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Radiopharmaceuticals enhance CAR T-cells against radio-sensitive and radio-resistant neuroblastoma by tumor sensitization and TME remodeling [RNA-Seq]

GSE330929 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/05/18 Platform GPL34284
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: 24 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.
Summary (written by the submitters)
Chimeric antigen receptor (CAR) T-cell therapy has limited efficacy against solid tumors such as neuroblastoma (NB). Key obstacles include extensive tumor burden and the presence of an immunosuppressive tumor microenvironment (TME). We employ targeted radiopharmaceutical therapy (RPT) using [67Cu]Cu-LLP2A and find that it potentiated the anti-tumor activity of CAR T-cells in radio-sensitive and radio-resistant NB models via distinct mechanisms.
Read the full summary ↓
In radio-sensitive NB, RPT is directly tumoricidal while also enhancing CAR T-cell efficacy through pro-immune pathways, most notably via the TNFα pathway, leading to paracrine activation of T-cells. In radio-resistant NB, RPT improves CAR T-cells by remodeling the myeloid compartment in the TME and increasing the formation of immunological niches of cytotoxic CD8⁺ GZMB⁺ and CD4⁺ GZMB+ CAR T-cells. While neither treatment modality alone can effectively treat NB, the combination of VLA-4-targeted RPT and GD2 or B7-H3 CAR T-cells augments anti-tumor efficacy, resulting in marked tumor regression in preclinical NB models.
This dataset
Open GSE330929 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 GSE330929_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 PRJNA1466208 and SRA study SRP700499. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
24 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 24 sample titles: 24 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
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.