Targeting the Human Papillomavirus 16 E6 Oncoprotein with Antibodies
Bibliographic record
Abstract
Abstract The human papillomavirus (HPV) 16 genome encodes two oncoproteins, E6 and E7, which are essential for viral carcinogenesis. While E7 promotes cell proliferation, E6 abolishes the resulting p53-dependent apoptotic response. Due to this specific function, E6 is considered a suitable target for the development of a variety of therapeutic agents such as antibodies. Here, we review anti-E6 antibodies/antibody fragments generated by us and others, as well as present our latest results with Camelidae -derived single-domain antibodies (sdAbs). We had previously isolated a pool of anti-E6 sdAbs to identify E6 binders with the potential to be used clinically and in research. While our previous work has focused on recombinant E6 proteins, here we evaluated these sdAbs’ binding capacity to the endogenous E6 protein using co-immunoprecipitation and immunofluorescence. We obtained reproducible results in these applications with two sdAbs, filling a gap in HPV research. Despite their apparent E6 binding ability, these sdAbs do not raise p53 levels or induce apoptosis. Thus, while these reagents are valuable diagnostic and detection tools, identifying their therapeutic potential will require further development and testing.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".