GEO series

Single cell transcriptomics of several organs in K14HPV16/H2b and FVBN/H2b mice.

GSE241988 Mus musculus (mouse) Single-cell RNA-seq 30 samples Submitted 2025/04/03 Platform GPL21103

At a glance

Single-cell RNA-seq · mouse · 30 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 30 samples: 30 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: HPV16-Expressing Tumors Release Multiple IL1 Ligands to Orchestrate Systemic Immunosuppression Whose Disruption Enables Efficacy of a Therapeutic VaccineCancer discovery · 2025

Summary (written by the submitters)

It is well established that symptomatic cancers evade immune destruction by coalescing lesional and tumor microenvironments to suppress adaptive immunity. Additionally, mouse models of cervical and other cancers have revealed a capability of tumors to systemically induce the expansion of myeloid cells that cripple T cell development in spleen and lymph nodes, further impairing immune responses.

Read the full summary ↓

We show that HPV16-driven cervical cancers release into the circulatory system four immunoregulatory ligands – IL1α, IL1ß, IL33, and IL36ß – that bias the bone marrow toward granulocytic myelopoiesis, producing immunosuppressive neutrophils and myeloid progenitors differentially populating spleens and tumors to facilitate immune evasion. A pan-IL1 receptor antagonist, anti-IL1RAP, attenuates this myeloid expansion and complements an HPV-E7 peptide vaccine plus anti-CTLA4 to elicit anti-tumor immunity. Evidence for similar systemic activity of these four IL1 ligands in human cervical and other cancers encourages multi-targeting this signaling axis to broaden the scope of cancer immunotherapy.

Published in

HPV16-Expressing Tumors Release Multiple IL1 Ligands to Orchestrate Systemic Immunosuppression Whose Disruption Enables Efficacy of a Therapeutic Vaccine

Lecointre M, Guillot J, Marcone R et al. · Cancer discovery 2025 · PMID 40287949 · doi:10.1158/2159-8290.CD-25-0382

This dataset

Open GSE241988 in finder → Find more mouse RNA-seq datasets →

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 GSE241988_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 PRJNA1010861 and SRA study SRP457640. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40287949) ↗

Study design

30 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 30 sample titles: 30 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

GSM7747193 HPV-mice, Replicate 1, Cervix
GSM7747194 HPV-mice, Replicate 2, Cervix
GSM7747195 HPV-mice, Replicate 3, Cervix
GSM7747196 H2B-mice, Replicate 1, Cervix
GSM7747197 H2B-mice, Replicate 2, Cervix
GSM7747198 H2B-mice, Replicate 3, Cervix
GSM7747199 HPV-mice, Replicate 1, Spleen
GSM7747200 HPV-mice, Replicate 2, Spleen
GSM7747201 HPV-mice, Replicate 3, Spleen
GSM7747202 H2B-mice, Replicate 1, Spleen
GSM7747203 H2B-mice, Replicate 2, Spleen
GSM7747204 H2B-mice, Replicate 3, Spleen
GSM7747205 HPV-mice, Replicate 1, Bone Marrow
GSM7747206 HPV-mice, Replicate 2, Bone Marrow
GSM7747207 HPV-mice, Replicate 3, Bone Marrow
GSM7747208 H2B-mice, Replicate 1, Bone Marrow
GSM7747209 H2B-mice, Replicate 2, Bone Marrow
GSM7747210 H2B-mice, Replicate 3, Bone Marrow
GSM7747211 HPV-mice, Replicate 1, Ear
GSM7747212 HPV-mice, Replicate 2, Ear
GSM7747213 HPV-mice, Replicate 3, Ear
GSM7747214 H2B-mice, Replicate 1, Ear
GSM7747215 H2B-mice, Replicate 2, Ear
GSM7747216 H2B-mice, Replicate 3, Ear
GSM7747217 HPV-mice, Replicate 1, Blood
GSM7747218 HPV-mice, Replicate 2, Blood
GSM7747219 HPV-mice, Replicate 3, Blood
GSM7747220 H2B-mice, Replicate 1, Blood
GSM7747221 H2B-mice, Replicate 2, Blood
GSM7747222 H2B-mice, Replicate 3, Blood

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