Unique FISH Patterns Associated with Cancer Progression of Oral Dysplasia
Bibliographic record
Abstract
Subgroups of patients with oral pre-malignant lesions (OPLs) are at extremely high risk for developing invasive cancer in spite of surgical excision. The objective of this study was to evaluate the utility of specific genes and their associated centromeres as markers to stratify OPLs for their cancer risk. Samples used in this study included 35 oral dysplasia with known outcome and 20 normal oral mucosa. Of the dysplasias, 20 were from an ongoing longitudinal study showing progression. The remaining 15 cases (2 of which progressed) were chosen from the population-based, provincial BC Oral Biopsy Service (OBS). Copy number alterations at EGFR, CEP7, CCND1, and CEP11 were evaluated by fluorescent in situ hybridization (FISH). There was no significant difference in demographics between progressors and non-progressors. Specific FISH profiles at these genes and their corresponding centromeres were associated with progression. High gene gain of CCND1 was associated with an 8-fold elevated risk of progression compared with those with no gain in time-to-progression analysis. Numerical alterations of EGFR and CCND1 and their centromeres might be an effective means for identifying OPLs at risk. Future studies will expand on this analysis and set the stage for application of this approach in routine clinical practice.
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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".