DFFB suppresses interferon to enable cancer persister cell regrowth
RNA-seq (gene expression) · human · 35 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
- 35 samples: 9 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.
- Paper
- Antigenic cancer persister cells survive direct T cell attackbioRxiv : the preprint server for biology · 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 GSE196018_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 PRJNA802916 and SRA study SRP357961. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 27 samples.
How we read this: 9 replicated groups read from 35 sample titles; they account for 27 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.
- GSM5857968 A375_WT_parental
- GSM5857969 A375_WT_persister
- GSM5857970 A375_DFFB_KO_parental
- GSM5857971 A375_DFFB_KO_persister
- GSM5857972 PC9_WT_parental
- GSM5857973 PC9_WT_persister
- GSM6721361 A375_WT_DTEPs
- GSM6721362 A375_DFFB_KO_DTEPs
- GSM8999139 A375 WT untreated rep1 A375 WT untreated
- GSM8999140 A375 WT untreated rep2 A375 WT untreated
- GSM8999141 A375 WT untreated rep3 A375 WT untreated
- GSM8999142 A375 WT persister rep1 A375 WT persister
- GSM8999143 A375 WT persister rep2 A375 WT persister
- GSM8999144 A375 WT persister rep3 A375 WT persister
- GSM8999145 A375 WT persister+AP1i rep1 A375 WT persister+AP1i
- GSM8999146 A375 WT persister+AP1i rep2 A375 WT persister+AP1i
- GSM8999147 A375 WT persister+AP1i rep3 A375 WT persister+AP1i
- GSM8999148 DFFB KO untreated rep1 DFFB KO untreated
- GSM8999149 DFFB KO untreated rep2 DFFB KO untreated
- GSM8999150 DFFB KO untreated rep3 DFFB KO untreated
- GSM8999151 DFFB KO persister rep1 DFFB KO persister
- GSM8999152 DFFB KO persister rep2 DFFB KO persister
- GSM8999153 DFFB KO persister rep3 DFFB KO persister
- GSM8999154 DFFB KO persister+AP1i rep1 DFFB KO persister+AP1i
- GSM8999155 DFFB KO persister+AP1i rep2 DFFB KO persister+AP1i
- GSM8999156 DFFB KO persister+AP1i rep3 DFFB KO persister+AP1i
- GSM8999157 ATF3 KO untreated rep1 ATF3 KO untreated
- GSM8999158 ATF3 KO untreated rep2 ATF3 KO untreated
- GSM8999159 ATF3 KO untreated rep3 ATF3 KO untreated
- GSM8999160 ATF3 KO persister rep1 ATF3 KO persister
- GSM8999161 ATF3 KO persister rep2 ATF3 KO persister
- GSM8999162 ATF3 KO persister rep3 ATF3 KO persister
- GSM8999163 ATF3 KO persister+AP1i rep1 ATF3 KO persister+AP1i
- GSM8999164 ATF3 KO persister+AP1i rep2 ATF3 KO persister+AP1i
- GSM8999165 ATF3 KO persister+AP1i rep3 ATF3 KO persister+AP1i
- GSE299562 PHIP suppresses NuRD to enable the growth of SWI/SNF-mutant cancers [RNA-seq] 42 samples shares suppresses, enable
- GSE315219 PHIP suppresses NuRD to enable the growth of SWI/SNF-mutant cancers 174 samples shares suppresses, enable
- GSE299672 PHIP suppresses NuRD to enable the growth of SWI/SNF-mutant cancers [ChIP-seq] 132 samples shares suppresses, enable
- GSE263931 Selective CAR-T cell mediated B cell depletion suppresses interferon signature in SLE [PBMC] 28 samples shares suppresses, interferon
- GSE263932 Selective CAR-T cell mediated B cell depletion suppresses interferon signature in SLE [Bcells] 20 samples shares suppresses, interferon
- GSE292601 Epithelial interferon-stimulated gene programs modulate chemotherapy sensitivity in colorectal cancer via EPSTI1 62 samples shares interferon
- GSE308782 Telomerase Dysfunction Strategy Overcomes Targeted Therapy Induced Drug Tolerant Persister in Pan-cancer via SUCLG2 downregulation 36 samples shares persister
- GSE325770 Concurrent CDK7 and CDK9 Blockade Sustains Transcriptional Shutdown and Suppresses Oncogenic Dependencies in Cancer 33 samples shares suppresses
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.