Abstract 3405: Characterizing treatment response in head and neck cancer through viral ctDNA quantification and fragment length
Notice bibliographique
Résumé
Abstract Background: Head and neck cancer (HNC) is the sixth most common cancer type worldwide, and despite decreases in the rates of Human Papillomavirus (HPV)-negative HNC, an alarming increase in HPV+ HNC is occurring. Circulating tumor (ct)DNA isolated from liquid biopsy has been shown to have clinical utility as a biomarker in cancer, with ctDNA levels and fragment size used to monitor treatment response. Methods: The aim of this study was to determine the presence of ctDNA in liquid biopsy (plasma and saliva) of HPV+ HNC patients to non-invasively monitor treatment response and disease progression. Blood and saliva samples were collected from 45 HPV+ HNC patients and 14 HPV-negative controls at the McGill University Health Centre before and/or after surgical resection. Samples were analyzed using droplet digital PCR (ddPCR) with primers and probes for HPV16/HPV18, the most common subtypes of HPV in HNC, accounting for 97% of cases in North America. Analysis was performed for all patients with confirmed follow-up scans and/or pathology. ctDNA levels were correlated with disease course as determined through imaging (>6 months post-sampling) and pathological examination. Results: ctDNA was detectable in 21/23 (91%) patients prior to treatment and 8/36 (22%) post treatment. In the two patients who were not positive for ctDNA prior to treatment, tumor tissue was found to be negative for HPV DNA despite being p16-positive by immunohistochemistry. Patients showed shifts in ctDNA fragment length in longitudinal samples following treatment. All post-treatment patients with no detectable ctDNA had no signs of recurrence/residual disease on follow-up imaging. In contrast, all 8 patients who tested positive for ctDNA post-treatment showed signs of recurrence on follow-up imaging. In our cohort, 14 patients had matched pre- and post-treatment samples and all showed major reductions in ctDNA post treatment compared to pre-treatment, with 12/14 patients having a complete loss of detectable ctDNA. Concordance between the presence of ctDNA in saliva and plasma was found in 86% of patients. ctDNA was only detected in one analyte in 6 patients (3 in plasma only and 3 in saliva only). Conclusion: HPV ctDNA was successfully detected in saliva and blood of patients with HPV-positive HNC, with a sensitivity of 92% for ctDNA prior to treatment, and a sensitivity of 100% when adjusted for tumor HPV status as opposed to p16 staining. The inclusion of both plasma and saliva in analysis increases the sensitivity of assays, with the use of both analytes allowing for the detection of ctDNA in patients with low plasma DNA levels and for patients who did not have salivary ctDNA, potentially due to inability to produce sufficient saliva or tumor location. The presence of ctDNA correlated with treatment response, indicating the potential of HPV ctDNA for monitoring tumor progression in HPV-positive HNC patients. Citation Format: Sarah Tadhg Ferrier, Anthony Zeitouni, Nader Sadeghi, Thupten Tsering, Julia V. Burnier. Characterizing treatment response in head and neck cancer through viral ctDNA quantification and fragment length [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3405.
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 | 0,001 | 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 | 0,001 |
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 ».