RETRACTED: Identification of novel candidate targets for suppressing ovarian cancer progression through IL-33/ST2 axis components using the system biology approach
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
Background: Cancer-associated fibroblasts (CAFs) of ovarian cancer (OvC) are the most prevalent element of the tumor microenvironment (TM). By promoting angiogenesis, immunological suppression, and invasion, CAFs speed up the growth of tumors by changing the extracellular matrix’s structure and composition and/or initiating the epithelial cells (EPT). IL-33/ST2 signaling has drawn a lot of attention since it acts as a pro-tumor alarmin and encourages spread by altering TM. Methods: Differentially expressed genes (DEGs) of the OvC tumor microenvironment were found in the GEO database, qRT-PCR, western blotting, and immunohistochemistry, and their presence and changes in healthy and tumor tissue content were examined. Primary cultures of healthy fibroblasts and CAFs obtained from healthy and tumor tissues retrieved from OvC samples were used for in vitro and in vivo investigations. Cultured primary human CAFs were utilized to investigate the regulation and the IL-33/ST2 axis role in the inflammation reactions. Results: Although ST2 and IL-33 expression was detected in both epithelial (EPT) and fibroblast cells of ovarian cancer, they are more abundant in CAFs. Lipopolysaccharides, serum amyloid A1, and IL-1β, the inflammatory mediators, could all induce IL-33 expression through NF-κB activation in human CAFs. In turn, via the ST2 receptor, IL-33 affected the production of IL-6, IL-1β, and PTGS2 in human CAFs via the MAPKs-NF-κB pathway. Conclusion: Our findings suggest that IL-33/ST2 is affected by the interaction of CAFs and epithelial cells inside the tumor microenvironment. Activation of this axis leads to increased expression of inflammatory factors in tumor CAFs and EPT cells. Therefore, targeting the IL-33/ST2 axis could have potential value in the prevention of OvC progression.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".