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[18F]FDG PET/CT multiomics identifies Hedgehog-driven HPV-negative head and neck squamous cell carcinoma

GSE316548 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2026/02/09 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.
Paper
[(18)F]FDG PET/CT multiomics identifies Hedgehog-driven HPV-negative head and neck squamous cell carcinomaMolecular cancer · 2026
Summary (written by the submitters)
Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous malignancy with limited predictive markers to guide personalized treatment, particularly in human papillomavirus (HPV)-negative cases, which exhibit poor outcomes. Identifying reliable biomarkers for prognosis and therapeutic response remains a critical challenge.
Read the full summary ↓
In a retrospective cohort of 51 patients with primary HPV-negative HNSCC, we investigated the prognostic significance of the Hedgehog (HH) signaling pathway and its association with imaging biomarkers. Genomic and transcriptomic analysis revealed that HH pathway activation correlated with distinct [18F]FDG PET/CT radiomic features, notably the PET-derived “histogram:ih.max” - a surrogate for peak [18F]FDG uptake and was associated with inferior survival outcomes. Functionally, pharmacologic inhibition of HH signaling demonstrated anticancer efficacy across multiple models, including HNSCC cell lines, patient-derived tumoroids, and in vivo xenograft models. Importantly, HH inhibition altered imaging characteristics in HNSCC xenografts, leading to a measurable reduction in [18F]FDG uptake. This imaging phenotype closely mirrored our clinical findings, suggesting that [18F]FDG PET/CT radiomics may serve as a non-invasive biomarker to identify and monitor HH-driven HNSCC tumors. The integration of multi-level molecular profiling and functional imaging supports a potential precision oncology strategy, in which HH inhibition may offer a viable therapeutic approach for HPV-negative HNSCC. Our study underscores the value of [18F]FDG PET/CT multiomics in linking tumor biology with imaging features, paving the way for improved patient stratification and treatment monitoring. These findings provide a compelling rationale for further investigation into HH-targeted therapies in this aggressive subset of HNSCC and their clinical implications.
Published in
[(18)F]FDG PET/CT multiomics identifies Hedgehog-driven HPV-negative head and neck squamous cell carcinoma
Stoiber S, Pölöske D, Spielvogel CP et al. · Molecular cancer 2026 · PMID 41904511 · doi:10.1186/s12943-026-02607-8
This dataset
Open GSE316548 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 GSE316548_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 PRJNA1403297 and SRA study SRP662671. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41904511) ↗
Study design
12 conditions, mostly in triplicate
CAL27 cells, Control, 6h, ×3 CAL27 cells, JK184 0.2 μM, 6h, ×3 SCC25 cells, Control, 6h, ×3 SCC25 cells, JK184 0.02 μM, 6h, ×3 CAL27 cells, Control, 12h, ×3 CAL27 cells, JK184 0.2 μM, 12h, ×3 SCC25 cells, Control, 12h, ×3 SCC25 cells, JK184 0.02 μM, 12h, ×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

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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.