TGF -Induced Smad Signaling Remains Intact in Primary Human Ovarian Cancer Cells
Bibliographic record
Abstract
Disruptions in TGFβ 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 TGFβ1 treatment and further characterize the expression and activity profile of TGFβ/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 TGFβ1. One primary ovarian cancer sample (OC1) and the established ovarian cancer cell lines CaOV3 and SkOV3 continued to grow in the presence of TGFβ1. All cells expressed components of the TGFβ/Smad signaling pathway including TGFβ1, TβRI, TβRII, Smad2, -3, -4, and Smad anchor for receptor activation. Although OC1, CaOV3, and SkOV3 are not growth inhibited by TGFβ1, they can transmit the TGFβ1 signal to turn on a transfected TGFβ/Smad reporter gene, p3TP.lux. In addition, all cells up-regulate the endogenous TGFβ target genes Smad7 and PAI-1. p15Ink4B mRNA is also up-regulated with TGFβ1 treatment in OC2–9, whereas the p15Ink4B gene has been deleted in OC1, CaOV3, and SkOV3 cells. Homozygous deletion of p15Ink4B may account for TGFβ resistance in some populations of ovarian cancer cells. Our data demonstrate that the TGFβ/Smad signaling pathway remains functional in human ovarian cancer cells and suggest that if abnormalities exist in the cellular response of TGFβ 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".