TP53 Gene Status Affects Survival in Advanced Mycosis Fungoides
Bibliographic record
Abstract
TP53 is frequently mutated in different types of neoplasms including leukemia and lymphomas. Mutations of TP53 have also been reported in mycosis fungoides (MF), the most common type of cutaneous lymphoma. However, little is known about the frequency, spectrum of mutations and their prognostic significance in MF. In this study we have optimized the protocol for Sanger sequencing of TP53 using DNA extracted from archival paraffin-embedded biopsies. Of 19 samples from patients with stage IIB MF or higher, 31% harboured mutations in TP53. Overall survival of the patients with mutated TP53 was significantly shorter than median survival in the age- and stage-matched patients treated in our Institution. Distribution of mutations was heterogenous in TP53 exons, however C>T transitions were common suggesting the causal role of ultraviolet radiation. We propose that TP53 mutation status would be useful for risk stratification of patients with advanced MF.
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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 | 0.000 | 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".