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Comparison of gene expression by activated T-cells that express NKG2D-based CARs

GSE249511 Homo sapiens (human) RNA-seq (gene expression) 17 samples Submitted 2024/10/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 17 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
17 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.
Paper
Solid tumor immunotherapy using NKG2D-based adaptor CAR T cellsCell reports. Medicine · 2024
Summary (written by the submitters)
NKG2D ligands are broadly expressed in cancer. To exploit this, we engineered an adaptor chimeric antigen receptor (CAR) termed NKG2D / Dap10-12 in which NKG2D is co-expressed with a fusion of Dap10 and the Dap12 endodomain. Dap10 was deployed to provide co-stimulation while Dap12 delivers an activation signal via a single immunoreceptor tyrosine-based activation motif (ITAM).
Read the full summary ↓
NKG2D / Dap10-12 T-cells elicited compelling anti-tumor activity in several solid tumor xenograft models. Disease eradication was accompanied by sustained functional persistence, indicated by reproducible protection from secondary tumor re-challenge. Anti-cancer activity was consistently superior to an analog of a clinical stage linear CAR comprising an NKG2D-CD3 fusion. Mechanistically, functionality of NKG2D / Dap10-12 CAR T-cells was underpinned by transcriptomic re-programming to increase oxidative phosphorylation and ribosome biosynthesis..
Published in
Solid tumor immunotherapy using NKG2D-based adaptor CAR T cells
Obajdin J, Larcombe-Young D, Glover M et al. · Cell reports. Medicine 2024 · PMID 39566469 · doi:10.1016/j.xcrm.2024.101827
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 GSE249511_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 PRJNA1049416 and SRA study SRP476179. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 17 more — browse all 17 samples with per-sample file links →

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