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Gene expression profile of 31 RAS/RAF-wild-type colorectal cancer (CRC) stem-cell (SC) spheroids and 7 FGFR-inhibitor resistant CSC-SC spheroids

GSE333925 Homo sapiens (human) RNA-seq (gene expression) 38 samples Submitted 2026/06/09 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 38 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
38 samples: 38 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
Involvement of tyrosine phosphatase PTPROt in acquired resistance to FGFR inhibitor therapy in colorectal cancerMolecular cancer therapeutics · 2026
Summary (written by the submitters)
This study investigated mechanisms of acquired resistance to FGFR inhibitor therapy in RAS/RAF–wild-type colorectal cancer (CRC). RNA sequencing (RNA-seq) data from 47 RAS/RAF-wild-type colorectal cancer stem-cell (CRC-SC) spheroid lines previously deposited under GSE205787 were integrated with newly generated RNA-seq data from 31 additional RAS/RAF-wild-type CRC-SC spheroid lines and seven FGFR inhibitor-resistant CRC-SC derivatives.
Read the full summary ↓
The resistant derivatives were established from parental CRC-SC spheroid lines by continuous exposure to erdafitinib or futibatinib. Comparative transcriptomic analysis between matched parental and resistant lines revealed consistent upregulation of EGFR and downregulation of PTPROt, a truncated isoform of PTPRO, in resistant derivatives. Gene set enrichment analysis further indicated activation of EGFR-related signaling pathways in FGFR inhibitor-resistant spheroids. In addition, the integrated RNA-seq dataset comprising 78 RAS/RAF-wild-type CRC-SC lines was used to validate the inverse correlation between EGFR and PTPRO mRNA expression, supporting the involvement of PTPROt downregulation and EGFR pathway activation in acquired resistance to FGFR inhibition.
Published in
Involvement of tyrosine phosphatase PTPROt in acquired resistance to FGFR inhibitor therapy in colorectal cancer
Kitano S, Miyoshi H, Yamamoto T et al. · Molecular cancer therapeutics 2026 · PMID 42295205 · doi:10.1158/1535-7163.MCT-25-1268
This dataset
Open GSE333925 in finder → Find more human RNA-seq datasets → Colorectal cancer landscape →
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.

Series matrix ↓
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 GSE333925_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1473232 and SRA study SRP705766. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42295205) ↗
Study design
38 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 38 sample titles: 38 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
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.