p53 Degradation Activity, Expression, and Subcellular Localization of E6 Proteins from 29 Human Papillomavirus Genotypes
Bibliographic record
Abstract
Human papillomaviruses (HPVs) are the etiological agents of cervical cancer and other human malignancies. HPVs are classified into high- and low-risk genotypes according to their association with cancer. Host cell transformation by high-risk HPVs relies in part on the ability of the viral E6 protein to induce the degradation of p53. We report the development of a cellular assay that accurately quantifies the p53 degradation activity of E6 in vivo, based on the fusion of p53 to Renilla luciferase (RLuc-p53). This assay was used to measure the p53 degradation activities of E6 proteins from 29 prevalent HPV types and variants of HPV type 16 (HPV16) and HPV33 by determining the amount of E6 expression vector required to reduce by half the levels of RLuc-p53 (50% effective concentration [EC₅₀]). These studies revealed an unexpected variability in the p53 degradation activities of different E6 proteins, even among active types whose EC₅₀s span more than 2 log units. Differences in activity were greater between types than between variants and did not correlate with differences in the intracellular localization of E6, with most being predominantly nuclear. Protein and mRNA expression of the 29 E6 proteins was also examined. For 16 high-risk types, spliced transcripts that encode shorter E6*I proteins of variable sizes and abundances were detected. Mutation of the splice donor site in five different E6 proteins increased their p53 degradation activity, suggesting that mRNA splicing can limit the activity of some high-risk E6 types. The quantification of p53 degradation in vivo represents a novel tool to systematically compare the oncogenic potentials of E6 proteins from different HPV types and variants.
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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) | 0.000 | 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 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".