Role of EPIC1 in cancer cells
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 17 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)
- Samples
- 17 samples: 17 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
- The lncRNA EPIC1 suppresses dsRNA-induced type I IFN signaling and is a therapeutic target to enhance TNBC response to PD-1 inhibitionScience signaling · 2025
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 GSE229724_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA955700 and SRA study SRP432672. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 3 samples read as cases, 3 as controls.
How we read this: Read from 17 sample titles: 17 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.
- GSM7174011 ChIP-Seq of H3K27me3, Control, Input
- GSM7174012 ChIP-Seq of H3K27me3, Control, IP
- GSM7174013 ChIP-Seq of H3K27me3, EPIC1 overexpression, Input
- GSM7174014 ChIP-Seq of H3K27me3, EPIC1 overexpression, IP
- GSM7174015 RNAseq of control MCF7
- GSM7174016 RNAseq of EPIC1 overexpressed MCF7
- GSM7174017 A2780_siLuc
- GSM7174018 A2780cis_siLuc
- GSM7174019 Hs578T_siLuc
- GSM7174020 A2780_siEPIC1_1#
- GSM7174021 A2780cis_siEPIC1_1#
- GSM7174022 Hs578T_siEPIC1_1#
- GSM7174023 A2780_siEPIC1_2#
- GSM7174024 A2780cis_siEPIC1_2#
- GSM7174025 Hs578T_siEPIC1_2#
- GSM7174026 GEX_CKDL220031167-1A
- GSM7174027 Feature_Barcode_CKDL220031167-1A
- GSE229722 Transcriptomic changes induced by knocking down EPIC1 in cancer cell lines [RNA-seq II] 9 samples shares epic1
- GSE216922 ChIP-Seq of MYC in MCF-7 cells with EPIC1 knockdown or overexpression. 10 samples shares epic1
- GSE229720 ChIP-Seq of H3K27me3 in MCF-7 cells overexpressing EPIC1 4 samples shares epic1
- GSE229721 Effect of overexpression of EPIC1 on gene expression in MCF7 cells [RNA-seq I] 2 samples shares epic1
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.