Defining Functional Heterogeneity In Acute Lymphoblastic Leukemia
Notice bibliographique
Résumé
Abstract Despite high survival rates for children with acute lymphoblastic leukemia (ALL), only 40% of adult patients will achieve long-term disease-free survival, and relapses in both pediatric and adult ALL are often fatal. Most current therapies are directed at molecular markers or dominant pathways present in the bulk of neoplastic cells, yet recent studies have identified many genetically distinct subclones co-existing within a single neoplasm. The functional properties and clinical relevance of these neoplastic subclones remain undefined. Genome wide copy number analysis of matched diagnostic and relapse ALL samples identified that in 50% of patients, the clones present at relapse are not the dominant clones at diagnosis, but have evolved from an ancestral pre-leukemic clone (Mullighan et al., 2008). In order to investigate the functional consequences of clonal evolution in disease progression and therapy resistance, we performed limiting dilution analysis of 3 diagnostic and 14 paired diagnostic/relapse samples from adult and pediatric B-ALL patients of varying cytogenetics, by transplantation into immune-deficient mice (xenografts). In one patient, the leukemia-initiating cell (LIC) frequency was 7.65 fold higher in the relapse sample than at diagnosis, while another patient showed the reverse with a 5.81 fold higher LIC frequency in the diagnostic sample. Two patients showed no significant differences in LIC frequency from diagnosis to relapse. LIC frequency varied from 1 in 14.2 to 1 in 4802 CD19+ blast cells. Interestingly, in 50% of the paired patient samples, transplantation of cells from the relapse sample gave rise to greater leukemic dissemination to the spleen and/or central nervous system of recipient mice in comparison to the diagnostic sample, despite similar levels of engraftment in the bone marrow. This data suggests that although the LIC frequency in B-ALL remains high and relatively static between diagnosis and relapse, relapse cells acquire increased invasive properties. To investigate the clonal composition of 3 diagnostic B-ALL samples, we undertook copy number variation (CNV) analysis of xenografts generated at both limiting and high transplanted cell doses. In all 3 samples, we detected subclones in the xenografts that were distinct from the predominant clone in the primary patient sample. We performed network analysis on these subclones and identified differentially enriched pathways, including differential expression of anti-apoptotic and apoptosis regulation pathways, providing evidence of putative functional differences. These results support the existence of functionally diverse subclones within diagnostic samples as well as functional diversity between the subclones present at diagnosis and relapse. Ongoing in depth genomic analysis of the diagnosis/relapse paired samples will add to our understanding of the functional role of the subclones identified at diagnosis in the establishment of disease relapse. In summary, these experiments will provide further insight into the functional heterogeneity present in B-ALL and the drivers of lymphoid leukemogenesis that lead to therapy failure and disease relapse. Disclosures: Danska: Trillium Therapeutics/Stem Cell Therapeutics: Research Funding.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,000 |
| 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 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 ».