Expression of interleukin-1 (IL-1) ligands system in the most common endometriosis-associated ovarian cancer subtypes
Bibliographic record
Abstract
OBJECTIVES: Endometrioid carcinoma of the ovary is one of the most types of epithelial ovarian cancer associated to endometrioisis. Endometrioid tumors as well as endometriotic implants are characterized by the presence of epithelial cells, stromal cells, or a combination of booth, that resemble the endometrial cells, suggesting a possible endometrial origin of these tumors. Pro-inflammatory cytokines, including interleukin-1 (IL-1) have been reported to be involved in both endometriosis and ovarian carcinogenesis. The major objective of this study was to determine the level expression of IL-1 ligands system (IL-1alpha, IL-1beta and IL-1RA) in the most common subtypes of ovarian cancer cells compared to endometrial cells. METHODS: We used primary endometrial cells, endometrial cell line RL-952 and different subtypes of epithelial ovarian cancer cell lines including TOV-112D (endometrioid), TOV-21G (clear cell) and OV-90 (serous). Immunofluorescence and real-time PCR analysis were used respectively for detecting IL-1 ligands at the levels of cell-associated protein and mRNA. Soluble IL-1 ligands were analyzed by ELISA. RESULTS: We demonstrated that IL-1 ligands were expressed by all endometriosis-associated ovarian cancer subtypes and endometrial cells. In contrast to other cancer ovarian cells, endometrioid cells exhibit a specific decrease of cell-associated IL-1RA expression and its soluble secretion. CONCLUSION: Endometrioid ovarian cancer exhibits an alteration in the expression of IL-1RA, a key protector against tumorogenic effects of IL-1. This alteration evokes the same alteration observed in endometriotic cells in previous studies. This suggests a possible link between the endometrium, the tissue ectopic endometriosis and endometrioid 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) | 0.001 | 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".