← BioTransfer GEO Dataset Finder
GEO series

Next-GenerationPediatric Cancer Models: Patient-Matched Orthotopic Xenografts, 3D Organoids, 2D Cultures, and Cell Lines for Identification of Therapeutic Vulnerabilities in Pediatric Solid Tumors [scRNAseq]

GSE319124 Homo sapiens (human) Single-cell RNA-seq 59 samples Submitted 2026/08/06 Platform GPL24676Platform GPL34284
At a glance

Single-cell RNA-seq · human · 59 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
59 samples: 58 distinct titles, 1 of them repeatedGroups 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)
Most pediatric solid tumor cell lines were established decades ago, so patient-matched organoids and xenografts are not available, limiting their translational utility. Here, we present a new approach to generate triads of patient-matched xenografts, 3-dimensional (3D) organoids, and 2D cultures. We have generated 3D organoids from 135 pediatric tumors, including rhabdomyosarcoma, osteosarcoma, neuroblastoma, Ewing sarcoma, Wilms tumor, and retinoblastoma.
Read the full summary ↓
We have also generated patient-matched 2D cultures (n=82) and cell lines (n=20). When these 3D organoids, 2D cultures, or cell lines were orthotopically implanted into immunocompromised mice, they replicated the molecular and cellular features of the original patient tumor and xenograft. We have completed 352 single-cell and single-nucleus RNA-sequencing experiments (>2.2 million cells) to confirm that our patient-matched triads preserve tumor cell heterogeneity. All samples are renewable and >3,000 vials have been cryopreserved for unrestricted distribution through the Childhood Solid Tumor Network. We demonstrate the utility of patient-matched triads for identifying therapeutic vulnerabilities, providing a powerful tool for advancing pediatric cancer research.
This dataset
Open GSE319124 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 GSE319124_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: 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 PRJNA1422141 and SRA study SRP676295. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
58 distinct titles, 1 of them repeated
SJRHB010928_C1_DYE ×2

How we read this: Read from 59 sample titles: 58 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

+ 19 more — browse all 59 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.