GEO series

Selective refueling of CAR T cells using ADA1 and CD26 boosts antitumor immunity

GSE262447 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2024/03/27 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 15 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: 15 samples: 15 samples, each with a distinct title — no replicated groupsGroups 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.
Paper: Selective refueling of CAR T cells using ADA1 and CD26 boosts antitumor immunityCell reports. Medicine · 2024

Summary (written by the submitters)

CAR T cell therapy has revolutionized the treatment of hematologic malignancies, but its efficacy in solid tumors remains limited due to the immunosuppressive nature of the tumor microenvironment and the inability of T cells to persist and traffic to the tumor site. While current strategies focus on enhancing CAR T cell activity through costimulatory molecules and cytokines, a critical yet often overlooked factor is the competition for nutrients between tumor cells and T cells in the nutrient-deprived tumor microenvironment.

Read the full summary ↓

To address this challenge, we employed a selective metabolic refueling (MR) strategy by providing T cells with inosine as an alternative fuel source for growth and functionality. In this study, we engineered CAR T cells to co-express a membrane-bound CD26 and a cytoplasmic adenosine deaminase 1 (ADA1) fused to an anti-CD3 scFv. ADA1 irreversibly converts both intracellular and extracellular adenosine to inosine, overcoming adenosine-mediated immunosuppression and providing T cells with inosine for growth. The inclusion of an anti-CD3 scFv fusion partner and overexpressing CD26 boosts ADA1 capture in a membrane proximal manner, providing inosine for T cells and minimizing feeding the tumor cells. We demonstrate that ADA1 is conditionally secreted in an autocrine manner in response to CD3/CD26 stimulation and that it activates CAR T cells through trans-signaling in a tumor-specific manner. In addition, we show that, compared to unmodified CAR T cells, CD26-overexpressing CAR T cells have better migration capacity and are less susceptible to TGF-β1 suppression. Finally, we demonstrate that, in mice models of human hepatocellular carcinoma (GPC3-MR-CAR) and human non-small cell lung cancer (HER2-MR-CAR), metabolically refueled CAR T cells (MR-CAR) are more efficient in reducing tumor growth than unmodified CAR T cells. Thus, selective refueling CAR T cells using ADA1 and CD26 holds promise for improving the efficacy of CAR T cell therapy of solid tumors.

Published in

Selective refueling of CAR T cells using ADA1 and CD26 boosts antitumor immunity

Hu Y, Sarkar A, Song K et al. · Cell reports. Medicine 2024 · PMID 38688275 · doi:10.1016/j.xcrm.2024.101530

This dataset

Open GSE262447 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 GSE262447_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 PRJNA1091888 and SRA study SRP497849. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38688275) ↗

Study design

15 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 15 sample titles: 15 distinct titles with little repetition. 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

GSM8169900 GPC3 CAR Expressed in T-cell (replicate 1)
GSM8169901 GPC3 CAR Expressed in T-cell (replicate 2)
GSM8169902 GPC3 CAR Expressed in T-cell (replicate 3)
GSM8169903 Metabolic refueling modified GPC3 CAR expressed in T-cell (replicate 1)
GSM8169904 Metabolic refueling modified GPC3 CAR expressed in T-cell (replicate 2)
GSM8169905 Metabolic refueling modified GPC3 CAR expressed in T-cell (replicate 3)
GSM8169906 HER2 CAR Expressed in T-cell (replicate 1)
GSM8169907 HER2 CAR Expressed in T-cell (replicate 2)
GSM8169908 HER2 CAR Expressed in T-cell (replicate 3)
GSM8169909 Metabolic refueling modified HER2 CAR expressed in T-cell (replicate 1)
GSM8169910 Metabolic refueling modified HER2 CAR expressed in T-cell (replicate 2)
GSM8169911 Metabolic refueling modified HER2 CAR expressed in T-cell (replicate 3)
GSM8169912 Non-transduced T-cell (replicate 1)
GSM8169913 Non-transduced T-cell (replicate 2)
GSM8169914 Non-transduced T-cell (replicate 3)

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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.