<i>HOXD-AS1</i> interacting with AMPK causes a disturbance in mTOR signaling, impairing ferroptosis in glioma
Bibliographic record
Abstract
Ferroptosis, a recently discovered form of cell death, plays an important role in cancer progression. It has been reported that ferroptosis plays a complex regulatory role in the biological processes of glioma. In glioma, the long noncoding RNA, HOXD cluster antisense RNA 1 ( HOXD-AS1), functions as an oncogene, contributing to glioma progression. However, its potential functions in ferroptosis are unclear. Herein, we aimed to clarify the biological function and detailed molecular mechanism of HOXD-AS1 in regulating ferroptosis in glioma. Firstly, cell viability, reactive oxygen species (ROS), and malondialdehyde (MDA) content assays were detected. The mechanisms of HOXD1-AS1’s effect on ferroptosis were evaluated by detecting glutathione, Cys, and solute carrier family 7 member 11 (SLC7A11) levels. RNA immunoprecipitation and RNA pull-down techniques were employed to explore whether HOXD-AS1 can directly bind AMP-activated protein kinase (AMPK). Our findings indicated that HOXD-AS1 levels were augmented significantly in glioma tissue. HOXD-AS1 knockdown induced MDA and ROS accumulation, subsequently resulting in ferroptosis. Further molecular analysis showed that the binding between HOXD-AS1 and AMPK regulated the mechanistic target of rapamycin kinase pathway, inhibit the transport of Cys, and decrease the production of glutathione, eventually resulting in ferroptosis. Our study revealed that HOXD-AS1 regulates cell ferroptosis, thus its downregulation might be an effective strategy to suppress glioma.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".