Retinoic acid and ascorbate synergize to suppress myeloid leukemia via TET2 activation [MV4-11 RNA-Seq]
RNA-seq (gene expression) · human · 12 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)
- Samples
- 12 samples: 3 × MV4-11, vehicle, RNA-seq, vs 3 × MV4-11, LAA, RNA-seq, vs 3 × MV4-11, ATRA, RNA-seq, vs 3 × MV4-11, LAA+ATRA, RNA-seq,Groups 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
- Retinoic acid and ascorbate synergize to suppress myeloid leukemia via TET2 activationCell reports · 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 GSE298864_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 PRJNA1271517 and SRA study SRP589639. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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.
- GSM9025280 MV4-11, vehicle, RNA-seq, rep5 MV4-11, vehicle, RNA-se…
- GSM9025281 MV4-11, vehicle, RNA-seq, rep6 MV4-11, vehicle, RNA-se…
- GSM9025282 MV4-11, vehicle, RNA-seq, rep7 MV4-11, vehicle, RNA-se…
- GSM9025283 MV4-11, LAA, RNA-seq, rep5 MV4-11, LAA, RNA-seq,
- GSM9025284 MV4-11, LAA, RNA-seq, rep6 MV4-11, LAA, RNA-seq,
- GSM9025285 MV4-11, LAA, RNA-seq, rep7 MV4-11, LAA, RNA-seq,
- GSM9025286 MV4-11, ATRA, RNA-seq, rep5 MV4-11, ATRA, RNA-seq,
- GSM9025287 MV4-11, ATRA, RNA-seq, rep6 MV4-11, ATRA, RNA-seq,
- GSM9025288 MV4-11, ATRA, RNA-seq, rep7 MV4-11, ATRA, RNA-seq,
- GSM9025289 MV4-11, LAA+ATRA, RNA-seq, rep5 MV4-11, LAA+ATRA, RNA-s…
- GSM9025290 MV4-11, LAA+ATRA, RNA-seq, rep6 MV4-11, LAA+ATRA, RNA-s…
- GSM9025291 MV4-11, LAA+ATRA, RNA-seq, rep7 MV4-11, LAA+ATRA, RNA-s…
- GSE240497 Activation of a nongenetic AHR-ELMSAN1 axis optimizes BET-targeting therapy and suppresses leukemia stem cells in preclinical models 66 samples shares activation, suppress, leukemia
- GSE211434 Diverse immune suppressing cancer communications with myeloid cells prevent T cell activation and recruitment and provide resistance to cell cycle inhibitor therapy 81 samples shares activation, suppress
- GSE270902 Twist1-induced suppression of oncogene-induced senescence in non-small cell lung cancer requires the transactivation domain of Twist1 12 samples shares activation, suppress
- GSE235244 Senescent cancer-associated fibroblasts in pancreatic adenocarcinoma suppress CD8+ T cell activation and inhibit response to immune checkpoint therapy [hPDAC] 8 samples shares activation, suppress
- GSE245249 CRISPR activation screens identify the SWI-SNF ATPases as suppressors of ferroptosis 65 samples shares activation, suppress
- GSE261322 NF-κB- and TET2-mediated macrophage reprogramming overrides the anti-inflammatory effects of hypoxia and improves responses in human cancer (RNA-Seq I). 20 samples shares tet2
- GSE326946 Transcriptomic profiling of AML cell lines MV4-11 and Kasumi-1 treated with CK1α degrader PinA1 12 samples shares mv4-11
- GSE230601 ZNF397 Deficiency Triggers TET2-driven Lineage Plasticity and AR-Targeted Therapy Resistance in Prostate Cancer [RNA-seq] 12 samples shares tet2
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.