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Molecular characterization of Wilms' Tumor: insights from single nucleus analystics on Wilms' Tumor development and oncogenesis

GSE273662 Homo sapiens (human) Single-nucleus RNA-seq 14 samples Submitted 2026/08/08 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 14 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). 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)
Topic
Wilms tumourThis series is part of our curated briefing on it.
Samples
14 samples: 9 × T vs 5 × KGroups 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
Single-nucleus RNA sequencing reveals transcriptional heterogeneity in the blastema of favorable-histology Wilms tumorJCI insight · 2026
Summary (written by the submitters)
Wilms tumors are known to arise from and maintain features of the embryonic kidney associated with a surprisingly heterogenous genetic and molecular landscape. To further investigate both intra-tumor and inter-tumor variability, single nucleus RNA-sequencing (snRNA-seq) was performed on favorable histology Wilms tumors capturing blastema, epithelial, and stromal components, which were analyzed in comparison to a normal kidney reference atlas established from kidney samples
Read the full summary ↓
(including patient-matched adjacent kidney) as well as publicly available single-cell RNA-seq from 18-week human fetal kidney. The transcriptomic profiles from Wilms tumor nuclei were shown to recapitulate its known triphasic histology, with similar gene expression signatures corresponding to nephron progenitor cells as well epithelial and stromal cells from human fetal kidneys. Tumors additionally show a high percentage of cycling cells in the G2/S phase, including tumor samples with blastemal cells both resembling “uninduced” nephron progenitors as well as tumor samples with blastema expressing more “differentiated” signatures of early proximal tubules, podocytes, as well as stromal/muscle genes. Furthermore, pathway enrichment analyses in the blastemal components show nephron/kidney epithelial development as expected, but interestingly also show neuronal/axon signatures across the majority of tumor samples. Additionally, enriched pathways in a subset of the tumors include WNT and TGF-beta signaling in the non-cycling blastema and polycomb repressive complex in cycling blastemal cells, suggesting that Wilms tumor blastema not only shows significant heterogeneity in its differentiation state/trajectory but also in its potential biological pathways/drivers.
Published in
Single-nucleus RNA sequencing reveals transcriptional heterogeneity in the blastema of favorable-histology Wilms tumor
Adam M, Drake KA, Pode-Shakked N et al. · JCI insight 2026 · PMID 42262873 · doi:10.1172/jci.insight.188078
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 GSE273662_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 PRJNA1142582 and SRA study SRP523415. Searching any of these in the dataset finder brings you back here.

Study design
9 × T vs 5 × K

Supports a between-group comparison across 14 samples.

How we read this: 2 replicated groups read from 14 sample titles; they account for 14 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 Wilms tumour 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.