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Multiple Nf1 Schwann cell populations reprogram the plexiform neurofibroma tumor microenvironment

GSE181985 Homo sapiens (human) Single-cell RNA-seq 31 samples Submitted 2022/11/23 Platform GPL18573Platform GPL17021
At a glance

Single-cell RNA-seq · human · 31 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
31 samples
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)
To define alterations early in tumor formation, we studied nerve tumors in neurofibromatosis 1 (NF1), a tumor predisposition syndrome in which affected individuals develop plexiform neurofibroma (PN). These benign tumors are driven by NF1 loss in Schwann cells (SC). By comparing normal nerve cells to PN cells using single cell and bulk RNA sequencing, we identified changes in five SC populations, including a de novo Schwann cell progenitor-like population.
Read the full summary ↓
Long after Nf1 loss, SC populations developed PN-specific expression of Dcn, Postn, and CD74, and showed dramatic expansion of immune and stromal cell populations; in human PN, immune and stromal cells comprised 90% of cells. Label transfer enabled verification of each SC population and predicted tumor unique patterns of cell-cell communication in each SC population. We identified PROS-AXL, FGF-FGFR, and MIF-CD74 and its effector pathway NFkB as deregulated in NF1 SC populations, including SCP-like cells. Each receptor-ligand pair was predicted to influence surrounding cells in mouse and human. These findings highlight remarkable changes in all PN cells driven by loss of NF1 in multiple types of SCs and identify therapeutic targets for PN.
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 GSE181985_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA754135 and SRA study SRP332271. Searching any of these in the dataset finder brings you back here.

Samples in this study

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