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Transcriptomic changes in HT29 cells and a patient-derived CRC 3D model after CRISPRi-based KAT2A knockdown

GSE268709 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/03/28 Platform GPL21697
At a glance

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: 12 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 histone modifier KAT2A presents a selective target in a subset of well-differentiated microsatellite-stable colorectal cancersCell death and differentiation · 2025
Summary (written by the submitters)
We were interested in transcriptional changes after depletion of histone acetyltransferase KAT2A in human colorectal cancer. Therefore, we utilized HT29 cells and a patient-derived CRC 3D spheroid line (CRC3) as model, and analyzed global alterations of gene expression.
Published in
The histone modifier KAT2A presents a selective target in a subset of well-differentiated microsatellite-stable colorectal cancers
Kufrin V, Seiler A, Brilloff S et al. · Cell death and differentiation 2025 · PMID 40140561 · doi:10.1038/s41418-025-01479-7
This dataset
Download · which file do I need?

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.

1 · Just have a look

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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE268709_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

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 PRJNA1118305 and SRA study SRP510868. Searching any of these in the dataset finder brings you back here.

Study design
12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 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.

Samples in this study
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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.