Abstract A006: Assessment of EBV DNA methylation to guide antiviral use in EBV-associated lymphoma
Notice bibliographique
Résumé
Abstract Introduction/Objective: Epstein-Barr Virus (EBV) is an oncogenic herpesvirus driving development of human lymphomas. EBV uses DNA methylation to silence its genome and switch from a lytic (actively replicating) to a latent (dormant) state. Clinical treatment decisions for EBV-associated (EBV+) lymphomas are limited by current diagnostics which provide no information on EBV’s activation state, despite this playing an important role in lymphoma pathogenesis. The antiviral ganciclovir (GCV) is effective specifically against lytic EBV due to viral BGLF4 expression, a kinase that activates GCV. The Baiocchi group discovered that BGLF4 expression in otherwise latent EBV+CNS lymphomas was associated with favorable outcomes when patients received GCV-containing treatment regimen GARD. This indicated improved EBV+ lymphoma outcomes with GCV, yet we cannot determine which patients will benefit. We hypothesized that DNA methylation loss at BGLF4 indicates its expression and is associated with GCV response, serving as a potential DNA biomarker to determine which patients are suitable GCV candidates. Methods: We established a high-throughput PCR and mass spectrometry assay quantifying methylation of n=12 CpG sites at the BGLF4 promoter. The assay was validated against the EpiTYPER methylation assay (R^2=0.766), methylation standards, and the limit of detection was determined to be 625 copies/reaction. We assessed n=136 EBV+ patient plasma samples from a cross-sectional study cohort including EBV-reactivations, post-transplant lymphoproliferation (PTLD), B-, T- and NK-cell lymphomas. Methylation was analyzed with unsupervised clustering and overlaid with in vitro luciferase reporter data for respective BGLF4 DNA elements. Retrospective chart review was performed to determine GCV use and response association with BGLF4 methylation. Results: We identified n=4 CpG sites within BLGF4 that are heterogeneously methylated among samples and highlight the BGLF4 core promoter. Preliminary analysis showed that across disease groups, patients who responded to GCV had a significantly lower BGLF4 methylation (p=0.0007) than patients who did not respond to GCV. Comparatively, we saw no significant difference in BGLF4 methylation of rituximab responders versus non-responders (p=0.343). These results suggest BGLF4 demethylation may indicate lytic EBV activity and thus response to GCV. Conclusions/Significance: Site specific BGLF4 methylation loss is widespread in EBV+ lymphoma. Administration of GCV, a drug that has already been well studied and is FDA-approved, may be guided by EBV methylation, serving as a biomarker to improve patient outcomes in EBV-driven lymphomas. Citation Format: Cara M. Noel, Christoph Weigel, Haley LT. Klimaszewski, Ada C. Sher, Kurits M. Host, Yue-Zhong Wu, Sarah Y. Schlotter, Elshafa H. Ahmed, Eric Brooks, Christopher C. Oakes, James S. Blachly, Mark Lustberg, Timothy Voorhees, Robert A. Baiocchi. Assessment of EBV DNA methylation to guide antiviral use in EBV-associated lymphoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr A006.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».