The RUNX1 transcription factor is expressed in serous epithelial ovarian carcinoma and contributes to cell proliferation, migration and invasion
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Bibliographic record
Abstract
Previously, we have identified the RUNX1 gene as hypomethylated and overexpressed in post-chemotherapy (CT) primary cultures derived from epithelial ovarian cancer (EOC) patients, when compared with primary cultures derived from matched primary (prior to CT) tumors. Here we show that RUNX1 displays a trend of hypomethylation, although not significant, in omental metastases compared with primary EOC tumors. Surprisingly, RUNX1 displayed significantly higher expression not only in metastatic tissue, but also in high-grade primary tumors and even in low malignant potential tumors. The RUNX1 expression levels were almost identical in primary tumors and omental metastases, suggesting that RUNX1 hypomethylation might have a limited impact on its overexpression in advanced (metastatic) stage of the disease. Knockdown of the RUNX1 expression in EOC cells led to sharp decrease of cell proliferation and induced G 1 cell cycle arrest. Moreover, RUNX1 suppression significantly inhibited EOC cell migration and invasion. Gene expression profiling and consecutive network and pathway analyses confirmed these findings, as numerous genes and pathways known previously to be implicated in ovarian tumorigenesis, including EOC tumor invasion and metastasis, were found to be downregulated upon RUNX1 suppression, while a number of pro-apoptotic genes and some EOC tumor suppressor genes were induced. Taken together, our data are indicative for a strong oncogenic potential of the RUNX1 gene in EOC progression and suggest that RUNX1 might be a novel EOC therapeutic target. Further studies are needed to more completely elucidate the functional implications of RUNX1 and other members of the RUNX gene family in ovarian tumorigenesis.
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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 it