Transcriptomics

Dataset Information

0

Single-cell molecular analysis defines therapy-response and immunophenotype of stem cell populations in CML


ABSTRACT: Understanding leukemia heterogeneity is critical for the development of curative treatments as the failure to eliminate therapy-persistent leukemic stem cells (LSCs) may result in disease relapse. Here we have combined high-throughput immunophenotypic screens with large-scale single-cell gene expression analysis to define the heterogeneity within the LSC-population in chronic phase (CP) chronic myeloid leukemia (CML) patients at diagnosis and following conventional tyrosine kinase inhibitor (TKI) treatment. Our results reveal substantial heterogeneity within the putative LSC population in CP-CML and demonstrate differences in response to subsequent TKI-treatment between distinct subpopulations. Importantly, LSC subpopulations with myeloid and proliferative molecular signatures are proportionally reduced at a higher extent in response to TKI-therapy compared to subfractions displaying primitive and quiescent signatures. Additionally, cell surface expression of the CP-CML stem cell markers CD25, CD26 and IL1RAP is high on all subpopulation at diagnosis, but downregulated and unevenly distributed across subpopulations in response to TKI-treatment. The most TKI-insensitive cells of the LSC-compartment can be captured within the CD45RA- fraction and further defined as positive for CD26 in combination with an aberrant lack of cKIT expression. Thus, our results reveal the heterogeneity of the CML stem cell population and propose a Lin-CD34+CD38-/lowCD45RA-cKIT-CD26+ population to be targeted for improved therapy response.

ORGANISM(S): Homo sapiens

PROVIDER: GSE84507 | GEO | 2017/01/27

SECONDARY ACCESSION(S): PRJNA329514

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2023-06-16 | GSE206421 | GEO
2014-04-17 | E-GEOD-40721 | biostudies-arrayexpress
2014-04-17 | GSE40721 | GEO
2016-06-01 | E-GEOD-76123 | biostudies-arrayexpress
2022-11-29 | GSE180496 | GEO
2013-01-01 | GSE43225 | GEO
2013-01-01 | E-GEOD-43225 | biostudies-arrayexpress
2019-04-02 | GSE124125 | GEO
2024-01-17 | GSE236233 | GEO
2016-06-01 | GSE76123 | GEO