← BioTransfer GEO Dataset Finder
GEO series

Characterizing the gene expression profiles of 4T1 and 4T1.2 cells at different stages of bone metastsis using SMART-Seq2 technology

GSE241165 Mus musculus (mouse) Single-cell RNA-seq 1248 samples Submitted 2024/07/01 Platform GPL21273
At a glance

Single-cell RNA-seq · mouse · 1248 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
1248 samples: 400 × 4T1, Day4, single cellGroups 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)
Bone metastasis, a frequent and devastating occurrence in breast cancer, affects over 70% of patients over time. Intriguingly, cancer cells residing within the bone microenvironment can serve as "cancer seeds," disseminating to distant organs and driving extensive metastasis. Even post-successful primary tumor removal, quiescent cells can persist, contributing to bone recurrence.
Read the full summary ↓
This phenomenon underscores the remarkably low efficiency of bone metastasis establishment and underscores the significance of comprehending the molecular underpinnings of this early bone-seeding phase. Deciphering the mechanisms orchestrating tumor cell dormancy and reawakening holds pivotal implications for designing effective anti-cancer therapies. Dormant tumor cells within the bone might be likened to being ensnared in an "extended seeding phase" prior to eventual expansion. Conceivably, shared signaling molecules could govern both proficient bone metastatic colonization and the re-emergence of indolent metastatic cells. Consequently, the molecular facilitators enabling bone colonization could also be integral to the reactivation of dormant tumor cells within the bone milieu. In this study, we conducted single-cell RNA sequencing (scRNA-seq) analysis on tumor cells procured from the initial stages of bone colonization within experimental bone metastasis models. Our investigation unearthed potential factors that foster tumor cell survival during this critical seeding phase.
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 GSE241165_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 PRJNA1006666 and SRA study SRP455797. Searching any of these in the dataset finder brings you back here.

Study design
400 × 4T1, Day4, single cell

Supports a between-group comparison across 400 samples.

How we read this: 1 replicated groups read from the first 400 of 1248 sample titles; they account for 400 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

+ 1208 more — browse all 1248 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.