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Analysis of the mechanism of acquisition of chemotherapy resistance in colorectal cancer cell lines

GSE289766 Homo sapiens (human) RNA-seq (gene expression) 27 samples Submitted 2026/04/09 Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 27 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
27 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
GDF15 promotes 5-Fluorouracil and Oxaliplatin resistance by promoting stem cell-like phenotype in colorectal cancerBritish journal of cancer · 2026
Summary (written by the submitters)
Although anticancer drugs such as fluorouracil and oxaliplatin are widely used in the treatment of colorectal cancer, they are ineffective when cancer cells acquire drug resistance. The treatment strategy for colorectal cancer that has acquired drug resistance has become a problem in chemotherapy. To investigate the cause of drug resistance, we created drug-resistant strains of colon cancer cell lines by mixing a small amount of anticancer drug in the culture medium and culturing them for a long period of time, and explored the genetic changes by RNA-sequence.
Published in
GDF15 promotes 5-Fluorouracil and Oxaliplatin resistance by promoting stem cell-like phenotype in colorectal cancer
Hashimoto M, Urabe S, Hata T et al. · British journal of cancer 2026 · PMID 42120524 · doi:10.1038/s41416-026-03379-0
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 GSE289766_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 PRJNA1224754 and SRA study SRP564354. Searching any of these in the dataset finder brings you back here.

Study design
9 conditions, mostly in triplicate
HCT116_WT ×3 HCT116_5FU ×3 HCT116_OX ×3 SW480_WT ×3 SW480_5FU ×3 SW480_OX ×3 DLD1_WT ×3 DLD1_5FU ×3 +1 more

Supports a between-group comparison across 27 samples.

How we read this: 9 replicated groups read from 27 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.

Samples in this study
More Colorectal cancer datasets

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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.