GEO series
Convergent Epigenetic Evolution Drives Relapse in Acute Myeloid Leukemia
GSE256495
Homo sapiens (human)
ChIP-seq / ATAC-seq (genome binding and open chromatin)
195 samples
Submitted 2024/04/17
Platform GPL20301Platform GPL24676
At a glance
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 195 samples
- What it is
- ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
- Organism
- Homo sapiens (human)
- Topic
- Acute myeloid leukemiaThis series is part of our curated briefing on it.
- Samples
- 195 samples: 195 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Convergent epigenetic evolution drives relapse in acute myeloid leukemiaeLife · 2024
Summary (written by the submitters)
Relapse of acute myeloid leukemia (AML) is highly aggressive and often treatment refractory. We analyzed previously published AML relapse cohorts and found that 40% of relapses occur without changes in driver mutations, suggesting that non-genetic mechanisms drive relapse in a large proportion of cases. We therefore characterized epigenetic patterns of AML relapse using 26 matched diagnosis-relapse samples with ATAC-seq.
Read the full summary ↓
This analysis identified a relapse-specific chromatin accessibility signature for mutationally stable AML, suggesting that AML undergoes epigenetic evolution at relapse independent of mutational changes. Analysis of leukemia stem cell (LSC) chromatin changes at relapse indicated that this leukemic compartment underwent significantly less epigenetic evolution than non-LSCs, while epigenetic changes in non-LSCs reflected overall evolution of the bulk leukemia. Finally, we used single-cell ATAC-seq paired with mitochondrial sequencing (mtscATAC) to map clones from diagnosis into relapse along with their epigenetic features. We found that distinct mitochondrially-defined clones exhibit more similar chromatin accessibility at relapse relative to diagnosis, demonstrating convergent epigenetic evolution in relapsed AML. These results demonstrate that epigenetic evolution is a feature of relapsed AML and that convergent epigenetic evolution can occur following treatment with induction chemotherapy.
Published in
Nuno K, Azizi A, Koehnke T et al.
· eLife 2024
· PMID 38647535
· doi:10.7554/eLife.93019
This dataset
Open GSE256495 in finder →
Find more
human ChIP / ATAC / CUT&Tag datasets →
Acute myeloid leukemia landscape →
Download · which file do I need?
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
1 · Just have a look
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
2 · Re-analyse it
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE256495_RAW.tar (it can run to tens of gigabytes).
3 · Start from the raw reads
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA1079789 and SRA study SRP491427. Searching any of these in the dataset finder brings you back here.
Study design
195 samples, each with a distinct title — no replicated groups
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 195 sample titles: 195 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
Samples in this study
- GSM8101643 Patient SU042 Diagnosis timepoint Blast replicate 1 ATACseq Sample
- GSM8101644 Patient SU042 Diagnosis timepoint Blast replicate 2 ATACseq Sample
- GSM8101645 Patient SU042 Relapse timepoint Blast replicate 1 ATACseq Sample
- GSM8101646 Patient SU042 Relapse timepoint Blast replicate 2 ATACseq Sample
- GSM8101647 Patient SU067 Diagnosis timepoint Blast replicate 1 ATACseq Sample
- GSM8101648 Patient SU067 Diagnosis timepoint Blast replicate 2 ATACseq Sample
- GSM8101649 Patient SU067 Relapse timepoint Blast replicate 1 ATACseq Sample
- GSM8101650 Patient SU067 Relapse timepoint Blast replicate 2 ATACseq Sample
- GSM8101651 Patient SU142 Diagnosis timepoint Blast replicate 1 ATACseq Sample
- GSM8101652 Patient SU142 Diagnosis timepoint Blast replicate 2 ATACseq Sample
- GSM8101653 Patient SU142 Relapse timepoint Blast replicate 1 ATACseq Sample
- GSM8101654 Patient SU142 Relapse timepoint Blast replicate 2 ATACseq Sample
- GSM8101655 Patient SU142 Relapse timepoint Bulk replicate 1 ATACseq Sample
- GSM8101656 Patient SU142 Relapse timepoint Bulk replicate 2 ATACseq Sample
- GSM8101657 Patient SU142 Relapse timepoint LSC replicate 1 ATACseq Sample
- GSM8101658 Patient SU142 Relapse timepoint LSC replicate 2 ATACseq Sample
- GSM8101659 Patient SU142 Diagnosis timepoint Bulk replicate 1 ATACseq Sample
- GSM8101660 Patient SU142 Diagnosis timepoint Bulk replicate 2 ATACseq Sample
- GSM8101661 Patient SU142 Diagnosis timepoint LSC replicate 1 ATACseq Sample
- GSM8101662 Patient SU142 Diagnosis timepoint LSC replicate 2 ATACseq Sample
- GSM8101663 Patient SU277 Diagnosis timepoint Blast replicate 1 ATACseq Sample
- GSM8101664 Patient SU277 Diagnosis timepoint Blast replicate 2 ATACseq Sample
- GSM8101665 Patient SU277 Relapse timepoint Blast replicate 1 ATACseq Sample
- GSM8101666 Patient SU277 Relapse timepoint Blast replicate 2 ATACseq Sample
- GSM8101667 Patient SU291 Diagnosis timepoint Blast replicate 1 ATACseq Sample
- GSM8101668 Patient SU291 Diagnosis timepoint Blast replicate 2 ATACseq Sample
- GSM8101669 Patient SU291 Relapse timepoint Blast replicate 1 ATACseq Sample
- GSM8101670 Patient SU291 Relapse timepoint Blast replicate 2 ATACseq Sample
- GSM8101671 Patient SU302 Diagnosis timepoint Blast replicate 1 ATACseq Sample
- GSM8101672 Patient SU302 Diagnosis timepoint Blast replicate 2 ATACseq Sample
- GSM8101673 Patient SU302 Diagnosis timepoint Bulk replicate 1 ATACseq Sample
- GSM8101674 Patient SU302 Diagnosis timepoint Bulk replicate 2 ATACseq Sample
- GSM8101675 Patient SU302 Relapse timepoint Blast replicate 1 ATACseq Sample
- GSM8101676 Patient SU302 Relapse timepoint Blast replicate 2 ATACseq Sample
- GSM8101677 Patient SU302 Relapse timepoint Bulk replicate 1 ATACseq Sample
- GSM8101678 Patient SU302 Relapse timepoint Bulk replicate 2 ATACseq Sample
- GSM8101679 Patient SU302 Relapse timepoint LSC replicate 1 ATACseq Sample
- GSM8101680 Patient SU302 Relapse timepoint LSC replicate 2 ATACseq Sample
- GSM8101681 Patient SU302 Diagnosis timepoint LSC replicate 1 ATACseq Sample
- GSM8101682 Patient SU302 Diagnosis timepoint LSC replicate 2 ATACseq Sample
+ 155 more — browse all 195 samples with per-sample file links →
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Share this dataset
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.