Gene expression data of non-mucinous colorectal cancers to support to identify molecular characteristics of mucinous colorectal cancer
RNA-seq (gene expression) · human · 119 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
- 119 samples: 119 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 GSE281918_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 PRJNA1186177 and SRA study SRP545277. 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 119 sample titles: 119 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.
- GSM8632327 RSDR2054_RNA-seq
- GSM8632328 HRCRC3209_RNA-seq
- GSM8632329 HRCRC3371_RNA-seq
- GSM8632330 HRCRC3397_RNA-seq
- GSM8632331 HRCRC3403_RNA-seq
- GSM8632332 HRCRC3316_RNA-seq
- GSM8632333 HRCRC3390_RNA-seq
- GSM8632334 HRCRC3398_RNA-seq
- GSM8632335 HRCRC3404_RNA-seq
- GSM8632336 HRCRC3392_RNA-seq
- GSM8632337 HRCRC3393_RNA-seq
- GSM8632338 HRCRC3394_RNA-seq
- GSM8632339 HRCRC3427_RNA-seq
- GSM8632340 HRCRC3425 _RNA-seq
- GSM8632341 HRCRC3439_RNA-seq
- GSM8632342 HRCRC3447_RNA-seq
- GSM8632343 HRCRC3438_RNA-seq
- GSM8632344 HRCRC3446_RNA-seq
- GSM8632345 HRCRC3442_RNA-seq
- GSM8632346 HRCRC3441_RNA-seq
- GSM8632347 HRCRC3443_RNA-seq
- GSM8632348 HRCRC3311_RNA-seq
- GSM8632349 MTCRT538_RNA-seq
- GSM8632350 MTCRT520_RNA-seq
- GSM8632351 MTCRT521_RNA-seq
- GSM8632352 MTCRT524_RNA-seq
- GSM8632353 MTCRT527_RNA-seq
- GSM8632354 MTCRT530_RNA-seq
- GSM8632355 MTCRT531_RNA-seq
- GSM8632356 MTCRT529_RNA-seq
- GSM8632357 MTCRT532_RNA-seq
- GSM8632358 MTCRT535_RNA-seq
- GSM8632359 MTCRT534_RNA-seq
- GSM8632360 MTCRT536_RNA-seq
- GSM8632361 MTCRT533_RNA-seq
- GSM8632362 MTCRT539_RNA-seq
- GSM8632363 MTCRT540_RNA-seq
- GSM8632364 MTCRT547_RNA-seq
- GSM8632365 MTCRT543_RNA-seq
- GSM8632366 MTCRT544_RNA-seq
+ 79 more — browse all 119 samples with per-sample file links →
- GSE281917 Gene expression data to identify molecular characteristics of mucinous colorectal cancer 140 samples shares characteristics, colorectal, mucinous
- GSE312236 Comprehensive proteogenomic analysis identifies immune targets in microsatellite stable and unstable colorectal cancers 26 samples shares colorectal
- GSE265906 Epigenetic and oncogenic inhibitors cooperatively drive differentiation and kill KRAS-mutant colorectal cancers [LOVO_BCat] 24 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
- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares colorectal
- GSE225182 Gene expression profiling study to identify distinct subtypes in Peritoneal metastasis of colorectal cancer 33 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.