<scp>HIF</scp> ‐1/2α: The Silent Architects of Adenoid Cystic Carcinoma—A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: Adenoid cystic carcinoma (AdCC) is a rare, aggressive salivary gland malignancy with a poor prognosis due to metastasis and local recurrence. Although hypoxia-inducible factors-1/2α (HIF-1/2α) play crucial roles in AdCC, their pleiotropic effects remain poorly understood. This systematic review and meta-analysis evaluates the impact of HIF-1/2α in AdCC progression. METHODS: A comprehensive literature search was conducted across PubMed, Scopus, EMBASE, and Web of Science to identify studies examining HIF-1/2α in AdCC. Study quality was assessed using the modified Newcastle-Ottawa scale, and meta-analyses were performed using IBM SPSS Statistics (Version 29). RESULTS: Sixteen studies met inclusion criteria, with 10 studies encompassing 650 AdCC cases included in the meta-analysis. Positive HIF-1/2α expression was reported in 77.4% of AdCC cases (95% CI: 0.630-0.919, p < 0.001) and was significantly correlated with tumor size (OR: 0.38, 95% CI: 0.16-0.89, p = 0.03), advanced stage (OR: 2.86, 95% CI: 1.74-4.71, p < 0.001), and distant metastasis (OR: 1.82, 95% CI: 1.02-3.25, p = 0.04). Human studies demonstrated significantly increased HIF-1/2α protein and mRNA expression in AdCC cases compared to control groups. Solid-type AdCC exhibited predominantly higher nuclear HIF-1α expression than cribriform and tubular subtypes. Additionally, in cell culture models, the hypoxia-induced upregulation of these factors increased the expression of VEGF (20-fold), BNIP3 (6-fold), and NID1, promoting angiogenesis, epithelial-mesenchymal transition, autophagy, and invasiveness. CONCLUSION: HIF-1/2α emerge as a pivotal drivers of AdCC progression, serving dual roles as prognostic biomarker and therapeutic target, necessitating further clinical investigation through multicenter validation studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| 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".