Abstract 3265: Characterization of epithelial oral dysplasia in non-smokers: working towards precision medicine
Bibliographic record
Abstract
Abstract Objectives: Although tobacco usage is still one of the strongest risk factors associated with oral cancer risk, there is a subset of non-smokers who develop oral cancer. Tobacco cessation efforts have resulted in a drop in oral cancer rates associated with this habit, leading to a growing interest in the increased proportion of cases occurring among non-smokers (NS). Lesions with oral epithelial dysplasia (OED) are at risk of progressing to oral cancer. Not only is the natural history of OED in NS poorly understood, but the path to interception of disease in NS is poorly defined. There is a gap in the knowledge surrounding the clinicopathological and genetic characterization, and the risk of progression in this growing category. This information is critical to the evolution of precision medicine in this subgroup. The aim of this study was to: 1) Describe the molecular and clinicopathological features of OED in NS as compared to smokers in longitudinal follow-up; and 2) To compare progression rates and time to progression in NS and smokers with OED. Methods: The study focused on cases with histologically confirmed mild or moderate OED in follow-up in the Oral Cancer Prediction Longitudinal Study. Clinicopathological data, including lesion site, size, texture, colour, consistency, border characteristics, fluorescence visualization (FV), and toluidine blue (TB) retention, were collected in addition to detailed smoking history. A genomic based marker test (gMART) which uses loss of heterozygosity (LOH) at key chromosomal loci to stratify lesions to progression risk, was performed on baseline biopsies. Progression was considered to be advancement to severe dysplasia, carcinoma in situ, or squamous cell carcinoma. Results: Out of 231 OED, 30% were NS related, based on self-reported smoking status. Although there were more smokers with OED than NS, a significantly higher proportion of the OED underwent malignant transformation in NS (P=.048). Although not significant, time to outcome was also faster in this group. Most clinical features were equally predictive except for lesion site. Ever smokers (ES) were more likely to have OED at the floor of mouth while OED was more likely to occur at the tongue or gingiva (P<.001) in NS. LOH risk patterns were strongly associated with progression (moderate risk = OR 4.84; high risk = OR 28.1; P=.001) and equally sensitive in both NS and ES subgroups. Conclusions: These findings support the premise that progressive lesions in NS and ES have some similar genetic underpinnings, and emphasize the need for clinicians to consider the molecular genomic profiles in the triage of OED. LOH markers can sort high-risk lesions, despite risk habits, and should be an important consideration in the treatment of OED. This marker is of particular use in the targeting of candidates for chemoprevention. Citation Format: Leigha D. Rock, Miriam P. Rosin, Lewei Zhang, Batoul Shariati, Denise M. Laronde. Characterization of epithelial oral dysplasia in non-smokers: working towards precision medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3265. doi:10.1158/1538-7445.AM2017-3265
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".