[Retracted] Analysis and Validation of Differentially Expressed Ferroptosis‐Related Genes in Regorafenib‐Induced Cardiotoxicity
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: Although tyrosine kinase inhibitors (TKIs) constitute a type of anticancer drugs, the underlying mechanisms of TKI-associated cardiotoxicity remain largely unknown. Ferroptosis is a regulated cell death form that implicated in several tumors' biological processes. Our objective was to probe into the differential expression of ferroptosis-related genes in regorafenib-induced cardiotoxicity through multiple bioinformatics analysis and validation. Methods and Materials: (V.3.6.3). Then, Gene Ontology (GO) Enrichment Analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) Enrichment Analysis, and Gene Set Enrichment Analysis (GSEA) were used to explore DEGs' bioinformatics functions and enriched pathways. We intersected DEGs with 259 ferroptosis-related genes from the FerrDb database. Finally, the mRNA levels of differentially expressed ferroptosis-related genes (DEFRGs) were validated in regorafenib-cultured cardiomyocytes to anticipate the link between DEFRGs and cardiotoxicity. Results: 747,1127,773 and 969 DEGs were screened out in adult human cardiomyocyte lines A, B, D, and E, respectively. The mechanism by which REG promotes cardiotoxicity associated with ferroptosis may be regulated by PI3K-Akt, TGF-beta, and MAPK. GSEA demonstrated that REG can promote cardiotoxicity by suppressing genes and pathways encoding extracellular matrix and related proteins, oxidative phosphorylation, or ATF-2 transcription factor network. After overlapping DEGs with ferroptosis-related genes, we got seven DEFRGs and found that ATF3, MT1G, and PLIN2 were upregulated and DDIT4 was downregulated. The ROC curve demonstrated that these genes predict regorafenib-induced cardiotoxicity well. Conclusion: We identified four DEFRGs which may become potential predictors and participate in the regorafenib-induced cardiotoxicity. Our findings provide possibility that targeting these ferroptosis-related genes may be an alternative for clinical prevention and therapy of regorafenib-related cardiotoxicity.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.018 |
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".