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NSD2 is upregulated by high-risk HPV E6/E7 and modulates epithelial differentiation in HPV-associated Head and Neck Cancer

GSE313615 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2026/02/11 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 14 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
14 samples: 14 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
NSD2 upregulation is driven by high-risk HPV E6/E7 and disrupts epithelial differentiation in HPV-associated head and neck cancerJournal of experimental & clinical cancer research : CR · 2026
Summary (written by the submitters)
Epigenetic alterations are a key hallmark of cancer and are increasingly recognized as promising clinical biomarkers and therapeutic targets. In recent years Head and Neck Squamous Cell Carcinomas (HNSCC) have been classified into two subtypes: HPV-positive (HPV+), driven by human papillomavirus (HPV) infections, and the HPV-negative (HPV-), associated with environmental risk factors.
Read the full summary ↓
Although exhibiting distinct molecular and clinicopathological features, both subtypes lack effective, tailored therapies. Thus, profiling their epigenetic landscape could thus have important clinical implications. In this study, we employed a quantitative mass spectrometry approach to profile histone post-translational modification (hPTMs) in HPV+ and HPV- HNSCC. We found that the histone mark H3K36me2 is significantly enriched in the HPV+ subtype and that this alteration is driven by hr-HPV E6/E7 oncoproteins which also upregulate NSD2, a histone methyltransferase specific for H3K36 dimethylation. Both H3K36me2 and NSD2 are upregulated in several cancers. Given the NSD2’s context and cell-type-dependent functions, we investigated its role in HPV+ and HPV- HNSCC. We observed that NSD2 regulates cell proliferation and migration in both the subtypes. Importantly, we identified a novel role for NSD2 in regulating epithelial cell differentiation, particularly in HPV+ HNSCC, where it appears to modulate the E6/E7-induced differentiation blockade. Overall, our findings highlight H3K36me2 as a potential biomarker for patient stratification and position NSD2 as a promising therapeutic target across HNSCC subtypes, regulating both shared and subtype-specific oncogenic pathways. Specifically, NSD2 inhibition in HPV+ tumors may restore epithelial differentiation and arrest tumor progression.
Published in
NSD2 upregulation is driven by high-risk HPV E6/E7 and disrupts epithelial differentiation in HPV-associated head and neck cancer
Ghiani L, Citro S, Medda A et al. · Journal of experimental & clinical cancer research : CR 2026 · PMID 41507992 · doi:10.1186/s13046-025-03631-0
This dataset
Open GSE313615 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 GSE313615_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 PRJNA1380401 and SRA study SRP654816. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41507992) ↗
Study design
14 samples, each with a distinct title — no replicated groups

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

How we read this: Read from 14 sample titles: 14 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.

Samples in this study
More Head and neck cancer datasets

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