Mutational analysis of tumor suppressor gene p53 in feline vaccine site-associated sarcomas
Bibliographic record
Abstract
OBJECTIVES: To investigate the role of tumor suppressor gene p53 mutation in feline vaccine site-associated sarcoma (VSS) development and to evaluate the relationship between p53 nucleotide sequence and protein expression. SAMPLE POPULATION: Formalin-fixed paraffin-embedded tissues of 8 feline VSS with dark p53 immunostaining (high p53 expression) and 13 feline VSS with faint or no staining (normal p53 expression). PROCEDURE: DNA was extracted from neoplastic and normal tissue from each paraffin block. The following 3 regions of the p53 gene were amplified by polymerase chain reaction: 379 base pair (bp) region of exon 5, intron 5, and exon 6, 108 bp region of exon 7, and 140 bp region of exon 8. Amplified p53 products were sequenced and compared with published feline p53. The p53 mutations identified were correlated with p53 mutations predicted by immunostaining. RESULTS: Neoplastic cells of 5 of 8 (62.5%) VSS that had high p53 expression harbored single missense mutations within the p53 gene regions examined. The p53 gene mutations were not detected in the 13 tumors with normal p53 immunostaining. Nonneoplastic tissues adjacent to all 21 VSS lacked mutations of these p53 gene regions. CONCLUSIONS: The p53 gene mutations were restricted to neoplastic tissue and, therefore, were unlikely to predispose to VSS. However, p53 mutations may have contributed to cancer progression in 5 of the 21 VSS. There was very good (kappa quotient = 0.67 with a confidence limit of 0.3 to 1.0), although not complete, agreement between prediction of mutation by p53 immunostaining and identification of mutations by sequencing of key p53 gene regions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".