Hypoxia-inducible factor 1 and its role in viral carcinogenesis
Bibliographic record
Abstract
The advent of modern molecular biology has allowed for the discovery of several mechanisms by which oncoviruses promote carcinogenesis. Remarkably, nearly all human oncogenic viruses increase levels of the transcription factor hypoxia-inducible factor 1 (HIF-1). In this review, we highlight HIF-1׳s significance in viral oncogenesis, while providing an in-depth analysis of its activation mechanisms by the following oncoviruses: human papillomaviruses (HPVs), hepatitis B/C viruses (HBV/HCVs), Epstein-Barr virus (EBV), Kaposi׳s sarcoma-associated herpes virus (KSHV), and human T-cell lymphotropic virus (HTLV-1). We discuss virus-induced HIF-1׳s role in transcriptional upregulation of metabolic, angiogenic, and microenvironmental factors that are integral for oncogenesis. Admittedly, conclusive evidence is lacking as to whether activation of HIF-1 target genes is necessary for malignant transformation or merely a result thereof. In addition, a complete understanding of host-virus interactions, the effect of viral genomic variation, and the clinical (and potential therapeutic) relevance of HIF-1 in viral oncogenesis warrant further investigation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".