14-3-3 σ Expression Effects G2/M Response to Oxygen and Correlates with Ovarian Cancer Metastasis
Bibliographic record
Abstract
BACKGROUND: In vitro cell culture experiments with primary cells have reported that cell proliferation is retarded in the presence of ambient compared to physiological O₂ levels. Cancer is primarily a disease of aberrant cell proliferation, therefore, studying cancer cells grown under ambient O₂ may be undesirable. To understand better the impact of O₂ on the propagation of cancer cells in vitro, we compared the growth potential of a panel of ovarian cancer cell lines under ambient (21%) or physiological (3%) O₂. PRINCIPAL FINDINGS: Our observations demonstrate that similar to primary cells, many cancer cells maintain an inherent sensitivity to O₂, but some display insensitivity to changes in O₂ concentration. Further analysis revealed an association between defective G2/M cell cycle transition regulation and O₂ insensitivity resultant from overexpression of 14-3-3 σ. Targeting 14-3-3 σ overexpression with RNAi restored O₂ sensitivity in these cell lines. Additionally, we found that metastatic ovarian tumors frequently overexpress 14-3-3 σ, which in conjunction with phosphorylated RB, results in poor prognosis. CONCLUSIONS: Cancer cells show differential proliferative sensitivity to changes in O₂ concentration. Although a direct link between O₂ insensitivity and metastasis was not determined, this investigation showed that an O₂ insensitive phenotype in cancer cells to correlate with metastatic tumor progression.
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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 | 0.000 | 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) | 0.001 | 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".