Transcriptomics

Dataset Information

0

Single cell analyses reveals a non-canonical EZH2 activity as main driver of RA resistance in PLZF/RARA leukemia [RNA-seq]


ABSTRACT: Resistance to treatment is due to the heterogeneity of the tumor which contains a subset of cancer cells that escape treatment and are responsible for the relapse. We took advantage of the PLZF/RARA retinoic acid (RA) resistant acute promyelocytic leukemia (APL) model to catch relapse-initiating cell features and their vulnerabilities. By developing an integrative single-cell multi-omics analysis (scRNA-seq and scATAC-seq), we uncovered transcriptional and chromatin heterogeneity of the PLZF/RARA APL blasts. We highlighted a subset of cells insensitive to RA-induced differentiation with a strong DNA repair signature ("Rep" cluster) and exhibiting a fine tuned transcriptional network targeting the histone methyltransferase Ezh2. Combining epigenomic profiling with mouse-derived models for Ezh2 catalytic inhibition or total KO, we revealed an independent methyltransferase Ezh2 activity linked to RA resistance. These findings demonstrate the power of single-cell multi-omics integration to highlight paths to sensitize therapy-resistant leukemia cells

ORGANISM(S): Mus musculus

PROVIDER: GSE206345 | GEO | 2022/08/22

REPOSITORIES: GEO

Dataset's files

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

Similar Datasets

2022-08-22 | GSE181189 | GEO
2022-08-22 | GSE181188 | GEO
2022-08-22 | GSE181186 | GEO
2022-07-01 | GSE181187 | GEO
2014-01-11 | E-GEOD-51723 | biostudies-arrayexpress
2014-01-11 | GSE51723 | GEO
2016-02-17 | E-GEOD-77946 | biostudies-arrayexpress
2016-02-17 | GSE77946 | GEO
2022-12-14 | GSE173754 | GEO
2022-12-14 | GSE173753 | GEO