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Acidovorax temperans polarizes T17 cells and skews neutrophil maturation to promote lung adenocarcinoma development

GSE259408 Mus musculus (mouse) RNA-seq (gene expression) 45 samples Submitted 2024/04/05 Platform GPL23479
At a glance

RNA-seq (gene expression) · mouse · 45 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
45 samples: 45 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
Acidovorax temperans skews neutrophil maturation and polarizes Th17 cells to promote lung adenocarcinoma developmentOncogenesis · 2024
Summary (written by the submitters)
Dysbiosis, or changes within the microbiome, is a common feature of solid tumors, however whether this dysbiosis directly contributes to tumor development is largely unknown. We previously characterized the human lung cancer microbiome and identified the Gram-negative Acidovorax temperans as enriched in tumors and associated with smoking status and TP53 mutations.
Read the full summary ↓
To determine if A. temperans exposure could contribute to the development of lung cancer, we investigated its effect in a genetically engineered mouse model of lung adenocarcinoma driven by mutant Kras and Tp53. In comparison to control mice and those instilled with a commensal species Lactobacillus gasseri, we found that repeated A. temperans exposure accelerates tumor development and burden through infiltration of proinflammatory cells in the lungs. Comparing immune cell infiltrates at two timepoints revealed increased proinflammatory cells immediately following A. temperans instillation while later the number of T cells, especially IL-17+ cells, was increased. These data indicate a clear role for microbiota-induced inflammation as a key mechanism in the development of lung cancer, demonstrating that dysbiosis contributes to tumor growth.
Published in
Acidovorax temperans skews neutrophil maturation and polarizes Th17 cells to promote lung adenocarcinoma development
Stone JK, von Muhlinen N, Zhang C et al. · Oncogenesis 2024 · PMID 38570533 · doi:10.1038/s41389-024-00513-6
This dataset
Open GSE259408 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 GSE259408_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 PRJNA1081431 and SRA study SRP492142. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38570533) ↗
Study design
45 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 45 sample titles: 45 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

+ 5 more — browse all 45 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.