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Updated: Aug 5, 2026
Dissociation of Human and Mouse Tumor Tissue Samples for Single-cell RNA Sequencing
Published on: August 16, 2024
Single-cell RNA sequencing reveals immunological heterogeneity of the tumor microenvironment in acute myeloid
Junyi Li1,2, Huoyan Zhu1, Chaoqiong Ye1
1Department of Hematology, The Second Affiliated Hospital of Guangzhou Medical University, China.
Background:
Acute myeloid leukemia (AML) is a malignancy characterized by abnormal myeloid proliferation. Despite therapeutic advances, relapse is frequent. Understanding the tumor microenvironment (TME), particularly the dysfunction and interactions of natural killer (NK) cells, is essential for improving immunotherapeutic strategies such as chimeric antigen receptor T-cell (CAR-T) and chimeric antigen receptor natural killer cell (CAR-NK) therapies.
Objectives:
This study aimed to characterize the AML TME using single-cell RNA sequencing (scRNA-seq), focusing on NK cell dysfunction and their interactions with immunosuppressive cell populations.
Material And Methods:
We investigated single-cell RNA sequencing data from 59 samples, comprising 40 AML and 19 healthy donor (HD) samples, obtained from public sources and processed using standard methods. After quality control and doublet removal, 284,687 high-quality cells were retained. Acute myeloid leukemia malignant cells were identified using cluster-specific occupancy scores and inferred copy number variations. Batch effects were corrected with Harmony, followed by clustering and cell-type annotation using SingleR and established markers. We performed pathway activity profiling with gene set variation analysis (GSVA), explored intercellular communication using CellChat, and inferred cellular trajectories with Monocle3. Functional characteristics of NK cell subsets were evaluated using curated gene sets, and transcriptional regulation was assessed with pySCENIC.
Results:
Single-cell RNA sequencing of 40 AML and 19 HD samples identified 76 cell clusters, including patient-specific malignant cells with elevated copy number variations (CNVs). Acute myeloid leukemia samples showed altered immune composition, with increased plasma cells and hematopoietic stem cell (HSC)/progenitor populations. T-cell analysis revealed higher proportions of exhausted CD8+T_LAG3 and immunosuppressive CD4+T_FOXP3 cells in AML, while CD4+T_GZMK cells were more abundant in HD samples. Natural killer (NK) cells exhibited AML-specific subtypes, notably NK_CD56dim_DNAJB1, characterized by terminal exhaustion and high stress scores. Myeloid analysis showed elevated LAMP3+ dendritic cells and macrophages in AML. Notably, enhanced interactions between NK_CD56dim_DNAJB1 and CD8+ T cells via TGFB1-TGFBR signaling suggest key immunoregulatory mechanisms in AML progression.
Conclusions:
This study highlights the cellular heterogeneity and complex immune interactions within the AML microenvironment, offering insights into immune evasion and informing future immunotherapeutic and targeted treatment strategies.
