Gene expression data to identify molecular characteristics of mucinous colorectal cancer
RNA-seq (gene expression) · human · 140 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
- 140 samples: 140 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
- Prognostic and therapeutic value of a 23-gene risk score tailored to the molecular characteristics of mucinous colorectal cancerBritish journal of cancer · 2025
Read the full summary ↓
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 GSE281917_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: 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 PRJNA1186176 and SRA study SRP545276. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 140 sample titles: 140 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.
- GSM8632187 HRCRC3109_RNA-seq
- GSM8632188 HRCRC3290_RNA-seq
- GSM8632189 HRCRC3314_RNA-seq
- GSM8632190 HRCRC3375_RNA-seq
- GSM8632191 HRCRC3410_RNA-seq
- GSM8632192 HRCRC3453_RNA-seq
- GSM8632193 HRCRC3462_RNA-seq
- GSM8632194 HRCRC3663_RNA-seq
- GSM8632195 HRCRC3714_RNA-seq
- GSM8632196 HRCRC3717_RNA-seq
- GSM8632197 HRCRC3725_RNA-seq
- GSM8632198 HRCRC3735_RNA-seq
- GSM8632199 HRCRC3792_RNA-seq
- GSM8632200 HRCRC3805_RNA-seq
- GSM8632201 HRCRC3873_RNA-seq
- GSM8632202 HRCRC3917_RNA-seq
- GSM8632203 HRCRC3928_RNA-seq
- GSM8632204 HRCRC3938_RNA-seq
- GSM8632205 HRCRC3963_RNA-seq
- GSM8632206 HRCRC3977_RNA-seq
- GSM8632207 MTCRT537_RNA-seq
- GSM8632208 mucCRC001_RNA-seq
- GSM8632209 mucCRC002_RNA-seq
- GSM8632210 mucCRC003_RNA-seq
- GSM8632211 mucCRC004_RNA-seq
- GSM8632212 mucCRC005_RNA-seq
- GSM8632213 mucCRC006_RNA-seq
- GSM8632214 mucCRC007_RNA-seq
- GSM8632215 mucCRC008_RNA-seq
- GSM8632216 mucCRC009_RNA-seq
- GSM8632217 mucCRC010_RNA-seq
- GSM8632218 mucCRC011_RNA-seq
- GSM8632219 mucCRC012_RNA-seq
- GSM8632220 mucCRC013_RNA-seq
- GSM8632221 mucCRC014_RNA-seq
- GSM8632222 mucCRC015_RNA-seq
- GSM8632223 mucCRC016_RNA-seq
- GSM8632224 mucCRC017_RNA-seq
- GSM8632225 mucCRC018_RNA-seq
- GSM8632226 mucCRC019_RNA-seq
+ 100 more — browse all 140 samples with per-sample file links →
- GSE250000 Bulk RNA-sequencing of transduced colorectal cancer cell line HCT-116 and breast cancer cell line MCF-7 overexpressing full-lenght p53β or p53β-stop-lost. 4 samples same disease briefing · shares colorectal
- GSE12032 Inherent gene signature of stage II and III colorectal cancer leads in individual recurrence 198 samples same disease briefing · shares colorectal
- GSE110009 Single cell transcriptome landscape of primary and metastatic tumor in colon cancer 76 samples same disease briefing
- GSE109308 Single-cell transcriptomic survey of adenomatous polyposis patients with germline APC mutations 97 samples same disease briefing
- GSE225182 Gene expression profiling study to identify distinct subtypes in Peritoneal metastasis of colorectal cancer 33 samples shares colorectal
- GSE319878 Interrogating the mechanistic link between neighborhood deprivation and colorectal cancer risk through gene expression analysis of normal colorectal biopsies 171 samples shares colorectal
- GSE330465 Gene expression profiling of neoadjuvant ABFOLFOX treatment in patients with unresectable colorectal cancer with liver metastases 104 samples shares colorectal
- GSE333925 Gene expression profile of 31 RAS/RAF-wild-type colorectal cancer (CRC) stem-cell (SC) spheroids and 7 FGFR-inhibitor resistant CSC-SC spheroids 38 samples shares colorectal
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.