Comparison ofp53 mutations in patients with localized osteosarcoma and metastatic osteosarcoma
Bibliographic record
Abstract
BACKGROUND: In some malignancies, p53 mutations are associated with tumor progression. To address the role of p53 mutations in the development and progression of osteosarcoma, the authors analyzed specimens from 247 patients with primary localized osteosarcomas and 25 patients with osteosarcomas that were metastatic at the time of diagnosis. The group included 27 matched biopsy-resection specimens and 21 biopsy-metastasis paired specimens. METHODS: The authors examined the nature and location of p53 mutations (exons 4-10) by polymerase chain reaction-single-strand conformation polymorphism and confirmed mutations by direct DNA sequencing. RESULTS: The overall frequency of p53 mutations was 22% (60 of 272 specimens), with 13 of 60 mutations located in exons 4 or 10. A similar proportion of localized osteosarcomas had alterations of the p53 gene (55 of 247 specimens; 22.3%) compared with tumors from patients who had metastases at the time of diagnosis (5 of 25 specimens; 20%; P = 0.96). Patients who had p53 missense mutations were older compared with patients who had nonsense alterations or a wild type gene (P = 0.01). Examination of paired biopsy-resection and biopsy-metastasis specimens revealed that the p53 status was concordant between the biopsy and later tumor specimens in all patients. CONCLUSIONS: The p53 mutation status did not differentiate between patients who presented with a localized osteosarcoma and those who presented with metastases at the time of diagnosis. The current data indicate that p53 mutations are not late events in osteosarcoma tumor progression, because they are evident before the development of metastases. The inclusion of exons 4 and 10 increased the sensitivity of the analysis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".