Genomic and transcriptomic determinants of clinical outcomes in patients with AML and DNMT3A mutations
RNA-seq (gene expression) · human · 264 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Topic
- Acute myeloid leukemiaThis series is part of our curated briefing on it.
- Samples
- 264 samples: 184 × DNMT3Awt vs 80 × DNMT3AmutGroups 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
- Genomic and transcriptomic determinants of clinical outcomes in patients with AML and DNMT3A mutationsBlood cancer journal · 2025
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE297413_RAW.tar (it can run to tens of gigabytes).
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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1263813 and SRA study SRP586281. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 264 samples.
How we read this: 2 replicated groups read from 264 sample titles; they account for 264 of them. 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.
- GSM8990559 DNMT3Amut_01 DNMT3Amut
- GSM8990560 DNMT3Amut_02 DNMT3Amut
- GSM8990561 DNMT3Amut_03 DNMT3Amut
- GSM8990562 DNMT3Amut_04 DNMT3Amut
- GSM8990563 DNMT3Amut_05 DNMT3Amut
- GSM8990564 DNMT3Amut_06 DNMT3Amut
- GSM8990565 DNMT3Amut_07 DNMT3Amut
- GSM8990566 DNMT3Amut_08 DNMT3Amut
- GSM8990567 DNMT3Amut_09 DNMT3Amut
- GSM8990568 DNMT3Amut_10 DNMT3Amut
- GSM8990569 DNMT3Amut_11 DNMT3Amut
- GSM8990570 DNMT3Amut_12 DNMT3Amut
- GSM8990571 DNMT3Amut_13 DNMT3Amut
- GSM8990572 DNMT3Amut_14 DNMT3Amut
- GSM8990573 DNMT3Amut_15 DNMT3Amut
- GSM8990574 DNMT3Amut_16 DNMT3Amut
- GSM8990575 DNMT3Amut_17 DNMT3Amut
- GSM8990576 DNMT3Amut_18 DNMT3Amut
- GSM8990578 DNMT3Amut_19 DNMT3Amut
- GSM8990581 DNMT3Amut_20 DNMT3Amut
- GSM8990584 DNMT3Amut_21 DNMT3Amut
- GSM8990588 DNMT3Amut_22 DNMT3Amut
- GSM8990590 DNMT3Amut_23 DNMT3Amut
- GSM8990591 DNMT3Amut_24 DNMT3Amut
- GSM8990592 DNMT3Amut_25 DNMT3Amut
- GSM8990593 DNMT3Amut_26 DNMT3Amut
- GSM8990594 DNMT3Amut_27 DNMT3Amut
- GSM8990595 DNMT3Amut_28 DNMT3Amut
- GSM8990596 DNMT3Amut_29 DNMT3Amut
- GSM8990597 DNMT3Amut_30 DNMT3Amut
- GSM8990598 DNMT3Amut_31 DNMT3Amut
- GSM8990599 DNMT3Amut_32 DNMT3Amut
- GSM8990600 DNMT3Amut_33 DNMT3Amut
- GSM8990601 DNMT3Amut_34 DNMT3Amut
- GSM8990602 DNMT3Amut_35 DNMT3Amut
- GSM8990603 DNMT3Amut_36 DNMT3Amut
- GSM8990604 DNMT3Amut_37 DNMT3Amut
- GSM8990605 DNMT3Amut_38 DNMT3Amut
- GSM8990606 DNMT3Amut_39 DNMT3Amut
- GSM8990607 DNMT3Amut_40 DNMT3Amut
+ 224 more — browse all 264 samples with per-sample file links →
- GSE122515 Bonn Dataset 3 of meta-analysis on AML classification, RNAseq dataset 0 samples same disease briefing · shares aml
- GSE137851 The long non-coding RNA HOXB-AS3 regulates ribosomal RNA transcription in NPM1-mutated acute myeloid leukemia 387 samples same disease briefing
- GSE270185 Repurposing CD19-directed immunotherapies for pediatric t(8;21) acute myeloid leukemia 249 samples same disease briefing
- GSE303795 Halofuginone exerts broad-spectrum cytotoxic effects by regulating p-eIF2α-S100A8/A9-calcium signaling, inhibiting global protein synthesis, and reversing the resistance of idarubicin in acute myeloid leukemia 6 samples same disease briefing
- GSE137574 Kevetrin induces apoptosis in TP53 wild-type and mutant acute myeloid leukemia cells 24 samples same disease briefing
- GSE129437 Genome-wde mapping of BRD9 binding sites and gene expression changes upon BRD9 knockdown 6 samples same disease briefing
- GSE289713 Superior preclinical efficacy of co-treatment with BRG1/BRM and FLT3 inhibitor against AML cells with FLT3 mutations 11 samples shares aml, mutations, clinical
- GSE289435 Single-cell transcriptional atlas of hematopoiesis reveals genetic and hierarchy-based determinants of aberrant differentiation in AML 13 samples shares aml, determinants
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.