Longitudinal single-cell transcriptomics reveals distinct patterns of recurrence in acute myeloid leukemia

Abstract

Background Acute myeloid leukemia (AML) is a heterogeneous and aggressive blood cancer that results from diverse genetic aberrations in the hematopoietic stem or progenitor cells (HSPCs) leading to the expansion of blasts in the hematopoietic system. The heterogeneity and evolution of cancer blasts can render therapeutic interventions ineffective in a yet poorly understood patient-specific manner. In this study, we investigated the clonal heterogeneity of diagnosis (Dx) and relapse (Re) pairs at genetic and transcriptional levels, and unveiled the underlying pathways and genes contributing to recurrence. Methods Whole-exome sequencing was used to detect somatic mutations and large copy number variations (CNVs). Single cell RNA-seq was performed to investigate the clonal heterogeneity between Dx-Re pairs and amongst patients. Results scRNA-seq analysis revealed extensive expression differences between patients and Dx-Re pairs, even for those with the same -presumed- initiating events. Transcriptional differences between and within patients are associated with clonal composition and evolution, with the most striking differences in patients that gained large-scale copy number variations at relapse. These differences appear to have significant molecular implications, exemplified by a DNMT3A/FLT3-ITD patient where the leukemia switched from an AP-1 regulated clone at Dx to a mTOR signaling driven clone at Re. The two distinct AML1-ETO pairs share genes related to hematopoietic stem cell maintenance and cell migration suggesting that the Re leukemic stem cell-like (LSC-like) cells evolved from the Dx cells. Conclusions In summary, the single cell RNA data underpinned the tumor heterogeneity not only amongst patient blasts with similar initiating mutations but also between each Dx-Re pair. Our results suggest alternatively and currently unappreciated and unexplored mechanisms leading to therapeutic resistance and AML recurrence.

Deep generative model deciphers derailed trajectories in acute myeloid leukemia

“…While AML presents significant genomic and transcriptomic heterogeneity across patients, suggesting multiple vulnerable states and origins of derailment from normal hematopoiesis 16,92 , we show Decipher’s ability to achieve personalized characterization of divergence from normal myeloid differentiation confirmed by genotyping, while the global geometry of trajectories is distorted by other integration methods. We characterized leukemic initiation marked with PROM1 expression.…”

Big data and single‐cell sequencing in acute myeloid leukemia research

“…Zhai et al 115 utilized scRNA‐seq to explore the clonal of diagnosis and relapse pairs at genetic and transcriptional levels and revealed the underlying pathways and genes leading to recurrence, suggesting alternative mechanisms leading to therapeutic resistance and AML recurrence. Clonal evolution in the stem cell compartment is nonlinear during myelodysplastic syndromes initiation and progression to AML, generating dominants clone as well as sub‐clones, with a reduced number of clones detectable in the blast compartment 116 .…”

Prognostic value of postinduction medullary myeloid recovery by flow cytometry in acute myeloid leukemia

“…for a single patient, the blastic population at diagnosis is heterogeneous, with coexisting clones expressing different genetic anomalies and immunophenotypic profiles. Minor clones hardly detectable at diagnosis can emerge after chemotherapy [3][4][5]. The overall survival (OS) in patients with de novo AML has been reported to be 44 months for young patients and dropped to 12 months for elderly patients (60 years and older) [6].…”