Abstract A55: Defining the transcriptional regulation of pediatric AML as a new strategy to find potential druggable vulnerabilities
Notice bibliographique
Résumé
Abstract Introduction: Nearly 35% of children with acute myeloid leukemia (AML) die, despite aggressive but toxic and nonspecific therapies. New approaches to find and drug pediatric AML targets are clearly needed. Super enhancers (SEs), large regions of highly active chromatin, define cell state and cell identity by regulating oncogenes in many cancers. Recent enhancer profiling of 66 adult AML patient samples revealed SE-defined, prognostically relevant subgroups. An SE was at the retinoic acid receptor alpha (RARA) gene locus in 59% of the samples, which were sensitive to the RARA agonist tamibarotene. We are delineating the transcriptional regulation of pediatric AML (pAML) by SE analysis, which has already elucidated deeper insights into pediatric leukemogenesis, as typified by RARA regulation. Methods: Four AML/APL cell lines and 19 pAML primary samples were enhancer profiled by H3K27Ac chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-seq). SEs were detected and assigned to genes using the rank ordering of super-enhancers (ROSE) algorithm. Tamibarotene treatment of cell lines and patient samples were assessed for gene and protein expression changes and phenotypic differences. Results: The primary pAML sample cohort encompassed the diverse pAML cytogenetic subtypes, with an over-representation of KMT2A rearrangements (n=9, 47%). The number of unique enhancer regions was nearly saturated in the 19 samples. Median SE size was 3,780bp, much larger than the 511bp of typical enhancers. When SE regions across all samples were clustered together, a RARA SE was seen in two of the ten clusters. Some of the highly correlated, SE-associated genes in these clusters encode proteins involved in inflammation. Eleven of the 19 samples (58%) contained a RARA SE, crossing multiple cytogenetic subtypes. Tamibarotene treatment of RARA SE+ pAML cell lines and patient samples reduced cell viability and increased apoptosis (detected by annexin V+ and activated caspase 3/7), with no effect in RARA SE- pAML samples. In the RARA SE+ samples, tamibarotene increased CD38 (a myeloid differentiation marker usually suppressed by ligand-unbound RARA) and DHRS3 (another RARA target gene used as a pharmacodynamic biomarker in the adult tamibarotene phase II trial). Conclusion: We have profiled the enhancer landscapes of 19 primary pAML samples, the largest dataset of its kind, and have seen a high frequency of a RARA SE in pAML. Tamibarotene has antiproliferative, proapoptotic, and prodifferentiation effects in RARA SE+ pAML. We are confirming these results in a RARA SE+ patient-derived xenograft mouse model, evaluating combinations, and interrogating other SE-regulated genes interacting with RARA that may predict degree of response or resistance to tamibarotene. Our studies confirm that studying the transcriptional regulation of pAML samples through SE analysis can identify druggable targets and also lay the preclinical foundation for a biomarker-defined tamibarotene trial in pediatric AML. Citation Format: Monika Perez, Alfred Daramola, Oscar Sias-Garcia, Helen Wei, Nikitha Cherayil, Charles Y. Lin, Joanna S. Yi. Defining the transcriptional regulation of pediatric AML as a new strategy to find potential druggable vulnerabilities [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A55.
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 | 0,001 | 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) | 0,003 | 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 ».