Abstract PO-022: Characterizing genetic and molecular differences in head and neck cancer based on history of smoking
Notice bibliographique
Résumé
Abstract Background: Even in the era of human papillomavirus (HPV)-associated disease, smoking remains an important cause of head and neck cancer (HNC). As genomic data emerges, it is important to examine whether there are molecular and genetic differences in HNC based on the history of smoking. Objective: This study aimed to characterize the genetic and molecular differences in a sample of patients with HNC based on smoking history. Methods: We used data from the Cancer Genome Atlas via cBioPortal for cancer genomics, and selected patients with a confirmed diagnosis of head and neck squamous cell carcinoma, independent of HPV status. Smoking history was defined as non-smokers (never smokers, n = 122) vs. smokers (current and previous history of smoking, n = 393). The genetic and molecular differences of interest were single nucleotide variation, copy number alteration, DNA methylation, mRNA expression and protein. Due to multiple testing, we report false discovery rate (FDR), with statistically significant FDR rate = 0.05. Results: The patients who were mainly White (85.8%), male (73.6%), diagnosed with stage IVA-C cancer (54.5%), and had a mean age of 60.8 years. There were significantly different copy number alterations on 10 genes, and the alterations were enriched in smokers (FDR < 0.05). Among these genes, two (FADD and CTTN) were significantly highly methylated in non-smokers (FDR<0.05), and one gene (ANO1) was marginally highly methylated in non-smokers (FDR=0.057). Four genes (PPFIA1, FGF19, CCND1 and LTO1) were highly expressed in mRNA in smokers (FDR< 0.05), while one gene (FADD) was marginally highly expressed in mRNA in smokers (FDR=0.079). FADD DNA methylation was negatively correlated with FADD mRNA expression in both non-smokers (Pearson r= -0.53, p<10−9) and smokers (Pearson r= -0.57, p<10−35). Among smokers, significant lower overall survival rate (p=0.033) among patients with FADD altered (median=35.3 months, CI 25.9-71.2) than those FADD unaltered (median=64.8 months, CI 48.2-89.3). Additionally, the CCND1 gene was highly mRNA expressed in smokers (FDR=0.007), and CCND1 mRNA expression was positively correlated with protein expressed in smokers (Pearson r=0.33, p<10−4) but not in non-smokers. For the CTTN gene, we found a significant high methylation in non-smokers (FDR=0.006) compared to smokers, but no significant difference in mRNA expression between smoking groups (FDR=0.17). Smokers with altered CTTN tended towards worse survival (p=0.069, median=35.8 months, CI 25.9-90.1) than unaltered CTTN ones (median=57.4 months, CI 48.2-88.8), and no difference in non-smokers. Conclusions: We found some significant genetic and molecular differences in HNC based on a history of smoking, especially for genes linked to mRNA overexpression. [which regulates tumor necrosis, apoptosis, and cell cycle] The findings suggest that there may be genetic and molecular differences in patients with HNC based on their history of smoking. However, further research is needed to confirm these findings in a larger study sample. Citation Format: Rong Jiang, Nosayaba Osazuwa-Peters, Tammara L. Watts. Characterizing genetic and molecular differences in head and neck cancer based on history of smoking [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-022.
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 | 0,001 |
| 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) | 0,003 | 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 ».