Introduction: Acute myeloid leukemia (AML) with retinoic acid receptor γ (RARG) rearrangement presents clinical, morphological, and immunophenotypic features similar to classic acute promyelocytic leukemia (APL). However, AML with RARG rearrangement exhibits different transcriptomic features compared to APL with PML-RARA or non-APL AML using bulk-RNA sequencing. To explore the biological heterogeneity, a comprehensive single-cell RNA sequencing (scRNA-seq) is essential to elucidate the molecular and genetic landscape of this disease.

Methods: A total of 10 participants (APL cases = 6, AML cases with RARG rearrangement = 2, healthy donors = 2) were included. Bone marrow samples were subjected to scRNA-seq. The sequencing data were processed using CellRanger (10x Genomics), and subsequent analyses were conducted with Seurat. Cell type annotation was performed utilizing SingleR, referencing the Human Primary Cell Atlas. Further analyses, including trajectory inference, pathway enrichment and score calculation, clonal evolution prediction and cellular communication, were conducted using R language.

Results: A detailed map of the hematopoietic cell states was created on 133,730 cells. Dimensionality reduction and unsupervised graph-based clustering revealed 14 distinct cell types, including hematopoietic stem cells (HSCs), granulocyte-monocyte progenitors (GMPs), promyelocytes, neutrophils, monocytes, plasma, B cells, T cells and NK cells. Further subdivision of myeloid cell populations revealed 12 subgroups, with CD38- promyelocytes and CD16- monocytes being markedly enriched in cases with RARG rearrangement. Compared with healthy controls and APL, the myeloid subsets of RARG rearrangement variants are characterized by the upregulation of specific genes, such as H1-10, H1-2, H2AZ1, H2AZ2, H3-3A, H3-3B, H4C3, MACROH2A1, SEPTIN7, and SNHG29. Furthermore, in contrast to APL the histone deacetylases class (HDAC) III pathway was up-regulated in CD38- promyelocytes of RARG rearrangement variants, and the interleukin-6 pathway was more highly activated in GMP subsets. Additionally, the pathways involved in necroptosis, neutrophil extracellular trap formation, and aminoacyl-tRNA biosynthesis were significantly upregulated across all myeloid cell subsets of RARG rearrangement variants. Subsequently, we employed Slingshot package to analyze data, which reconstructs putative branching transcriptional trajectories to identify potential relationships across calculated states. The five inferred trajectory paths in AML with RARG rearrangement were all derived from CD34+CD38+ HSCs. Notably, the trajectory path leading to leukemic promyelocytes demonstrated a significant overexpression of key genes, including XIST, AZU1, CTSG, and ELANE, in comparison to the paths transited into normal monocytes. Using inferCNV and UPhyloplot2, a clonal evolution analysis was conducted, revealing that some of the myeloid clusters in RARG rearrangement variants were predominantly characterized by a gain of chromosome 21q. In contrast, the originating APL myeloid cells across samples exhibited a loss of chromosome 6p and 8q. However, this chromosomal loss was observed at a lower frequency or was absent in AML with RARG rearrangement. Finally, cell communication revealed the specific pathways related to RARG rearrangement variants, as opposed to APL. These pathways were predominantly implicated in the activated effector memory CD8+GZMK+ T cells involved in immune suppression. The identified pathways included the incoming pathways of APP-CD74, LCK-CD8A-CD8B1, and MHC-I, as well as the CD99-CD99 outgoing pathway from this T subset.

Conclusions: This study elucidates the unique molecular characteristics of AML with RARG rearrangement using scRNA-seq, identifying specific gene overexpression, pathway activation and genetic alterations that may underpin therapy resistance. Notably, the HDAC III and interleukin-6 pathways emerge as potential therapeutic targets. Additionally, signaling pathways associated with immune suppression are implicated in RARG rearrangement variants. These insights can inform the development of targeted therapeutic strategies for AML with RARG rearrangement.

Disclosures

No relevant conflicts of interest to declare.

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