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cFLIP suppresses Caspase-1- and MLKL-independent perinatal lethality driven by autoprocessing impaired caspase-8 D387A

GSE299620 Mus musculus (mouse) RNA-seq (gene expression) 36 samples Submitted 2025/11/10 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 36 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
36 samples: 11 conditions, mostly in triplicateGroups 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)
Death ligands, including FAS ligand (FASL) and tumor necrosis factor (TNF), trigger apoptosis by promoting caspase-8 dimerization and activation. Impaired FAS signaling causes unconventional lymphocytes to accumulate, resulting in lymphadenopathy. Although autoprocessing of caspase-8 is considered important for apoptosis, autoprocessing-deficient Casp8 D387A/D387A mice do not develop lymphadenopathy.
Read the full summary ↓
We show that this is because heterodimers of caspase-8 D387A and cFLIP, besides suppressing MLKL-driven necroptosis, can also induce apoptosis. Interestingly, caspase-8 D387A elicited MLKL- and caspase-1-independent intestinal atrophy and perinatal lethality in mice lacking cFLIP. Caspase-8 D387A interacted with FADD and RIPK1 in the intestine, where there was aberrant cleavage of N4BP1 and caspase-3, plus enhanced NF-κB signaling. Eliminating FADD, the adaptor protein that promotes caspase-8 oligomerization, prevented this perinatal lethality. Collectively, our results suggest that cFLIP forms heterodimers with caspase-8 D387A to promote apoptosis in some contexts, while limiting the activity of caspase-8 D387A homodimers in others.
This dataset
Open GSE299620 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 GSE299620_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 PRJNA1275685 and SRA study SRP591790. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
11 conditions, mostly in triplicate
11449_Control ×3 6654_Casp8_D387A_KI ×3 11449_DKO ×3 11893_Casp1_TKO ×3 12146_Casp1_Ifnar_QKO ×3 12562_Casp1_FADD_QKO ×3 KI_MLKL_KO ×3 KI_MLKL_CASP1_DKO ×3 +6 more

Supports a between-group comparison across 33 samples.

How we read this: 11 replicated groups read from 36 sample titles; they account for 33 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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