Abstract B057: Dual-omic characterization of pediatric solid tumors identified a subset of tumors with epigenetically altered immune phenotype
Notice bibliographique
Résumé
Abstract Background: Immune checkpoint blockades (ICBs) lack clinical efficacy in all-coming pediatric solid tumors. Gene expression-based classification of the tumor immune environment (TiME) can identify a subset of pediatric tumors with a rich immune environment, potentially actionable by ICBs. Methylation reprogramming is a major player in TiME modeling and ICB resistance, its role in pediatric tumors has been little explored. Hypothesis: dual-omic classification, combining DNA-methylation and RNA-sequencing, can identify tumors with epigenetically altered TiME, potentially responsible for ICB resistance. Objective: identify and characterize pediatric solid tumors with epigenetically altered immune phenotypes. Methods: We studied RNA-sequencing and DNA-methylation quantitative data from pediatric extra-cranial solid tumors. We used similarity network fusion (SNF) to individualize immune phenotypes. A preselected customized panel of 1226 immune genes, and their corresponding probes, were used for dual-omics clustering. Differential expression (DE) and methylation (DM) were performed between clusters using volcano3D. Scatter plots visualized the cis-regulation of probe-gene pairs with significant DE-DM. Gene set enrichment analyses (GSEA) were performed with clusterProfiler and gometh packages for DE and DM, respectively. Adjusted p values <0.01 were retained. Results: 184 samples were included. SNF clustering identified 3 phenotypes regrouping 52 (28%), 83 (45%), 49 (27%) samples in clusters (cl) 1, 2 and 3, respectively. Cl1 was characterized by a low expression of immune genes (cold phenotype), cl2 by overexpression in immune genes (hot phenotype), and cl3 by global hypermethylation (epigenetically altered phenotype). Both cl2 and cl3 overexpressed genes of immune checkpoints (CD274, PDCD1) and T-cell activator chemokines (CXCL9, CXCL10), central for ICB sensitivity. However, only cl2 overexpressed major histocompatibility complex (MHC) class I-II genes and their regulators (CIITA, TAP2), essential for antigen (Ag)-presenting machinery and immune recognition. Cl2 and 3 were also enriched for T-, B-cell and pro-inflammatory interferon gamma signaling pathways, known as ICB sensitivity biomarkers. Only cl2 was enriched in Ag processing and presentation pathway, confirming prior observation. DE-DM correlation showed that DNA-methylation programming induced overexpression of most immune genes (78%) in cl2, including CIITA, CXCR3 and MHC genes, when most immune genes (63%) were repressed by methylation in cl3. Methylation-based GSEA confirmed the epigenetic regulation of T- and B-cell signaling in cl2 and cl3, and for Ag presentation in cl2 only. Conclusion We demonstrated that DNA-methylation can reshape the TiME of pediatric solid tumors. We identified a subset of tumors with epigenetically altered immune phenotype characterized by inflamed immune environment but altered for Ag presentation by methylation reprogramming. Future studies should investigate methylation modulators to reverse these mechanisms and enable ICB sensitivity. Citation Format: Stéphanie Bianco, Anas Belaktib, Virgile Raufaste-Cazavieille, Charles Joly-Beauparlant, Lara Herrmann, Emeric Texeraud, Sylvie Langlois, Thomas Sontag, Alex Richard-St-Hilaire, Vincent-Philippe Lavallée, Thai Hoa Tran, Sonia Cellot, Daniel Sinnett, Arnaud Droit, Raoul Santiago. Dual-omic characterization of pediatric solid tumors identified a subset of tumors with epigenetically altered immune phenotype [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr B057.
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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 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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 | 0,001 |
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 ».