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c-JUN Enhances CRISPR Knock-In anti-B7-H3 CAR T-cell Function for Treatment of Small Cell Lung Cancer and thoracic SMARCA4-deficient undifferentiated tumors

GSE307259 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/11/13 Platform GPL24676
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)
Topic
Small cell lung cancerThis series is part of our curated briefing on it.
Samples
12 samples: 12 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
c-JUN enhances CRISPR knockin anti-B7-H3 CAR T cell function in small cell lung cancer and thoracic SMARCA4-deficient undifferentiated tumorsCell reports. Medicine · 2026
Summary (written by the submitters)
Small Cell Lung Cancer (SCLC), a highly lethal disease, limits T-cell responses by downregulating Major Histocompatibility (MHC) class I molecules. Because chimeric antigen receptor (CAR) T-cells are not MHC-restricted, they may provide a powerful strategy against SCLC. However, few CAR targets for SCLC have been identified. Here we show that B7-H3/CD276 is expressed on the surface of SCLC and thoracic SMARCA4-deficient undifferentiated tumor (UT) cells that can clinicopathologically mimic SCLC.
Read the full summary ↓
Thoracic SMARCA4-deficient UT, despite high B7-H3 expression, limit killing by B7-H3 CAR-T cells via secretion of transforming growth factor beta 1 (TGFB1). To overcome tumor-driven CAR-T cell suppression, we knocked-in c-JUN alongside a B7-H3 CAR into the TRAC locus of primary human T-cells utilizing CRISPR/Cas9. Non-viral c-JUN+B7-H3 CAR-T cells show enhanced killing of both SCLC cells with low antigen density and thoracic SMARCA4-deficient UT, providing a platform to address these highly aggressive entities. We also provide evidence that GMP clinical scale manufacturing is feasible for c-JUN+B7-H3 CAR-T cells.
Published in
c-JUN enhances CRISPR knockin anti-B7-H3 CAR T cell function in small cell lung cancer and thoracic SMARCA4-deficient undifferentiated tumors
Balke-Want H, Keerthi V, Del Carmen Arenas M et al. · Cell reports. Medicine 2026 · PMID 41564857 · doi:10.1016/j.xcrm.2025.102549
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 GSE307259_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 PRJNA1306191 and SRA study SRP609027. Searching any of these in the dataset finder brings you back here.

Study design
12 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 12 sample titles: 12 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
More Small cell lung cancer datasets

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