Inactive full-length p53 mutants lacking dominant wild-type p53 inhibition highlight loss of heterozygosity as an important aspect of p53 status in human cancers
Bibliographic record
Abstract
Over 1000 different mutants of the tumor suppressor protein p53 with one amino acid change in the core domain have been reported in human cancers. In mouse knock-in models, two frequent mutants displayed loss of wild-type (wt) p53 function, inhibition of wt p53 and wt p53-independent gain of function. The remaining mutants have been systematically characterized for loss of wt p53 function, but not other phenotypes. We report the concomitant assessment of loss of function and interference with wt p53 using URA3-based p53 yeast and confirmatory mammalian assays. We studied 76 mutants representing 54% of over 15 000 reported missense core domain mutations. The majority showed the expected complete loss of wt p53 function and dominant p53 inhibition. A few infrequent p53 mutants had wt p53-like activity. Remarkably, one-third showed no interference with wt p53 despite loss of wt p53 function at 37 degrees C. Half of this group consisted of temperature-sensitive p53 mutants, but the other half was surprisingly made up of mutants with complete loss of wt p53 function. Our findings illustrate the diverse behavior of p53 mutants and mechanisms of malignant transformation by p53 mutants. The identification of full-length p53 mutants without dominant inhibition of wt p53 highlights the importance of determining the status of the wt p53 allele in human cancers, in particular in the context of clinical studies. In the case of p53 mutants with no or weak dominant p53 inhibition, presence of the wt allele may indicate a good prognosis cancer, whereas loss of heterozygosity may spell an aggressive, therapy-resistant cancer.
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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) | 0.001 | 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".