TGFβ-Induced Smad Signaling Remains Intact in Primary Human Ovarian Cancer Cells
Bibliographic record
Abstract
Disruptions in TGF beta signaling have been implicated in various human cancers, including ovarian cancer. Our goal was to determine whether ovarian cancer cells isolated from patient ascites fluid were growth inhibited by TGF beta 1 treatment and further characterize the expression and activity profile of TGF beta/Smad signaling components in human ovarian cancer cells. We found that 9 of 10 primary cultures of ovarian cancer cells (OC2-10) were growth inhibited by 16 pM TGF beta 1. One primary ovarian cancer sample (OC1) and the established ovarian cancer cell lines CaOV3 and SkOV3 continued to grow in the presence of TGF beta 1. All cells expressed components of the TGF beta/Smad signaling pathway including TGF beta 1, T beta RI, T beta RII, Smad2, -3, -4, and Smad anchor for receptor activation. Although OC1, CaOV3, and SkOV3 are not growth inhibited by TGF beta 1, they can transmit the TGF beta 1 signal to turn on a transfected TGF beta/Smad reporter gene, p3TP.lux. In addition, all cells up-regulate the endogenous TGF beta target genes Smad7 and PAI-1. p15(Ink4B) mRNA is also up-regulated with TGF beta 1 treatment in OC2-9, whereas the p15(Ink4B) gene has been deleted in OC1, CaOV3, and SkOV3 cells. Homozygous deletion of p15(Ink4B) may account for TGF beta resistance in some populations of ovarian cancer cells. Our data demonstrate that the TGF beta/Smad signaling pathway remains functional in human ovarian cancer cells and suggest that if abnormalities exist in the cellular response of TGF beta signals, they must lie downstream of the Smad proteins.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".