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Idelalisib and pneumococcal infection induce distinct transcriptional responses in mouse precision-cut lung slices

GSE181259 Mus musculus (mouse) RNA-seq (gene expression) 40 samples Submitted 2025/12/20 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 40 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
40 samples: 8 conditions, mostly with about 5 replicates eachGroups 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)
Idelalisib has excellent activity in management of chronic lymphocytic leukemia and follicular lymphoma while inducing serious microbial pneumonia in the clinic. To understand the mechanisms of Idelalisib-induced infection risk, we performed RNAseq analyses on mouse precision-cut lung slices treated with Idelalisib in the absence and presence of human lung pathogen Streptococcus pneumoniae.
Read the full summary ↓
RNAseq transcriptome profiling identifies distinct response signatures in mouse lung slices in responses to Idelalisib treatment and pneumococcal infection. The expression of genes vital for regulation of transcription, immunity and inflammation, cell proliferation and apoptosis, kinase signaling, metabolism, and extracellular matrix remodeling is significantly modulated by Idelalisib. This study provides a new insight for predicting the immunomodulatory impact of drug candidates on host defense and thereby improving the safety profiling of novel drugs for human respiratory diseases.
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 GSE181259_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: 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 PRJNA751233 and SRA study SRP330713. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly with about 5 replicates each
0_1uM_IDELA ×5 0_1uM_IDELA_Spn ×5 1_0_uM_IDELA ×5 1_0_uM_IDELA_Spn ×5 10_uM_IDELA ×5 10_uM_IDELA_Spn ×5 Veh ×5 Veh_Spn ×5

Supports a between-group comparison across 40 samples.

How we read this: 8 replicated groups read from 40 sample titles; they account for 40 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
Datasets on a similar topic

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