Abstract 2758: Methylome plasticity as a biomarker of treatment response in small cell lung cancer
Notice bibliographique
Résumé
Abstract Background: Small cell lung cancer (SCLC) is an aggressive disease with poor treatment outcomes, in part due to epigenetic mechanisms driving tumor growth and resistance. Cell-free DNA methylome profiles in untreated SCLC can identify prognostic sub-groups, making it a useful biomarker. In this study, we hypothesize that changes in the cell free methylome of SCLC influence disease response to therapy and drive treatment resistance. Methods: Cell free methylated DNA immunoprecipitation followed by sequencing (cfMeDIP-seq) was performed on 34 baseline-relapse paired samples belonging to a cohort of SCLC patients treated at the Princess Margaret Cancer Centre (Toronto, Canada). Matched leukocyte DNA methylation profiles were incorporated to exclude the contribution of non-cancer methylation to the cfMeDIP signal and allow focused profiling of changes in the SCLC methylome through first-line treatment. The plasticity of the SCLC methylome was determined by subtracting the reads per kilobase of transcript per million mapped reads (RPKM) at the time of progression compared to the pre-treatment timepoint. A methylome demonstrated plasticity if it showed an increase or decrease in reads compared to the median RPKM across all samples in the cohort. Associations between methylation groups and relevant clinical data were identified. Kaplan-Meier and Cox regression analysis were performed to determine if methylome changes were associated with overall survival and progression-free survival, anchored from the time of SCLC diagnosis. KEGG pathways corresponding to the top differentially methylated windows between baseline and relapse pairs were identified and characterized. Results: Plasticity of the SCLC methylome were seen in 67% of patients (n=23/34). Methylome plasticity was found to be associated with a shorter time to progression from the end of first-line treatment (mean difference = 70 days; 95% CI 25-115, p = 0.0031). Accordingly, patients with greater methylome plasticity were more likely to be platinum resistant (57% vs. 17%; χ-squared p = 0.033). Cox regression showed that methylome plasticity was significantly associated with worse progression free survival (PFS) (adjusted hazard ratio [aHR] = 5.7, p = 0.0010) and overall survival (OS) (aHR = 1.9, p = 0.11), after adjusting for VA stage at diagnosis. Pathway analysis of differentially methylated windows mapped to genes related to neuronal polarity and axonal guidance, as well as Wnt signaling. Conclusion: Changes in cell-free DNA methylomes serve as a biomarker for treatment response in SCLC. Increased plasticity of the methylome is associated with shorter PFS. The underlying biology of this relationship may involve changes in pathways that govern neuronal change and established cancer-associated pathways. Citation Format: Danielle Benedict Sacdalan, Sami Ul Haq, Luna Jia Zhan, Janice J. Li, Vivek Philip, Scott V. Bratman, Geoffrey Liu, Benjamin H. Lok. Methylome plasticity as a biomarker of treatment response in small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2758.
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) | 0,001 | 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 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 ».