Abstract 5325: 5-hydroxymethylcytosine profiling identifies differential targeting in <i>IDH1</i> mutant versus <i>IDH1</i> wild-type high-grade gliomas
Notice bibliographique
Résumé
Abstract Glioblastoma demonstrates significant epigenetic dysregulation with subgroup differences highlighted by the Glioma CpG-Island Methylator Phenotype (G-CIMP) seen in IDH1 mutant tumors. 5-hydroxymethylcytosine (5hmC) has been implicated in IDH1 wild-type gliomas, however its role in IDH1 mutant tumors remains incompletely understood. We examined 5hmC profiles in high grade (WHO III/IV) IDH1 mutant (n = 12) and IDH1 wild-type (n = 9) tumors through parallel processing of samples using bisulfite (BS) and oxidative bisulfite (OxBS) conversion, with subsequent analysis on the Illumina MethylationEPIC Beadchip platform. Hydroxymethylation profiles were correlated with gene expression measured using the Affymetrix Human Gene 2.0 ST array platform. Cumulative density plots for mean 5hmC β-value across IDH1 mutant and wild-type tumors demonstrated 5hmC accumulation predominantly within the top 10th percentile of probes. No significant difference in global 5hmC levels between IDH1 mutant versus wild-type tumors was evident. Mean 5hmC β-values were 4.6%% and 3.8% for IDH1 mutant and wild-type tumors across all probes, respectively. To focus on regions with greatest 5hmC abundance, we assessed probes among the top 1% mean 5hmC β-values. In addition to probes with high 5hmC abundance, differentially hydroxymethylated (DHMR) regions were identified using the R package ChAMP, comparing IDH1 mutant to wild-type tumors. At the probe level, top 1% and DHMR probes demonstrated a relative increase in 5hmC among IDH1 mutant tumors versus IDH1 wild-type. Top 1% and DHMR probes were enriched for enhancer and super-enhancer regions in both IDH1 mutant and IDH1 wild-type tumors, however enhancer and super-enhancers targeted only partially overlapped. Pathway enrichment analysis for top 1% probe gene targets and DHMR-associated genes identified pathways implicated in glioma pathogenesis. Among genes characteristically ‘hypermethylated' in G-CIMP + tumors, 28/50 were methylated while 22/50 were hypermethylated in our IDH1 mutant cohort, suggesting that 5hmC contributes to overall methylation of G-CIMP target genes. 5hmC marked the most highly expressed genes in our tumor cohort, with increased expression associated with gene body hydroxymethylation. Among 1367 genes differentially expressed between IDH1 mutant and wild-type tumors, 48 demonstrated a positive significant Spearman correlation between probe 5hmC β-value and gene expression (r ≥ 0.5, p < 0.05), including genes implicated in gliomagenesis as well as novel candidates. This correlation was most evident for genes upregulated in the IDH1 mutant cohort. Citation Format: Wioletta Glowacka, Harshika Jain, Makiko Okura, Abulizi Maimaitiming, Romina Nejad, Mamatjan Yasin, Hamza Farooq, Kenneth Aldape, Paul Kongkham. 5-hydroxymethylcytosine profiling identifies differential targeting in IDH1 mutant versus IDH1 wild-type high-grade gliomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5325.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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 ».