← BioTransfer GEO Dataset Finder
GEO series

Multi-omics analyses construct an inflammatory response based prognostic gene signature for cervical cancer and suggest tumor infiltrating monocytes subgroups as key players

GSE291865 Homo sapiens (human) Single-cell RNA-seq 23 samples Submitted 2025/05/15 Platform GPL29480
At a glance

Single-cell RNA-seq · human · 23 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Topic
Cervical cancerThis series is part of our curated briefing on it.
Samples
23 samples
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
Multi-omics analyses construct an inflammatory response based prognostic gene signature for cervical cancer and suggest tumor infiltrating monocytes subgroups as key playersFrontiers in immunology · 2025
Summary (written by the submitters)
A multi-gene model based on inflammatory response relevant genes was constructed for cervical cancer patients. The association of patients’ scores for the model and the characteristics of tumor microenvironment as well as patients’ predicted response to anti-cancer treatments was analyzed. Based on the single-cell RNA-sequencing (scRNA-seq) data, two tumor infiltrating monocytes (TIM) clusters were found to be associated with the inflammatory response in the tumor microenvironment.
Read the full summary ↓
The tumour tissues of 23 cervical adenocarcinoma patients in our hospital were collected and bulk RNA-sequencing was carried out. The correlation of marker genes of the two TIM clusters and patients’ score of the multi-gene model was analyzed to validate the findings on the scRNA-seq data.
Published in
Multi-omics analyses construct an inflammatory response based prognostic gene signature for cervical cancer and suggest tumor infiltrating monocytes subgroups as key players
Zhang Y, Zhu J, Hu K et al. · Frontiers in immunology 2025 · PMID 40458391 · doi:10.3389/fimmu.2025.1563593
This dataset
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.

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 GSE291865_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1235690 and SRA study SRP570261. Searching any of these in the dataset finder brings you back here.

Study design
A cohort of 23 individual samples

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

How we read this: Sample titles run patient1 … patient23 and carry no group information.

Samples in this study
More Cervical cancer datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.