GEO series

Transcriptional Regulation by NFATc1 and NFATc2 in chronically activated CD8+ T cells

GSE253492 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2026/07/14 Platform GPL30172

At a glance

RNA-seq (gene expression) · mouse · 16 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: 16 samples: 5 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)

Both chronic viral infections and progressing tumors result in dysfunctional CD8+T cells in a process called exhaustion. Such TEX cells exhibit a reduced proliferative capacity, reduced cytokine expression and target cell killing. They are characterized by increased expression of co-inhibitory receptors as PD-1, Tim-3, Lag-3 and TIGIT, and resistance against immune checkpoint therapies (ICT).

Read the full summary ↓

These cells develop from so called precursors of exhaustion (TPEX) that express high levels of TCF1 and Ly108 and still respond to ICT. The NFAT factors NFATc1 and NFATc2 play a crucial role in exhaustion of CD8+ T cells and, thereby, in suppression of tumor formation by immune cells. NFATc1 is the most prominent NFAT factor in nuclei of activated T cells and the inducible isoform NFATc1/aA, is strongly expressed in chronically induced CD8+ T cells. The inducible expression of NFATc1/aA is controlled by the distal enhancer E2 and conditional ablation of E2 abolish this induction. We compared here the transcriptome of in vitro chronically stimulated CD8+ T cells with different NFAT deficiencies. While the ablation of NFATc2 resulted in reduced expression of exhaustion markers Tim3 and Tigit and increased expression of Tcf7 and Slamf6, only minor effects on exhaustion markers were detected upon ablation of inducible NFAT1/aA or entire NFATc1.

This dataset

Open GSE253492 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 GSE253492_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 PRJNA1065893 and SRA study SRP484281. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

5 conditions, mostly in triplicate

CD8_plus_Tcells_WT ×5 CD8_plus_Tcells_E2ko ×3 CD8_plus_Tcells_Nc1ko ×3 CD8_plus_Tcells_Nc2ko ×3 CD8_plus_Tcells_Nc1Nc2ko ×2

Supports a between-group comparison across 16 samples.

How we read this: 5 replicated groups read from 16 sample titles; they account for 16 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

GSM8021649 CD8_plus_Tcells_WT_1 CD8_plus_Tcells_WT
GSM8021650 CD8_plus_Tcells_WT_2 CD8_plus_Tcells_WT
GSM8021651 CD8_plus_Tcells_WT_3 CD8_plus_Tcells_WT
GSM8021652 CD8_plus_Tcells_WT_4 CD8_plus_Tcells_WT
GSM8021653 CD8_plus_Tcells_WT_5 CD8_plus_Tcells_WT
GSM8021654 CD8_plus_Tcells_E2ko_1 CD8_plus_Tcells_E2ko
GSM8021655 CD8_plus_Tcells_E2ko_2 CD8_plus_Tcells_E2ko
GSM8021656 CD8_plus_Tcells_E2ko_3 CD8_plus_Tcells_E2ko
GSM8021657 CD8_plus_Tcells_Nc1ko_1 CD8_plus_Tcells_Nc1ko
GSM8021658 CD8_plus_Tcells_Nc1ko_2 CD8_plus_Tcells_Nc1ko
GSM8021659 CD8_plus_Tcells_Nc1ko_3 CD8_plus_Tcells_Nc1ko
GSM8021660 CD8_plus_Tcells_Nc2ko_1 CD8_plus_Tcells_Nc2ko
GSM8021661 CD8_plus_Tcells_Nc2ko_2 CD8_plus_Tcells_Nc2ko
GSM8021662 CD8_plus_Tcells_Nc2ko_3 CD8_plus_Tcells_Nc2ko
GSM8021663 CD8_plus_Tcells_Nc1Nc2ko_1 CD8_plus_Tcells_Nc1Nc2ko
GSM8021664 CD8_plus_Tcells_Nc1Nc2ko_2 CD8_plus_Tcells_Nc1Nc2ko

Datasets on a similar topic

GSE290455 RNAseq of activated CD8+ T cells with and without Glutamine Synthetase 10 samples shares cd8, activated
GSE232024 Differences in gene expression of liver cancer cells after co-culture with activated CD8+ T cells in vitro 10 samples shares cd8, activated
GSE281719 PD-1 Mediated Regulation of Unique Activated CD8+ T Cells by NK Cells in the Submandibular Gland [I15, I16] 60 samples shares cd8, activated
GSE337601 XCR1+ and CD11b+ migratory dendritic cells cooperate for the crosspriming of intratumoral CD8+ T cells with a tissue-resident memory phenotype [RNA-Seq] 36 samples shares cd8
GSE306744 Pre-division TCF1 downregulation determines long-term effector and memory CD8 T cell fates [RNA-Seq] 31 samples shares cd8
GSE338265 Smad4 and Eomes converge on a shared transcriptional program associated with inflammatory CD8 T-cell differentiation 31 samples shares cd8
GSE331107 The transcription factor AFF3 is necessary to maintain metabolic quiescence in naïve CD8 T cells and prevent premature immune aging 30 samples shares cd8
GSE316541 α2,6-Sialoglycan-regulated anti-tumor immunity of tumor-infiltrating CD8+ T cells in the tumor microenvironment [CD8+T] 27 samples shares cd8

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.