Abstract P02: Uncovering Tailored Therapies for Acute Myeloid Leukemia in Children with Down Syndrome
Notice bibliographique
Résumé
Abstract Acute megakaryoblastic leukemia (AMKL), a subtype of acute myeloid leukemia (AML), is a rare hematological malignancy affecting children with Down syndrome (T21-AML) or without (non-DS-AMKL). T21-AML and non-DS AMKL are characterized by malignant megakaryoblasts that harbour distinct genetic profiles and prognoses. Prognoses for T21-AML are favourable; however, refractory/relapsed cases are met with dismal cure rates that are in part driven by drug resistance. Moreover, the paucity of patient samples introduces a challenge for studying this rare cancer. Thus, there is an urgency to develop a well-characterized model for uncovering novel therapies. Our group generated T21-AML patient xenograft models (PDX) by using primary DS patient samples, classified either as high- or low-risk according to co-occurring genetic alterations. Primary cells were transplanted into immunodeficient SGM3 mice. Through this method, we observed latencies between 2.9 to 3.0 weeks and 11.9 to 16.7 weeks for high-risk and low-risk primary mice, respectively. Engraftment and phenotypic characterization were done through flow cytometry and cytology. Phenotypic and molecular characterization of blasts from the bone marrow and spleen confirmed that the models recapitulate the disease. This was evident by the expression of previously characterized megakaryopoietic markers such as CD41 and CD61 and gene expression signatures correlating with leukemic patient profiles. Additionally, the models were sustained through serial transplantation for up to three generations. To monitor disease progression non-invasively, a luciferase-based bioluminescent model was engineered. Following optimization of cell culture conditions, high-throughput chemical screens against a library of 2,000 FDA-approved compounds were performed using a CellTiterGlo cell viability assay (n=1 high- and n=1 low-risk T21-AML PDX, along with normal CD34+ hematopoietic stem and progenitor cells/HSPC from cord blood). Drugs were identified as hits if they reduced the viability of leukemic cells by >75% with or without sparing normal CD34+ HSPC. Hits were validated using dose-response curve analyses and IC50 values were determined using a CellTiterGlo assay. We identified navitoclax, an apoptotic inducer with broad affinity to BCL-2, BCL-XL and BCL-W, BCL-XL-specific inhibitors, and other compound classes as potential therapeutic vulnerabilities. T21-AML PDX were resistant to venetoclax (e.g., IC50 >10µM), a selective inhibitor of BCL-2 currently used in pediatric relapsed/refractory malignancies. Overall, children affected by DS-AMKL generally fare favourable outcomes but endure long-term toxicities resulting from exposure to conventional genotoxic agents. Therefore, we generated a model of study to understand specific genotypes that would aid in the development of tailored therapies. Additionally, drug studies demonstrate BCL-XL as a therapeutic vulnerability as opposed to BCL-2. Our approach allows us to leverage the molecular understanding of this leukemia and discover a new realm of targeted therapeutics. Citation Format: Billy Ta, Emma Rose Cheetham, Sophie Cardin, Verena Gress, Anne-Cécile Soufflet, Nehme Hachem, Melanie Bilodeau, Sonia Cellot, Carolina Marmolejo, Louise Laramée. Uncovering Tailored Therapies for Acute Myeloid Leukemia in Children with Down Syndrome [abstract]. In: Proceedings of the Blood Cancer Discovery Symposium; 2024 Mar 4-6; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P02.
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 | 0,001 |
| 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 ».