GEO series

Single cell analysis highlights the significance of malignant cell IFN/MHC-II for immunotherapy response in head and neck squamous cell carcinoma

GSE301741 Homo sapiens (human) Single-cell RNA-seq 58 samples Submitted 2026/02/10 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 58 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Topic: Head and neck cancerThis series is part of our curated briefing on it.
Samples: 58 samples: 58 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: Single-cell analysis highlights the significance of malignant cell IFN/MHC-II for immunotherapy response in head and neck squamous cell carcinomaCell reports. Medicine · 2026

Summary (written by the submitters)

For many cancers, including head and neck squamous cell carcinoma (HNSCC), response rates to immunotherapy remain modest, with limited ability to predict responders. Previous studies that characterized cellular changes associated with immunotherapy in HNSCC focused on immune cells, providing limited insight into malignant cell responses.

Read the full summary ↓

Motivated by this gap, we performed single cell RNA-sequencing on 16 HNSCC patients pre- and post-neoadjuvant pembrolizumab treatment. We identified a malignant-interferon (IFN)/MHC-II program in malignant cells, characterized by expression of MHC-II and interferon response genes, which was associated with tumor response to pembrolizumab. We validated malignant cell MHC-II expression at the protein level and characterized its relationship with surrounding immune subsets via multiplexed immunofluorescence. In a murine HNSCC model, IFN-γ-induced malignant cell MHC-II expression marked tumors with favorable immune microenvironments and sensitivity to immunotherapy. Finally, we confirmed pre-treatment expression of the malignant-IFN/MHC-II program as marker of response through deconvolution of bulk RNA-seq data from an independent cohort of 25 pembrolizumab-treated HNSCC patients. Beyond identifying malignant cell MHC-II expression and the malignant-IFN/MHC-II program as potential biomarkers for immunotherapy response in HNSCC, our work provides additional insights into the specific and important role of malignant cells in immunotherapy.

Published in

Single-cell analysis highlights the significance of malignant cell IFN/MHC-II for immunotherapy response in head and neck squamous cell carcinoma

Mints M, Sample RA, Parikh AS et al. · Cell reports. Medicine 2026 · PMID 41923630 · doi:10.1016/j.xcrm.2026.102715

This dataset

Open GSE301741 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 GSE301741_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1283925 and SRA study SRP595878. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41923630) ↗

Study design

58 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 58 sample titles: 58 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

GSM9088456 OCSCC1, Post, CD45neg, 3prime
GSM9088457 OCSCC1, Post, CD45pos, 5prime
GSM9088458 OCSCC1, Post, CD45pos, TCR
GSM9088459 OCSCC1, Pre, CD45neg, 3prime
GSM9088460 OCSCC1, Pre, CD45pos, 5prime
GSM9088461 OCSCC1, Pre, CD45pos, TCR
GSM9088462 OCSCC3, Post, CD45neg, 3prime
GSM9088463 OCSCC3, Post, CD45ratio, 5prime
GSM9088464 OCSCC3, Post, CD45ratio, TCR
GSM9088465 OCSCC3, Pre, Unsorted, 5prime
GSM9088466 OCSCC3, Pre, Unsorted, TCR
GSM9088467 OCSCC12, Post, CD3, 5prime
GSM9088468 OCSCC12, Post, CD3, TCR
GSM9088469 OCSCC13, Post, CD45neg, 3prime
GSM9088470 OCSCC13, Post, CD45pos, 5prime
GSM9088471 OCSCC13, Post, CD45pos, TCR
GSM9088472 OCSCC13, Pre, CD45pos, 5prime
GSM9088473 OCSCC13, Pre, CD45pos, TCR
GSM9088474 OCSCC19, Post, CD3, 5prime
GSM9088475 OCSCC19, Post, CD3, TCR
GSM9088476 OPSCC41, Post, CD3, 5prime
GSM9088477 OPSCC41, Post, CD3, TCR
GSM9088478 OCSCC30, Post, CD3, 5prime
GSM9088479 OCSCC30, Post, CD3, TCR
GSM9088480 OCSCC33, Post, CD3, 5prime
GSM9088481 OCSCC33, Post, CD3, TCR
GSM9088482 OCSCC31, Post, CD3, 5prime
GSM9088483 OCSCC31, Post, CD3, TCR
GSM9088484 OCSCC31, Pre, CD3, 5prime
GSM9088485 OCSCC31, Pre, CD3, TCR
GSM9088486 OCSCC34, Post, CD3, 5prime
GSM9088487 OCSCC34, Post, CD3, TCR
GSM9088488 OCSCC34, Pre, CD3, 5prime
GSM9088489 OCSCC34, Pre, CD3, TCR
GSM9088490 OCSCC35, Post, CD3, 5prime
GSM9088491 OCSCC35, Post, CD3, TCR
GSM9088492 OCSCC35, Pre, CD3, 5prime
GSM9088493 OCSCC35, Pre, CD3, TCR
GSM9088494 LSCC20, Post, CD3, 3prime
GSM9088495 LSCC20, Post, CD3, 5prime

+ 18 more — browse all 58 samples with per-sample file links →

More Head and neck cancer datasets

GSE140042 Single-cell atlas of head and neck squamous cell carcinoma 18 samples same disease briefing · shares squamous, head
GSE185965 Single cell RNA sequencing of head and neck squamous carcinoma (HNSCC) patient sample 3 samples same disease briefing · shares squamous, head
GSE173647 Single-cell Sequencing Analysis of Head and Neck Squamous Cell Carcinoma 2 samples same disease briefing · shares squamous, head
GSE103322 Single cell RNA-seq analysis of head and neck cancer 5901 samples same disease briefing · shares head
GSE139324 Immune landscape of viral- and carcinogen-drived head and neck cancer 63 samples same disease briefing · shares head
GSE164690 Investigating Immune and Non-Immune Cell Interactions in Head and Neck Tumors by Single-Cell RNA Sequencing 51 samples same disease briefing · shares head
GSE181919 Single-cell transcriptome profiling of the stepwise progression of head and neck cancer 37 samples same disease briefing · shares head
GSE176077 RNA-seq profiling of salivary transcriptome reveals potential diagnostic RNAs and oral microbial dysbiosis in oral squamous cell carcinoma 28 samples same disease briefing · shares squamous

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.