Abstract 6234: Single-cell analysis of state-transition from health to leukemia and the leukemic cell heterogeneities in inv(16) acute myeloid leukemia (AML)
Authors: Fu Yu-Hsuan , Zhang Lianjun , Chen Ying-Chieh , Frankhouser David E. , Uechi Lisa , O'Meally Denis , Branciamore Sergio , Marcucci Guido , Rockne Russell , Kuo Ya-Huei 
Published: March 2024

AML is an aggressive hematological malignancy with heterogeneous genetic abnormalities. Using a conditional knock-in mouse model (Cbfb56M/+/Mx1-Cre) to mimic the somatic acquisition of fusion gene CBFB-MYH11 (CM), created in the recurrent chromosome translocation inv(16)(p13q22) of AML, we previously reported that the blood transcriptome undergoes state-transition from health to leukemia. In this study, we analyze the transcriptomic alterations and leukemic cell heterogeneities in a leukemia state-space using single-cell RNA sequencing (scRNA-seq). CM expression was induced in Cbfb56M/+/Mx1-Cre mice by poly (I:C) injection, and scRNA-seq analysis was performed on peripheral blood mononuclear cells (PBMC) and bone marrow (BM) cells from leukemic mice and age-matched wild-type (WT) controls. More than 105,000 cells were subjected to the following dimensionality reduction and cell type annotation. By performing principal component analysis (PCA), we observed a Y-shape cell distribution with emergence of a divergent branch occupied by leukemic cells which can be mapped to a leukemic state. The principal components 1 and 2 (PC1 and PC2) clearly distinguish the leukemic cells from normal cell types such as myeloid cells and lymphocytes. By accessing the eigenvalue of genes for PC1 and PC2, we quantified the crucial genes and pathways related to leukemia progression at a single-cell level. We characterized cKit+ leukemic cell clusters by transcriptome-based correlation and gene expression pattern and found that they resembled stem cells and megakaryocytic-erythroid progenitors (MEP) with dysregulated pathways, including upregulated "inflammatory response" and downregulated pathways related to Myc targets, oxidative phosphorylation, mitochondrial protein translation, and ribosomal biogenesis/assembly. Examining the 31 clusters (C0-C30) seen in cKit+ BM cells, we identified 9 leukemic clusters exhibiting distinct features, including high heme-metabolism (C0, C1, and C2), high proliferation (C1, C8), S phase (C4, C10), low oxidative phosphorylation (C2, C5, C17), high Cd9 (C10), high Egfl7 (C7, C8). In conclusion, our study unveils state-transition from health to leukemia at single-cell resolution, and uncovers diverse biological heterogeneities associated with the inv(16) AML state. Further refinement of transcriptome state-transition and single-cell analysis will provide an analytical framework for modeling the dynamic changes during disease evolution at the single-cell level.

Citation Format: Yu-Hsuan Fu, Lianjun Zhang, Ying-Chieh Chen, David E. Frankhouser, Lisa Uechi, Denis O'Meally, Sergio Branciamore, Guido Marcucci, Russell Rockne, Ya-Huei Kuo. Single-cell analysis of state-transition from health to leukemia and the leukemic cell heterogeneities in inv(16) acute myeloid leukemia (AML) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6234.