Fluorescent In Situ Hybridization for TP53 in the Diagnosis of Pediatric Osteogenic Sarcoma
Bibliographic record
Abstract
Osteogenic sarcoma (OS) is the most common malignant bone tumor in children and adolescents. Despite advances in molecular genetic characterization of pediatric and adult tumors, the diagnosis of OS still depends almost entirely on light microscopy. The lack of consistent genetic changes in OS has greatly hindered the development of any diagnostic molecular test. Recently, whole-genome sequencing has shown that ~50% of cases of OS have a translocation involving the TP53 gene with breakpoints confined to the first intron. We developed a 2 color break-apart fluorescent in situ hybridization (FISH) probe for intron 1 of TP53 and applied it to an archived series to assess its diagnostic utility. The study group included 37 cases of OS (including osteoblastic, chondroblastic, and fibroblastic), as well as 53 cases of non-OS pediatric sarcomas (including Ewing sarcoma, rhabdomyosarcoma, undifferentiated small cell sarcoma, CCNB3-BCOR sarcoma, CIC-DUX sarcoma, synovial sarcoma, and malignant peripheral nerve sheath tumor) and 27 cases of benign bone lesions (including osteoblastoma, chondromyxoid fibroma, fibrous dysplasia, and fibro-osseous dysplasia). A rearranged signal was found in 20/37 cases (54%) of OS and in none of the other sarcomas or benign bone lesions, giving the FISH test 100% specificity for a diagnosis of OS. p53 immunostaining was generally not predictive of the results obtained by FISH and could not substitute for this test. This FISH probe offers a simple and specific genetic test to aid in the diagnosis of OS, despite the genetic complexity of this tumor.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".