TGF-Beta Induces Serous Borderline Ovarian Tumor Cell Invasion by Activating EMT but Triggers Apoptosis in Low-Grade Serous Ovarian Carcinoma Cells
Bibliographic record
Abstract
Apoptosis in ovarian surface epithelial (OSE) cells is induced by transforming growth factor-beta (TGF-β). However, high-grade serous ovarian carcinomas (HGC) are refractory to the inhibitory functions of TGF-β; their invasiveness is up-regulated by TGF-β through epithelial-mesenchymal transition (EMT) activation. Serous borderline ovarian tumors (SBOT) have been recognized as distinct entities that give rise to invasive low-grade serous carcinomas (LGC), which have a relatively poor prognosis and are unrelated to HGC. While it is not fully understood how TGF-β plays disparate roles in OSE cells and its malignant derivative HGC, its role in SBOT and LGC remains unknown. Here we demonstrate the effects of TGF-β on cultured SBOT3.1 and LGC-derived MPSC1 cells, which express TGF-β type I and type II receptors. TGF-β treatment induced the invasiveness of SBOT3.1 cells but reduced the invasiveness of MPSC1 cells. The analysis of apoptosis, which was assessed by cleaved caspase-3 and trypan blue exclusion assay, revealed TGF-β-induced apoptosis in MPSC1, but not SBOT3.1 cells. The pro-apoptotic effect of TGF-β on LGC cells was confirmed in another immortalized LGC cell line ILGC. TGF-β treatment led to the activation of Smad3 but not Smad2. The specific TβRI inhibitor SB431542 and TβRI siRNA abolished the SBOT3.1 invasion induced by TGF-β, and it prevented TGF-β-induced apoptosis in MPSC1 cells. In SBOT3.1 cells, TGF-β down-regulated E-cadherin and concurrently up-regulated N-cadherin. TGF-β up-regulated the expression of the transcriptional repressors of E-cadherin, Snail, Slug, Twist and ZEB1. In contrast, co-treatment with SB431542 and TβRI depletion by siRNA abolished the effects of TGF-β on the relative cadherin expression levels and that of Snail, Slug, Twist and ZEB1 as well. This study demonstrates dual TGF-β functions: the induction of SBOT cell invasion by EMT activation and apoptosis promotion in LGC cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".