Comparison of HPV infection, p53 mutation and allelic losses in post‐transplant and non‐posttransplant oral squamous cell carcinomas
Bibliographic record
Abstract
BACKGROUND: Oral squamous cell carcinoma (SCC) is increasingly found in transplant recipients, although little is known of the natural history of the disease or the mechanism underlying this increase. METHODS: In this article we describe the history of development of 5 oral post-transplant SCCs (PSCCs) and compare their genetic profiles to 34 non-posttransplant SCCs (NPSCCs). RESULTS: Of the five patients with PSCCs, 3 had bone marrow transplants and two, kidney. All three PSCCs from bone marrow recipients were preceded locally by graft-vs.-host disease (GVHD). Two of the GVHD were biopsied and demonstrated dysplasia. Similar frequencies of loss of heterozygosity (LOH) occurred in PSCCs and NPSCCs at 3p, 9p, 17p and 8p, with lower frequencies in PSCCs at 4q (39% vs. 0%), 11q (53% vs. 20%) and 13q (45% vs. 20%), although the latter were not significantly different. Only 1 PSCC had a p53 mutation, compared to historical values of 40-60% for NPSCC. Interestingly, human papillomavirus (HPV) DNA was detected in 3 (60%) PSCCs, in comparison to only 4 (12%) of the 34 NPSCCs (P = 0.0346). CONCLUSIONS: Dysplasia in oral GVHD may be a strong indicator of cancer risk and should not be regarded as reactive changes to lichenoid mucosites. The low level of p53 mutation and increased HPV infection support the involvement of HPV in the development of PSCC, while the similarity in LOH patterns suggests that other aspects of carcinogenesis may be comparable in these two types of SCCs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".