GEO series

Spatially controlled enhanced anti-tumor efficacy via CAR T cells engineered with a CTLA-4-based autoregulated circuit

GSE310581 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/11/23 Platform GPL34281

At a glance

RNA-seq (gene expression) · human · 12 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: 12 samples: 6 conditions, mostly in duplicateGroups 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)

The widespread application of CAR T cell therapy to solid tumors is hindered by antigen expression heterogeneity, on-target off-tumor toxicity, and limited functional persistence of CAR T cells. Next generation engineering strategies aiming to overcome these hurdles rely on multiple antigen-targeting approaches that fail to simultaneously address all the limitations and/or the use of synthetic receptor transcriptional circuits, which suffer from slow activation kinetics.

Read the full summary ↓

Here, we leveraged the unique trafficking properties of CTLA-4, regulated by a rapid internalization process, to create CTLA-4-based activation-inducible antigen receptors (CAVI-Rs). CAVI-Rs were exclusively expressed on T cells upon activation with remarkably fast on/off kinetics and self-sustainable expression. In in vitro and in vivo models of heterogeneous tumors, CAR+CAVI-R dual-engineered T cells demonstrated enhanced cytotoxicity and tumor-selective, spatially restricted functionality. Additionally, intermittent co-expression of the CAVI-R lead to improved T cell metabolic and transcriptional fitness, resulting in superior expansion, persistence and anti-tumor efficacy. The CAVI-R provides a novel, simple, safe, potent, and fully-human approach to expand CAR T cell applicability while improving anti-tumor outcomes.

This dataset

Open GSE310581 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 GSE310581_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 PRJNA1366526 and SRA study SRP646998. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 conditions, mostly in duplicate

CR_CAVIR_D2_d ×2 CR_CAVIR_J1_d ×2 CR_CAVIR_J3_d ×2 CR_CCR_D2_d ×2 CR_CCR_J1_d ×2 CR_CCR_J3_d ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 replicated groups read from 12 sample titles; they account for 12 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

GSM9304129 CR_CAVIR_D2_d0 CR_CAVIR_D2_d
GSM9304130 CR_CAVIR_D2_d14 CR_CAVIR_D2_d
GSM9304131 CR_CAVIR_J1_d0 CR_CAVIR_J1_d
GSM9304132 CR_CAVIR_J1_d14 CR_CAVIR_J1_d
GSM9304133 CR_CAVIR_J3_d0 CR_CAVIR_J3_d
GSM9304134 CR_CAVIR_J3_d14 CR_CAVIR_J3_d
GSM9304135 CR_CCR_D2_d0 CR_CCR_D2_d
GSM9304136 CR_CCR_D2_d14 CR_CCR_D2_d
GSM9304137 CR_CCR_J1_d0 CR_CCR_J1_d
GSM9304138 CR_CCR_J1_d14 CR_CCR_J1_d
GSM9304139 CR_CCR_J3_d0 CR_CCR_J3_d
GSM9304140 CR_CCR_J3_d14 CR_CCR_J3_d

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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.