Mutant IDH1 inhibition induces dsDNA sensing to activate tumor immunity [human_cgas_AZT_rnaseq]
RNA-seq (gene expression) · human · 36 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
- 36 samples: 12 conditions, mostly in triplicateGroups 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.
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 GSE265804_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 PRJNA1104232 and SRA study SRP503843. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 36 samples.
How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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.
- GSM8229434 RNA-seq, SNU1079 in vitro, sgCtrl, DMSO, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229435 RNA-seq, SNU1079 in vitro, sgCtrl, DMSO, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229436 RNA-seq, SNU1079 in vitro, sgCtrl, DMSO, Replicate 3 RNA-seq, SNU1079 in vit…
- GSM8229437 RNA-seq, SNU1079 in vitro, sgCtrl, IFNg, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229438 RNA-seq, SNU1079 in vitro, sgCtrl, IFNg, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229439 RNA-seq, SNU1079 in vitro, sgCtrl, IFNg, Replicate 3 RNA-seq, SNU1079 in vit…
- GSM8229440 RNA-seq, SNU1079 in vitro, sgCtrl, AG120, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229441 RNA-seq, SNU1079 in vitro, sgCtrl, AG120, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229442 RNA-seq, SNU1079 in vitro, sgCtrl, AG120, Replicate 3 RNA-seq, SNU1079 in vit…
- GSM8229443 RNA-seq, SNU1079 in vitro, sgCtrl, AG120+IFNg, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229444 RNA-seq, SNU1079 in vitro, sgCtrl, AG120+IFNg, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229445 RNA-seq, SNU1079 in vitro, sgCtrl, AG120+IFNg, Replicate 3 RNA-seq, SNU1079 in vit…
- GSM8229446 RNA-seq, SNU1079 in vitro, sgCGAS, DMSO, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229447 RNA-seq, SNU1079 in vitro, sgCGAS, DMSO, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229448 RNA-seq, SNU1079 in vitro, sgCGAS, DMSO, Replicate 3 RNA-seq, SNU1079 in vit…
- GSM8229449 RNA-seq, SNU1079 in vitro, sgCGAS, IFNg, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229450 RNA-seq, SNU1079 in vitro, sgCGAS, IFNg, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229451 RNA-seq, SNU1079 in vitro, sgCGAS, IFNg, Replicate 3 RNA-seq, SNU1079 in vit…
- GSM8229452 RNA-seq, SNU1079 in vitro, sgCGAS, AG120, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229453 RNA-seq, SNU1079 in vitro, sgCGAS, AG120, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229454 RNA-seq, SNU1079 in vitro, sgCGAS, AG120, Replicate 3 RNA-seq, SNU1079 in vit…
- GSM8229455 RNA-seq, SNU1079 in vitro, sgCGAS, AG120+IFNg, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229456 RNA-seq, SNU1079 in vitro, sgCGAS, AG120+IFNg, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229457 RNA-seq, SNU1079 in vitro, sgCGAS, AG120+IFNg, Replicate 3 RNA-seq, SNU1079 in vit…
- GSM8229458 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+DMSO, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229459 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+DMSO, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229460 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+DMSO, Replicate 3 RNA-seq, SNU1079 in vit…
- GSM8229461 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+IFNg, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229462 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+IFNg, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229463 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+IFNg, Replicate 3 RNA-seq, SNU1079 in vit…
- GSM8229464 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+AG120, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229465 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+AG120, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229466 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+AG120, Replicate 3 RNA-seq, SNU1079 in vit…
- GSM8229467 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+AG120+IFNg, Replicate 1 RNA-seq, SNU1079 in vit…
- GSM8229468 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+AG120+IFNg, Replicate 2 RNA-seq, SNU1079 in vit…
- GSM8229469 RNA-seq, SNU1079 in vitro, sgCtrl, AZT+AG120+IFNg, Replicate 3 RNA-seq, SNU1079 in vit…
- GSE313114 Inhibition of METTL3 by STC-15 induces RNA misprocessing that results in dsRNA formation and activates innate immunity [RNA-Seq dose_response] 21 samples shares inhibition, activate, immunity, induces
- GSE281506 Combining Menin and MEK inhibition to target poor prognosis KMT2A-rearranged RAS pathway-mutant acute myeloid leukemia 42 samples shares inhibition, mutant
- GSE295260 CDK4/6 inhibition induces a senescence-associated secretory phenotype via delayed NF-κB activation 40 samples shares inhibition, induces
- GSE303051 Prolonged KRAS-MAPK Inhibition Induces Interferon-mediated Epithelial-to-Mesenchymal Transition and Reveals Therapeutic Opportunities. 30 samples shares inhibition, induces
- GSE303446 Beyond CD30 Targeting: Brentuximab Vedotin Triggers Immunogenic Cell Death and Antitumor Immunity in Mycosis Fungoides, Overcoming Resistance via BCL2 Inhibition 13 samples shares inhibition, immunity
- GSE280564 Reprogramming of normal fibroblasts into ovarian cancer-associated fibroblasts via non-vesicular paracrine signaling induces an activated fibroblast phenotype 12 samples shares activate, induces
- GSE280280 Reprogramming of Cellular Plasticity via ETS and MYC Core-regulatory circuits During Response to MAPK Inhibition in BRAF-mutant colorectal cancer 36 samples shares inhibition, mutant
- GSE303106 Prolonged KRAS-MAPK Inhibition Induces Interferon-mediated Epithelial-to-Mesenchymal Transition and Reveals Therapeutic Opportunities [cut and run-ChipSeq] 9 samples shares inhibition, induces
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.