Abstract C53: The genetic evolution of oral cancer fields
Notice bibliographique
Résumé
Abstract Introduction: The evolution of oral cancer results from the accumulation of genetic alterations. Field cancerization, where histologically or molecularly abnormal cells surround a clinically visible tumor to a wider extent, imposes a challenge to delineate surgical boundaries. We applied a newly emerging optical technique using direct fluorescence visualization (FV) to redefine the field of alteration. Using genomic profiling we examined multiple biopsies within the field to assess clonal expansion of cells within this optically altered field. Experimental Approach: A hand-held FV device was used in the operating room to define the field that extended beyond the margins of clinically visible oral cancer. Multiple biopsies (N=15) were taken within the altered FV field (FV loss or FVL) and the surgical margins with no FVL, as controls, from three patients. Histological assessment and microdissection were performed for each biopsied sample. The genomic profile of each sample was generated using a tiling-path DNA microarray. A breakpoint detection algorithm was used to define genetic breakpoints and clonal ordering was performed to infer the sequence of genetic events of samples within each patient. Result: Early stage low-grade dysplasias were found within the FVL field in all patients, while no dysplasia was detected in the areas with no FVL. In general, each field is histologically and genetically heterogeneous. Specifically, patient A presented with a clinically identifiable SCC (#1), while another SCC (#3) was found in an area 10-mm anterior to SCC#1, which was not clinically apparent but showed FVL. A moderate dysplasia (#2) was found between SCC#1 and SCC#3. Interestingly, 5q, 8p, and 8q loss were common among all three samples (suggesting a common progenitor), while genetic alterations (e.g., high-level amplification on 9p22.3-pter) accumulated in both SCC#3 and dysplasia#2 but was absent in SCC#1. On the other hand, SCC#1 accumulated different genetic changes (e.g., gain of 11q13.2-q13.4 (CCND1)). This suggested that two clonal lineages were present within this cancerous field. Similarly, in patient B, the biopsies obtained revealed both common and different genetic signatures. For example, a moderate dysplasia showed genetic alterations specific to this lesion (e.g., high-level amplification of 8q11.21 (SNAI2)), while its corresponding carcinoma in situ harbored numerous different genetic alterations, including three regions of high-level amplification (e.g., 20q11.23 (SRC)). Genomic profiles of these samples suggest that two different genetic pathways diverged from a common progenitor, while subsequent genetic alterations accumulated for the formation of each unique subpopulation. In patient C, one genetic pathway was found governing the development of the clinically identifiable SCC, and increased genetic alterations were detected in the SCC compared to the mild dysplasia. All the controls did not show matching genetic changes. Conclusion: Our results indicate that the genetics of the oral cancer field is extremely dynamic, where different clones are evolving in the field. Genetic alterations occurring early in the genetic pathway may be important events that prime the area for further development of cancer. These findings provide evidence for the importance of implementing optical technologies in defining surgical margins as well as the importance of tailored targeted therapies to effectively treat different subclones of a field. Citation Information: Cancer Res 2009;69(23 Suppl):C53.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».