Decoding Clonal Evolution in Relapsed T Cell Acute Lymphoblastic Leukemia at Single Cell Resolution

T-lineage acute lymphoblastic leukemia (T-ALL) comprises approximately 10-15% of pediatric ALL cases with distinct feature in biology and largely inferior outcome compared to B-ALL. Growing evidence has reflected pivotal roles of clonal evolution in T-ALL recurrence, but bulk sequencing may not serv...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Blood 2021-11, Vol.138 (Supplement 1), p.3482-3482
Hauptverfasser: Zhang, Jingliao, Duan, Yongjuan, Chang, Yanxia, Wang, Yue, Liu, Chao, Guo, Ye, Chen, Xiaojuan, Zhang, Li, Zhu, Xiaofan, Zhang, Yingchi
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:T-lineage acute lymphoblastic leukemia (T-ALL) comprises approximately 10-15% of pediatric ALL cases with distinct feature in biology and largely inferior outcome compared to B-ALL. Growing evidence has reflected pivotal roles of clonal evolution in T-ALL recurrence, but bulk sequencing may not serve as the perfect model to reliably infer clonal heterogeneities and their immunomodulatory milieu during leukemia development. In this study, single-cell sequencing was applied to uncover leukemic clonal relationships with relapse throughout chemotherapy in T-ALL at a more accurate resolution. We performed bulk whole-exome sequencing for sorted CD7 + BMMCs from 5 pairs of diagnosis-relapse (Dx_Rel) samples, revealing a series of well-reported hotspot mutations in T-ALL. Among those, we observed diagnosis-specific variations and relapse-emerged variations, suggesting the putative correlations with chemo-resistance. Transcriptomic sequencing highlighted additional stemness and metabolic abnormalities underlying leukemic re-occurrence. Incorporated Dx_Rel paired ATAC-seq depicted relapse-specific activated chromatin regions, such as ELK1, ELK4, RUNX1. To dissect clonal diversities within and across the 5 Dx_Rel T-ALL pairs, we carried out high-throughput droplet-based 5'-single-cell RNA-seq (scRNA-seq) and paired T cell receptor sequencing (scTCR-seq). By performing unsupervised clustering of scRNA-seq profiles encompassing 10 samples, we identified 23 distinct T-lineage clusters (Cluster 0-22) based on the two-dimensional UMAP visualization. In 2 out of 5 patients (T593 and T788), diffusion map of T-lineage sub-clusters between diagnostic and relapsed samples appeared to be almost identical, while distinct shifts from diagnosis to relapse in the compositions have been observed in the other 3 out of 5 patients (T956, T723 and T856). Besides, it was noteworthy that two T-cell sub-clusters were concluded as “normal” T cells (Cluster 9 and 12) uniformly presented in both diagnostic and relapsed diffusion of T-cell sub-clusters across 5 Dx_Rel, from which TCR repertoires and expression profiles could well discriminate leukemic cells. Next, we sought to further deconvolute the clonal evolution patterns for T-ALL Dx_Rel pairs. We observed that except in T788 lacking of clonal TCRs, dominant diagnostic clones of the other 4 patients diminished (T593) or vanished (T956, T723, T856) at relapse, sparing newly emerged subclones predominantly substituted at relapse. We clearly
ISSN:0006-4971
1528-0020
DOI:10.1182/blood-2021-153299