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A brain organoid/ALL co-culture model reveals the AP-1 pathway as critically associated with CNS involvement of BCP-ALL

GSE271750 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/07/15 Platform GPL30173
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
Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples
12 samples: 3 × 697 - isolated from organoid vs 3 × 697 - isolated from suspension vs 3 × KASUMI2 - isolated from organoid vs 3 × KASUMI2 - isolated from suspensionGroups 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)
Central nervous system (CNS) involvement remains a clinical hurdle in treating childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL). The disease mechanisms of CNS leukemia are primarily investigated using 2D cell culture and mouse models. Given the variations in cellular identity and architecture between the human and murine CNS, it becomes imperative to seek complementary models to study CNS leukemia.
Read the full summary ↓
Here, we present a first-of-its-kind 3D co-culture model combining human brain organoids and BCP-ALL-cells. We noticed significantly higher engraftment of BCP-ALL cell lines and patient-derived xenograft (PDX) cells in cerebral organoids as compared to non-ALL-cells. To validate translatability between organoid co-culture and in vivo murine models, we confirmed that targeting CNS leukemia relevant pathways like CD79a/Igα or CXCR4- SDF1 reduced the invasion of BCP-ALL-cells into organoids. RNA sequencing and functional validations of organoid-invading leukemia cells compared to the non-invaded fraction revealed significant upregulation of AP-1 transcription factor-complex members in organoid-invading cells. Moreover, we detected a significant enrichment of AP-1 pathway genes in ALL-PDX-cells recovered from the CNS compared to spleen blasts of mice transplanted with TCF3::PBX1+ PDX-cells, substantiating the role of AP-1 signaling in CNS disease. Accordingly, we found significantly higher levels of the AP-1-gene JUN in patients initially diagnosed as CNS-positive compared to CNS negative cases as well as CNS-relapse vs non-CNS-relapse cases in a cohort of 100 BCP-ALL-patients. Our results suggest CNS-organoids as a novel model to investigate CNS-involvement and identify the AP-1 pathway as a critical driver of CNS-disease in BCP-ALL.
This dataset
Open GSE271750 in finder → Find more human RNA-seq datasets → Acute lymphoblastic leukemia landscape →
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 GSE271750_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 PRJNA1133032 and SRA study SRP518564. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × 697 - isolated from organoid vs 3 × 697 - isolated from suspension vs 3 × KASUMI2 - isolated from organoid vs 3 × KASUMI2 - isolated from suspension

Supports a between-group comparison across 12 samples.

How we read this: 4 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
More Acute lymphoblastic leukemia datasets

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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.