CircRHOT1 restricts gastric cancer cell ferroptosis by epigenetically regulating GPX4
Bibliographic record
Abstract
Background: Gastric cancer (GC) is a malignant form of cancer that severely threatens human health. Despite developments on treatment, the prognosis of patients with advanced GC remains poor. Hence, the identification of detailed molecular mechanisms and potential therapeutic targets is of great importance for GC study. In recent years, circular RNAs have been widely reported to be important regulators in cancer initiation and progression. This study sought to evaluate the function of circRHOT1 in GC development. Methods: Clinical specimens were collected from patients with GC to detect the level of circRHOT1. The expression of circRHOT1 in several GC cell lines was detected by quantitative real-time polymerase chain reaction. Cell Counting Kit 8 (CCK-8), colony formation, and xenograft tumor growth experiments were performed to check cell proliferation. Cell ferroptosis was determined by the levels of intracellular iron, Fe2+ (Divalent iron ion), lipid reactive oxygen species, malondialdehyde, and glutathione. The protein levels of SLC7A11 and glutathione peroxidase-4 (GPX4) were detected by western blot assays. The epigenetic regulation of the GPX4 gene was analyzed by chromatin immunoprecipitation assays. Results: CircRHOT1 was more highly expressed in the GC tumors than the adjacent non-tumor tissues. The knockdown of circRHOT1 significantly suppressed cell growth (P<0.05) and stimulated the ferroptosis of the GC cells (P<0.05). CircRHOT1 recruited KAT5 (Acetyltransferase Tip60) to promote the acetylation of lysine 27 on histone H3 protein subunit (H3k27Ac) of the GPX4 gene and stimulated gene transcription. The overexpression of KAT5 and GPX4 notably reversed the anti-proliferation effect of circRHOT1 depletion (P<0.05). Conclusions: CircRHOT1 promoted GC progression and suppressed ferroptosis by recruiting KAT5 to initiate GPX4 transcription. Our findings showed that cirRHOT1 is a promising target for GC treatment.
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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) | 0.002 | 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".