridization, and spectral karyotyping revealed the overall net copy number losses of hsa-let-7a and other miRNAs predicted to target KLK6. CONCLUSIONS: The hsa-let-7 family member hsa-let-7a is a modulator of KLK6 protein expression that is independent of the KLK6 copy number status.
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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) | 0.001 | 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 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".