Tumourigenesis Driven by the Human Papillomavirus Type 16 Asian-American E6 Variant in a Three-Dimensional Keratinocyte Model
Bibliographic record
Abstract
Infection with a transforming human papillomavirus (HPV) such as type 16 (of species Alphapapillomavirus 9) causes ano-genital and oral tumours via viral persistence in human squamous cell epithelia. Epidemiological studies showed that the naturally occurring HPV16 Asian-American (AA) variant (sublineage D2/D3) is found more often than the European Prototype (EP) (sublineage A1) in high-grade cervical neoplasia and tumours compared to non-cancer controls. Just three amino acid changes within the early gene, E6, of HPV16 AA have been linked to this augmented tumourigenicity. The AAE6 variant's greater immortalizing and transforming potential over EPE6 has recently been confirmed in retrovirally-transduced keratinocytes expressing the E6 gene only. However, the tumourigenic role of the full-length viral genome of HPV16 has not yet been addressed with regard to these E6 variants. To investigate this process in the context of these two HPV16 E6 genotypes, an organotypic tissue culture model was used to simulate the HPV infectious life cycle. The AAE6 variant demonstrated an enhanced ability over EPE6 to drive the viral life cycle toward tumourigenesis, as evidenced phenotypically-by a more severe grade of epithelial dysplasia with higher proliferation and deregulated differentiation, and molecularly-by high viral oncogene E6 and E7 expression, but lack of productive viral life cycle markers. In contrast, EPE6 had low E6 and E7 but high E1∧E4 expression, indicative of a productive life cycle. We suggest increased viral integration into the host genome for AAE6 as one possible mechanism for these observed differences from EPE6. Additionally, we found downstream effects on immortalization and host innate immune evasion. This study highlights how minor genomic variations in transforming viruses can have a significant affect on their tumourigenic ability.
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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) | 0.001 | 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".