USP22 promotes hypoxia-induced hepatocellular carcinoma stemness by a HIF1α/USP22 positive feedback loop upon TP53 inactivation
Bibliographic record
Abstract
OBJECTIVE: We aimed to elucidate the mutual regulation mechanism of ubiquitin-specific protease 22 (USP22) and hypoxia inducible factor-1α (HIF1α), and the mechanism they promote the stemness of hepatocellular carcinoma (HCC) cells under hypoxic conditions. DESIGN: Cell counting, migration, self-renewal ability, chemoresistance and expression of stemness genes were established to detect the stemness of HCC cells. Immunoprecipitation, ubiquitination assay and chromatin immunoprecipitation assay were used to elucidate the mutual regulation mechanism of USP22 and HIF1α. HCC patient samples and The Cancer Genome Atlas data were used to demonstrate the clinical significance. In vivo USP22-targeting experiment was performed in mice bearing HCC. RESULTS: USP22 promotes hypoxia-induced HCC stemness and glycolysis by deubiquitinating and stabilising HIF1α. As direct target genes of HIF1α, USP22 and TP53 can be transcriptionally upregulated by HIF1α under hypoxic conditions. In TP53 wild-type HCC cells, HIF1α induced TP53-mediated inhibition of HIF1α-induced USP22 upregulation. In TP53-mutant HCC cells, USP22 and HIF1α formed a positive feedback loop and promote the stemness of HCC. HCC patients with a loss-of-function mutation at TP53 and high USP22 and/or HIF1α expression tend to have a worse prognosis. The USP22-targeting lipopolyplexes caused high tumour inhibition and high sorafenib sensitivity in mice bearing HCC. CONCLUSION: USP22 promotes hypoxia-induced HCC stemness by a HIF1α/USP22 positive feedback loop on TP53 inactivation. USP22 is a promising target for the HCC therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".