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Targeting axonal guidance dependencies in glioblastoma with ROBO1 CAR T cells

GSE240490 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2024/08/30 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 20 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
20 samples: 20 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
Targeting axonal guidance dependencies in glioblastoma with ROBO1 CAR T cellsNature medicine · 2024
Summary (written by the submitters)
Resistance to genotoxic therapies and tumor recurrence are hallmarks of glioblastoma (GBM), an aggressive brain tumor. Here, we explore functional drivers of post-treatment recurrent GBM. By conducting genome-wide CRISPR-Cas9 knockout screens in patient-derived GBM models, we uncover distinct genetic dependencies in recurrent tumor cells absent in their patient-matched primary predecessors, accompanied by increased mutational burden and differential transcript and protein expression.
Read the full summary ↓
These analyses map a multilayered genetic response to drive tumor recurrence, identifying protein tyrosine phosphatase 4A2 (PTP4A2) as a novel modulator of self-renewal, proliferation and tumorigenicity at GBM recurrence. Genetic perturbation or small molecule inhibition of PTP4A2 activity represses axon guidance activity through a dephosphorylation axis with roundabout guidance receptor 1 (ROBO1), exploiting a functional dependency on ROBO signaling. Importantly, engineered anti-ROBO1 single-domain antibodies mimic effects of PTP4A2 inhibition. Since a pan-PTP4A inhibitor was limited by poor penetrance across the blood brain barrier (BBB) in vivo, a second-generation chimeric antigen receptor (CAR)-T cell therapy was engineered against ROBO1 that elicits specific and potent anti-tumor responses in vivo. A single dose of anti-ROBO1 CAR-T cells doubles median survival in patient-derived xenograft (PDX) models of recurrent glioblastoma, and also eradicates tumors in ~50% of mice in PDX models of adult lung-to-brain metastases and pediatric relapsed medulloblastoma. We conclude that functional reprogramming drives tumorigenicity and dependence on a multi-targetable PTP4A-ROBO1 signaling axis at GBM recurrence, with potential in other malignant brain tumors.
Published in
Targeting axonal guidance dependencies in glioblastoma with ROBO1 CAR T cells
Chokshi CR, Shaikh MV, Brakel B et al. · Nature medicine 2024 · PMID 39095594 · doi:10.1038/s41591-024-03138-9
This dataset
Open GSE240490 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 GSE240490_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 PRJNA1003904 and SRA study SRP454351. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39095594) ↗
Study design
20 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 20 sample titles: 20 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

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