Abstract 3265: Characterization of epithelial oral dysplasia in non-smokers: working towards precision medicine
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».