Study of the carcinogenic potential of the E6 protein of human papillomavirus type 16
Bibliographic record
Abstract
While most Human papillomavirus (HPV) infections are asymptomatic and self-resolved, high-risk types, such as HPV-16 and HPV-18 are responsible for 99% of cervical cancers worldwide, whereas low-risk types, such as HPV-6 and HPV-11, are responsible for 90% of genital warts. While the different types of HPV and their varying oncogenicities have been studied extensively, it is still not clear what features of a HPV type make it more oncogenic than another. Two aspects which could affect the oncogenicity of HPV were studied: HPV variants and the E6 protein’s interaction with membrane associated guanylate kinase (MAGUK) proteins. Previous studies have shown that some HPV-16 variants may be more oncogenic than others. The first goal of this work was to characterise the HPV-16 variants in a Manitoba cervical cancer sample population to possibly identify mutations which could be associated with an increased risk of developing cervical cancer. Seventy-five samples from different individuals were sequenced in three distinct regions: the long control region and the E6 and E7 open reading frames. The DNA sequences obtained from these genomic regions were then compared between HPV-16 cervical cancer samples and Manitoba HPV-16 non cancer samples to identify any mutations that were exclusive to the cervical cancer samples. No specific mutations in any of the regions could be associated with cervical cancer. It is also proposed that HPV16 E6 protein’s interaction with MAGUK proteins contributes to its oncogenicity since low-risk E6 proteins lack this ability. The second goal of this work was to investigate which regions of high-risk HPV E6 proteins are needed in order to achieve MAGUK protein degradation, more specifically MAGI-1 degradation. Wild-type high-risk HPV16E6, low-risk HPV6E6, as well as mutants, were synthesized and cloned into vectors. In vitro translated proteins were used in MAGI-1 degradation assays. The ability of both wild-type HPV6 and HPV16 E6 proteins to degrade MAGI-1 was confirmed. Based on the performance of the different mutants in these degradation assays, it was determined that the PDZ-binding domain is necessary but not sufficient to induce E6-induced MAGI-1 degradation. In conclusion, it was determined that the entire HPV16 E6 protein is needed for the induction of MAGI-1 degradation.
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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 | 0.001 | 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) | 0.001 | 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".