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Single nuclear RNA sequencing and 10X spatial transcriptomic profiling of murine tumors initiated by transplantation of engineered prostate organoids [snRNA-seq]

GSE246768 Mus musculus (mouse) Single-nucleus RNA-seq 1 samples Submitted 2024/08/02 Platform GPL24247

At a glance

Single-nucleus RNA-seq · mouse · 1 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).
Organism: Mus musculus (mouse)
Samples: 1 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.
Paper: The neuroendocrine transition in prostate cancer is dynamic and dependent on ASCL1Nature cancer · 2024

Summary (written by the submitters)

Single-nuclear RNA-sequencing of murine organoid transplant-derived prostate tumors. Purpose: To identify differences in cell composition in murine prostatic tumors and to generate a reference dataset of all major cell types present in mouse prostate tumors Results: We recovered 4,872 cells with a median of 7055.5 UMIs per cell. Conclusions: snRNASeq reveals heterogeneity within neuroendocrine prostate cancer compartment, dominated by an Ascl1+ expression profile with mixed luminal lineage marker genes.

Read the full summary ↓

snRNASeq recovers all the major epithelial, immune, and stromal cell types in prostate tumors. Spatial transcriptomic profiling of murine prostate tumors. Purpose: To spatially map the major cell types in the mouse prostatic tumors and identify spatially distinct neuroendocrine tumor compartments. Distinct tumor microenvironments were also used for identification of cell:cell signaling axes distributed between the histological subtypes. Conclusions: Spatial transcriptomic profiling of the mouse prostate reveals all major cell types and allows for cell:cell signaling analyses upon integration with our matching snRNA-Seq data

Published in

The neuroendocrine transition in prostate cancer is dynamic and dependent on ASCL1

Romero R, Chu T, González Robles TJ et al. · Nature cancer 2024 · PMID 39394434 · doi:10.1038/s43018-024-00838-6

This dataset

Open GSE246768 in finder → Find more mouse 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 GSE246768_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 PRJNA1034583 and SRA study SRP469711. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39394434) ↗

Samples in this study

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+ 1 more — browse all 1 samples with per-sample file links →

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