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Effect of FTO deletion on gene expression of HT29 and HCT116 in colon cancer cell lines

GSE278117 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/06/16 Platform GPL24676
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)
Topic
Colorectal cancerThis series is part of our curated briefing on it.
Samples
12 samples: 3 × HT29 cell,WT, vs 3 × HT29 cell,FTOKO, vs 3 × HCT116 cell,WT, vs 3 × HCT116 cell,FTOKO,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
FTO facilitates colorectal cancer chemoresistance via regulation of NUPR1-dependent iron homeostasisRedox biology · 2025
Summary (written by the submitters)
Colorectal cancer stands as one of the four most lethal malignancies globally, ranking second among women and third among men in terms of prevalence. The m6A RNA methylation process, mediated by various m6A regulatory genes, has been implicated in promoting the development and progression of tumors. However, the understanding of its involvement in colorectal cancer remains limited. Therefore, RNA sequencing (RNA-seq) was performed in HT29 and HCT116 cells following FTO knockout, as it functions as an oncogene and is one of the m6A erasers.
Published in
FTO facilitates colorectal cancer chemoresistance via regulation of NUPR1-dependent iron homeostasis
Xu C, Shen T, Feng L et al. · Redox biology 2025 · PMID 40334546 · doi:10.1016/j.redox.2025.103647
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 GSE278117_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 PRJNA1187843. Searching any of these in the dataset finder brings you back here.

Study design
3 × HT29 cell,WT, vs 3 × HT29 cell,FTOKO, vs 3 × HCT116 cell,WT, vs 3 × HCT116 cell,FTOKO,

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.

Samples in this study
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