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Analysis of gene expression profiles in matched cancer-associated and non-tumoral fibroblasts from patients with head and neck squamous cell carcinoma

GSE303690 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2026/06/22 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 36 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
Head and neck cancerThis series is part of our curated briefing on it.
Samples
36 samples: 12 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.
Summary (written by the submitters)
Among stromal components, cancer-associated fibroblasts (CAFs) constitute the predominant non-malignant population in the HNSCC microenvironment, where their abundance correlates with advanced disease and poor prognosis. CAFs support tumor progression via extracellular matrix remodeling and paracrine signaling through cytokines, growth factors, exosomes and miRNA.
Read the full summary ↓
Here, we carried out a transcriptomic analysis of 6 couples of CAFs and matching non-tumoral fibroblasts (NFs) derived from HNSCC patients in order to reveal gene expression changes between CAF and NF cell populations and identify potential CAF-specific therapeutic targets.
This dataset
Open GSE303690 in finder → Find more human RNA-seq datasets → Head and neck 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 GSE303690_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 PRJNA1297100 and SRA study SRP603678. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
CAF population from HT3 patient_biol ×3 CAF population from HT10 patient_biol ×3 CAF population from HT15B patient_biol ×3 CAF population from HT16 patient_biol ×3 CAF population from HT17A patient_biol ×3 CAF population from HT17B patient_biol ×3 NF population from HT3 patient_biol ×3 NF population from HT10 patient_biol ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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 Head and neck 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.