GEO series

Single cell gene expression profiling of the SW620 colorectal cell line

GSE270763 Homo sapiens (human) Single-cell RNA-seq 1 samples Submitted 2024/07/16 Platform GPL11154

At a glance

Single-cell RNA-seq · human · 1 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: 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 SW480 cell line as a model of resident and migrating colon cancer stem cellsiScience · 2024

Summary (written by the submitters)

Intra-tumor heterogeneity, i.e. the presence of diverse cell types and subpopulations within tumors, presents a significant obstacle in cancer treatment due to its negative consequences for resistance to therapy and disease recurrence. However, the mechanisms which underlie intra-tumor heterogeneity and result in the plethora of different cancer cells within a single lesion remain poorly understood.

Read the full summary ↓

Here, we leverage the SW480 and SW620 cell lines as a model system to investigate the molecular and functional diversity of colon cancer cells. Through a combination of fluorescence activated cell sorting (FACS) analysis and transcriptomic profiling, we identify three distinct subpopulations, namely resident cancer stem cells (rCSCs), migratory CSCs (mCSCs), and high-relapse cells (HRCs). These subpopulations show varying Wnt signaling levels and gene expression profiles mirroring their stem-like properties. Examination of publicly available spatial transcriptomic data confirms the presence of these subpopulations in patient-derived cancers and reveals their distinct spatial distribution relative to the tumor microenvironment.

Published in

The SW480 cell line as a model of resident and migrating colon cancer stem cells

Verhagen MP, Xu T, Stabile R et al. · iScience 2024 · PMID 39246444 · doi:10.1016/j.isci.2024.110658

This dataset

Open GSE270763 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 GSE270763_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 PRJNA1128134 and SRA study SRP516145. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39246444) ↗

Samples in this study

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

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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.