Relapse-Initiating Clones Preexisting at Diagnosis in B- Cell Acute Lymphoblastic Leukemia Help Predict Molecular Pathways of Relapse
Notice bibliographique
Résumé
Abstract Disease recurrence remains a significant cause of mortality in B-cell acute lymphoblastic leukemia (B-ALL). Genomic analysis of matched diagnosis and relapse samples have demonstrated that relapse arises from a minor subclone already present at diagnosis and not the dominant clone in the majority of patients. However, the reasons why only some clones survive therapy and generate relapse are obscure and elucidation of the mechanisms that underlie these differing fates may be revealed by functional analysis of isolated subclones. Previous work has shown that the subclonal diversity in B-ALL exists at the level of the leukemia-initiating cells capable of generating patient derived xenografts (Notta et al., Nature, 2011). In order to investigate the functional consequences of genetic clonal evolution during disease progression, we performed in-depth genomic and functional analysis of 14 paired diagnosis/relapse samples from adult and pediatric B-ALL patients with varying cytogenetic abnormalities. Diagnosis-specific, relapse-specific, and shared clonal and subclonal variants were identified by whole exome sequencing of the patient samples. Targeted sequencing of these variants in 372 xenografts generated by transplantation of CD19+ cells in a limiting cell dilution assay uncovered clonal variation. This analysis provided for the unequivocal identification of minor subclones ancestral to the relapse, termed diagnosis Relapse-Initiating (dRI) clones, in the diagnostic sample. Our xenografting approach enabled the physical isolation of dRI clones providing a unique opportunity to interrogate their epigenetic and transcriptional landscapes in order to unravel their relapse initiating capacity. To this end, representative diagnosis, dRI and relapse clones from 5 of the 14 patients were subjected to RNAseq and ATACseq (assay for transposase-accessible chromatin using sequencing) analysis. Despite the differences in transcriptional and chromatin openness between patients, principal component analysis of subclones from individual patients positioned the dRI clones as evolutionary intermediates between the diagnosis and relapse clones. Hierarchical clustering of the most significantly differentially expressed genes and open chromatin regions demonstrated that dRI clones shared gene expression and chromatin accessibility signatures with both the dominant diagnosis clone as well as the dominant relapse clone. To gain mechanistic insight into the data we used gene set enrichment analysis (GSEA) and identified common molecular pathways present in all patients that were enriched in dRI clones and persisted at the time of relapse in comparison to the dominant diagnosis clone. dRI and relapse clones converged in the activation of genes involved in cellular functions such as endocytosis, autophagy and innate immune response. In addition, cell surface proteins like ABC transporters and ephrins were also upregulated in dRI and relapse clones. Remarkably, functional interrogation of dRI clones in secondary xenografts, in comparison to more representative diagnosis clones, displayed increased tolerance to standard chemotherapeutic agents (dexamethasone, L-asparaginase and vincristine). Investigation of the molecular pathways and cellular receptors/transporters identified by gene expression analysis are being assessed in vitro and in vivo as potential targets for novel therapeutic approaches and disease monitoring. Overall, we have shown evidence that minor subclones at diagnosis, ancestral to the relapse clone, possess functional advantages and unique properties over other diagnostic subclones prior to treatment exposure. In depth analysis of pathways identified in these dRI subclones will shed light on potential new therapeutic approaches for abrogating and reducing disease recurrence in B-ALL. Disclosures Mullighan: Amgen: Honoraria, Speakers Bureau; Cancer Prevention and Research Institute of Texas: Consultancy; Abbvie: Research Funding; Pfizer: Honoraria, Research Funding, Speakers Bureau; Loxo Oncology: 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 | 0,001 |
| 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 | 0,000 | 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 ».