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L-type voltage-gated Ca2+ channels control T cell killing via non-canonical Hedgehog signaling

GSE305142 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/03/20 Platform GPL24247
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 × t_24h_Carrier, vs 6 × t_24h_FPL, vs 6 × t_3h_Carrier, vs 6 × t_3h_FPL,Groups 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)
Cytotoxic CD8+ T lymphocytes (CTLs) efficiently eliminate infected and cancerous cells throughout the body. Hedgehog signaling is critical for CTL-mediated killing. Remarkably the pathway cannot be induced canonically by extracellular Hedgehog ligands but instead is activated by the T cell receptor (TCR). How the Hedgehog pathway is mechanistically activated downstream of the TCR is unknown.
Read the full summary ↓
Here we show that L-type voltage gated Ca2+ (Cav1) channels at the plasma membrane downstream of the TCR control an extracellular Ca2+ influx leading to induction of the Hedgehog transcription factor Gli1 which is essential for efficient CTL killing in vitro and in vivo. This novel non-canonical Hedgehog pathway is independent of canonical signaling and represents a primary mechanism of Gli1 induction in naive CD8+ T cells, while CTLs can also activate Gli1 via MAPK. We show that Cav1 channel-controlled Gli1 induction is functionally required for CTL killing in mice and humans and other cytotoxic lymphocytes. Importantly, we demonstrate that killing capacity can be amplified using a small molecule Cav1 channel agonist or by overexpression of a gain-of-function Cav1 subunit. Our findings indicate that Gli inhibitors, currently in clinical trials as anti-cancer therapeutics, likely inhibit the cytotoxic anti-tumor response. On the other hand, our work opens up the possibility to enhance CTL performance in the clinic by selectively increasing Ca2+ flux via Cav1 channels, for example in the context of CAR T cell therapy.
This dataset
Open GSE305142 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 GSE305142_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 PRJNA1304502 and SRA study SRP608121. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 × t_24h_Carrier, vs 6 × t_24h_FPL, vs 6 × t_3h_Carrier, vs 6 × t_3h_FPL,

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
Datasets on a similar topic

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