GEO series

Transcriptomic Profiling of anti-CD276/NKG2DLs CAR-T Cells Stimulated by A549 Cells

GSE302681 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/12/12 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 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: Homo sapiens (human)
Samples: 24 samples
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)

1. we performed a bulk RNA-seq analysis after 24-hour co-culture with A549 cells. Compared with untransduced T cells, CAR-T cells presented broad transcriptomic differences. Pathway enrichment analysis of the differentially expressed genes (DEGs) revealed significantly upregulated cytokine-receptor cross-talk pathway, as well as TNF, JAK-STAT, NF-κB, and IL-17 signaling pathways in CAR-T cells compared with that in UTD.

Read the full summary ↓

All these pathways are critical for T cell activation, proliferation, differentiation, and effector functions. 2. We also carried out continuous antigen exposure (CAE) wherein CAR-T cells were induced into an exhaustion state. We observed substantial transcriptomic differences and thousands of DEGs among distinct CAR-T cell groups and the UTD group. To better understand the specific advantages of Bicephali CAR-T cells over two single-targeting CAR-T cells, we employed Venn diagrams to visualize the DEGs among the three groups and revealed 346 unique DEGs of multi-targeting Bicephali CAR-T cells. We further subjected these 346 DEGs to Gene Ontology (GO) pathway enrichment analysis and found that positive regulation of T cell function and oxidative stress were among the top enriched pathways.

This dataset

Open GSE302681 in finder → Find more human 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 GSE302681_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 PRJNA1291725 and SRA study SRP601027. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 24 more — browse all 24 samples with per-sample file links →

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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.