Early transformative changes in normal ovarian surface epithelium induced by oxidative stress require Akt upregulation, DNA damage and epithelial–stromal interaction
Bibliographic record
Abstract
Ovarian cancer is the deadliest gynecological malignancy due to detection of cancer at a late stage when the disease has metastasized. One likely progenitor cell type of ovarian cancer is the ovarian surface epithelium (OSE), which proliferates rapidly in the presence of inflammatory cytokines and oxidative stress following ovulation. To determine whether oxidative stress induces DNA damage leading to spontaneous transformative changes in normal OSE, an immortalized mouse OSE cell line (MOSE cells) or normal mouse ovarian organoids were treated with hydrogen peroxide (H2O2) and loss of contact inhibition was assessed by soft agar assay. In response to H2O2, OSE cells grown in 3D exhibited growth in soft agar but MOSE cells grown on 2D plastic did not, indicating a critical role for epithelial-stromal interactions in neoplastic initiation. Loss of contact inhibition in response to H2O2 correlated with an increase in proliferation, DNA damage and upregulation of the oncogene Akt1. Use of a reactive oxygen species scavenger or Akt inhibitor blocked H2O2-induced proliferation and growth in soft agar. Although parental MOSE cells did not undergo transformation by H2O2, MOSE cells stably overexpressing constitutively active myristoylated Akt or knockdown of phosphatase and tensin homolog (PTEN) exhibited loss of contact inhibition and increased proliferation. This study indicates that normal OSE undergo transformative changes induced by oxidative stress and that this process requires Akt upregulation and activation. A 3D model that retains tissue architecture is critical for studying this process and may lead to development of new intervention strategies directed at early stages of ovarian cancer.
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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) | 0.002 | 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".