Transcriptomics

Dataset Information

0

Single-cell transcriptomic profiling reveals immune cell heterogeneity in acute myeloid leukaemia peripheral blood mononuclear cells after chemotherapy


ABSTRACT: Purpose Acute myeloid leukaemia (AML) is a heterogeneous disease characterised by the rapid clonal expansion of abnormally differentiated myeloid progenitor cells residing in a complex microenvironment. However, the immune cell types, status, and genome profile of the peripheral blood mononuclear cell (PBMC) microenvironment in AML patients after chemotherapy are poorly understood. In order to explore the immune microenvironment of AML patients after chemotherapy, we conducted this study for providing insights into precision medicine and immunotherapy of AML. Methods In this study, we used single-cell RNA sequencing (scRNA-seq) to analyse the PBMC microenvironment from five AML patients treated with different chemotherapy regimens and six healthy donors. We compared the cell compositions in AML patients and healthy donors, and performed gene set enrichment analysis (GSEA), CellPhoneDB, and copy number variation (CNV) analysis. Results Using scRNA-seq technology, 91,772 high quality cells of 44,950 PBMCs from AML patients and 46,822 PBMCs from healthy donors were classified as 14 major cell clusters. Our study revealed the sub-cluster diversity of T cells, natural killer (NK) cells, monocytes, dendritic cells (DCs), and haematopoietic stem cell progenitors (HSC-Prog) in AML patients under chemotherapy. NK cells and monocyte-DCs showed significant changes in transcription factor expression and chromosome copy number variation (CNV). We also observed significant heterogeneity in CNV and intercellular interaction networks in HSC-Prog cells. Conclusion Our results elucidated the PBMC single-cell landscape and provided insights into precision medicine and immunotherapy for treating AML.

ORGANISM(S): Homo sapiens

PROVIDER: GSE235857 | GEO | 2023/08/31

REPOSITORIES: GEO

Similar Datasets

2021-07-01 | GSE169428 | GEO
2023-09-28 | GSE218999 | GEO
| PRJNA354364 | ENA
2021-09-10 | GSE183817 | GEO
2016-05-14 | E-GEOD-79605 | biostudies-arrayexpress
2006-10-27 | GSE6112 | GEO
2021-08-31 | GSE159028 | GEO
2012-07-31 | E-GEOD-39345 | biostudies-arrayexpress
2019-02-28 | GSE116256 | GEO
2014-10-02 | E-GEOD-61926 | biostudies-arrayexpress