GEO series

Mannose enhances anti-PD-1 therapy efficacy in ovarian cancer via modulating gut microbial metabolite [Peritoneum]

GSE285965 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2025/03/17 Platform GPL34290

At a glance

RNA-seq (gene expression) · mouse · 24 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: Mus musculus (mouse)
Samples: 24 samples: 6 × Control vs 6 × Pro vs 6 × But vs 6 × CombineGroups 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.

Summary (written by the submitters)

The gut microbiome plays a critical role in enhancing the effectiveness of immune checkpoint blockade (ICB) therapy. Here, we demonstrate that oral supplementation with the prebiotics mannose slows tumor growth in immunocompetent mice in a manner dependent on the gut microbiota. This effect is associated with an increase in the abundance of Faecalibaculum.

Read the full summary ↓

Mannose generates an immune-stimulatory tumor microenvironment (TME), characterized by a higher percentage of effector and memory CD8+ T cells, along with a notable immunoreactive gene expression signature. Crucially, mannose modulates the stemness program of CD8+ T cells and promotes the generation of progenitor exhausted CD8+ T cells (Tpex). Mechanistically, mannose enhances the production of the short-chain fatty acids (SCFA) propionate and butyrate by the gut microbiota. Administration of propionate and butyrate suppresses tumor progression and stimulates the expansion and differentiation of Tpex both in vivo and in vitro. Furthermore, mannose works synergistically with PD-1 blockade, resulting in tumor regression and enhanced differentiation of intratumoral Tpex into intermediate exhausted CD8+ T cells (Tex-int) and terminally exhausted CD8+ T cells (Tex-term). We also identified a gene signature related to mannose therapy that correlates with favorable responses to ICB across various cancers. Overall, our findings support the combination of mannose dietary supplementation with anti-PD-1 immunotherapy in treating ovarian cancer and suggest its potential for clinical application.

This dataset

Open GSE285965 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 GSE285965_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 PRJNA1207068 and SRA study SRP555573. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 × Control vs 6 × Pro vs 6 × But vs 6 × Combine

Supports a between-group comparison across 24 samples.

How we read this: 4 replicated groups read from 24 sample titles; they account for 24 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

GSM8714057 Control 1 Control
GSM8714058 Control 2 Control
GSM8714059 Control 3 Control
GSM8714060 Control 4 Control
GSM8714061 Control 5 Control
GSM8714062 Control 6 Control
GSM8714063 Pro 1 Pro
GSM8714064 Pro 2 Pro
GSM8714065 Pro 3 Pro
GSM8714066 Pro 4 Pro
GSM8714067 Pro 5 Pro
GSM8714068 Pro 6 Pro
GSM8714069 But 1 But
GSM8714070 But 2 But
GSM8714071 But 3 But
GSM8714072 But 4 But
GSM8714073 But 5 But
GSM8714074 But 6 But
GSM8714075 Combine 1 Combine
GSM8714076 Combine 2 Combine
GSM8714077 Combine 3 Combine
GSM8714078 Combine 4 Combine
GSM8714079 Combine 5 Combine
GSM8714080 Combine 6 Combine

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GSE306720 The microbial tryptophan metabolite indole acts on the gastrointestinal tract to improve glucose homeostasis in a mouse model of diabetes by enhancing GLP-1 secretion and L cell differentiation 14 samples shares metabolite, microbial
GSE307919 Aromatic Microbial Metabolite Hippuric Acid Potentiates Pro-Inflammatory Responses in Macrophages through TLR-MyD88 Signaling and Lipid Remodeling 12 samples shares metabolite, microbial
GSE334585 iNOS is a key mediator of anti-PD-1 melanoma therapy response 48 samples shares anti-pd-1

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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.