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Evaluation of cetuximab-induced gene expression changes in residual PDX tumors of head and neck squamous cell carcinoma

GSE303798 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/06/22 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × Cetuximab-treated residual HNC004 PDX_biol vs 3 × Vehicle-treated residual HNC004 PDX_biol vs 3 × Vehicle-treated residual UCLHN04 PDX_biol vs 3 × Cetuximab-treated residual UCLHN04 PDX_biolGroups 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)
Cetuximab, a monoclonal antibody targeting EGFR, offers only modest and often transient clinical responses in recurrent or metastatic HNSCC, owing to the persistence of a therapy-tolerant cell population that seeds residual disease and eventual therapeutic failure. Clinical evidence across cancer types indicates that depth of response to targeted therapy correlates with prolonged progression-free survival, highlighting the importance of residual disease as a driver of resistance.
Read the full summary ↓
However, the molecular features enabling HNSCC cells to tolerate EGFR blockade before the acquisition of stable resistance remain incompletely understood. We analyzed residual tumors from cetuximab-treated patient-derived xenograft (PDX) models of HNSCC (#UCLHN04 and #HNC004) to identify gene expression changes associated with anti-EGFR tolerance in HNSCC cells.
This dataset
Open GSE303798 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 GSE303798_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 PRJNA1297702 and SRA study SRP604008. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × Cetuximab-treated residual HNC004 PDX_biol vs 3 × Vehicle-treated residual HNC004 PDX_biol vs 3 × Vehicle-treated residual UCLHN04 PDX_biol vs 3 × Cetuximab-treated residual UCLHN04 PDX_biol

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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.