Long noncoding RNA HIF1A-AS2 facilitates cell survival and migration by sponging miR-33b-5p to modulate SIRT6 expression in osteosarcoma
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Long noncoding RNAs (lncRNAs) are emerging as vital regulators in various physiological and pathological processes. It was recently found that lncRNA HIF1A-AS2 could play oncogenic roles in several cancers. However, the function and regulatory mechanism of lncRNA HIF1A-AS2 in osteosarcoma (OS) remain largely unclear. In this study, we demonstrated that HIF1A-AS2 was overexpressed in OS tissues and cells. Downregulation of HIF1A-AS2 significantly affects multiple biological functions in OS cells, including cell proliferation, cell cycle progression, cell apoptosis, cell migration, and cell invasiveness. Mechanistic investigations demonstrated that HIF1A-AS2 can interact with miR-33b-5p and negatively regulate its expression, thereby upregulating the protein expression of miR-33b-5p's target SIRT6. Additionally, in vivo experiments using a xenograft tumor mouse model revealed that downregulation of HIF1A-AS2 suppresses tumor growth in OS. Taken together, a newly identified regulatory mechanism for the lncRNA HIF1A-AS2-miR-33b-5p-SIRT6 axis was systematically studied in OS, which could be a promising target for the treatment of OS.
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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".