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Omics · study · 2026

A Role for Rapid Transcription Dynamics in Cytarabine Resistance in Acute Myeloid Leukemia [ATAC-seq]

Listed in NCBI GEO

Chemotherapy resistance remains a critical challenge in the treatment of patients with cancer including acute myeloid leukemia (AML).

Description

While genetic alterations contribute to chemotherapy resistance, rapid-adaptive non-genetic mechanisms, particularly transcription dynamics, remain poorly understood. Given the role of cell-intrinsic transcriptional variability in cell fate decisions, understanding and targeting chemotherapy-induced changes in transcription dynamics could offer new strategies to prevent chemotherapy resistance.

In this study, we demonstrate that short-term treatment with the widely used chemotherapeutic cytarabine (AraC) leads to the rapid emergence of RNA-induced AML cells with increased AraC resistance in both cell lines as well as primary patient samples. Mechanistically, through global transcriptomic analyses and targeted high-resolution analysis of transcription dynamics using single-molecule RNA FISH, we found rapid induction of transcriptional dynamics and upregulation of key transcription factors (TFs) - which we term “AraC rapid response TFs (ARR-TFs)” and which include PU.1 and GATA1 – following chemotherapy treatment.

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At a functional level, short-term pre- and co-treatment with RNA transcription inhibitors effectively suppressed chemotherapy-induced RNA induction and prevented resistance acquisition, in both in vitro and in vivo models. Furthermore, we found that CRISPR-mediated suppression of PU.1 and GATA1 induction significantly attenuated AraC resistance. In summary, our findings reveal a previously unrecognized role of rapid and early adaptive transcriptional dynamics in AML chemotherapy resistance, highlighting master TFs as key regulators of drug resistance.

These insights offer a novel, pharmacologically targetable and accessible approach to alleviate chemotherapy resistance, and encourage further testing with the ultimate goal to improve AML treatment outcomes.

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Life Sciences
Inferred from text
Cancer 75%
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
NCBI GEOGSE32405812 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · NCBI GEOconnector:ncbi_geo@1.0.0
concepts[disease].local:disease:cancerenrichment · NCBI GEOkeyword-concept-rules@1.0.0title+description (75%)
concepts[field].local:field:life-sciencesmapping · NCBI GEOconnector:ncbi_geo@1.0.0
concepts[method].geo_series_type:genome-binding-occupancy-profiling-by-high-throughput-sequencingsource · NCBI GEOconnector:ncbi_geo@1.0.0/gdstype
concepts[organism].NCBITaxon:9606source · NCBI GEOconnector:ncbi_geo@1.0.0/taxon
descriptionsource · NCBI GEOconnector:ncbi_geo@1.0.0/summary
publication_datesource · NCBI GEOconnector:ncbi_geo@1.0.0
titlesource · NCBI GEOconnector:ncbi_geo@1.0.0/title