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Transcriptional and immune repertoire profiling of mismatch repair-deficient colorectal cancer

GSE303444 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2026/04/23 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 30 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
30 samples
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.
Summary (written by the submitters)
Colorectal cancers (CRC) with deficient mismatch repair (dMMR) exhibit variable responses to immune checkpoint inhibitors, despite their immunogenic nature. To investigate the molecular basis of this heterogeneity, we performed integrated bulk RNA sequencing and immune repertoire profiling on tumor and adjacent normal mucosa from treatment-naïve dMMR CRC patients.
Read the full summary ↓
Using weighted gene co-expression network analysis, we identified transcriptional modules associated with T and B cell clonality, immune-metabolic interactions, and therapeutic responsiveness. Our dataset provides a valuable resource for understanding the tumor microenvironment in dMMR CRC and supports the development of biomarkers for patient stratification beyond mismatch repair status.
This dataset
Open GSE303444 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 GSE303444_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 PRJNA1295433 and SRA study SRP603036. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
A cohort of 30 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run crc_dmmr_tumor_s1 … crc_dmmr_tumor_s30 and carry no group information.

Samples in this study
More Colorectal cancer datasets

Search all human RNA-seq datasets in GEO →

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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.