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Integrated transcriptomic and bioelectrical profiling of stem-like cellular states in a colorectal cancer using SdFFF and UHF-DEP

GSE342462 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/08/08 Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 12 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Colorectal cancerThis series is part of our curated briefing on it.
Samples
12 samples: 4 × F1 subpopulation derived from SdFFF sorting of SW480 cells, vs 4 × F3 subpopulation derived from SdFFF sorting of SW480 cells, vs 4 × PT subpopulation derived from SdFFF sorting of SW480 cells,Groups 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)
Cancer stem-like cells (CSCs) enrichment and characterization remain an analytical challenge, as conventional marker-based approaches are often time-consuming and can alter cellular properties. Here, we develop a complete label-free protocol for the enrichment and characterization of cellular states associated to stemness properties in colorectal cancer model, based on the coupling adjustment of sedimentation field-flow fractionation (SdFFF) and ultra-high-frequency dielectrophoresis (UHF-DEP).
Read the full summary ↓
To this end, the operating conditions of SdFFF were adapted to a low conductivity dielectrophoresis buffer while maintaining the hyperlayer elution regime. Fractionated cellular subpopulation exhibits phenotypic differences in proliferative status, clonogenic potential, stem-cell related protein levels and UHF-DEP highlights significantly different high-frequency crossover distributions. Transcriptome sequencing revealed dysregulation of pathways associated with stemness, cell adhesion, membrane organization, calcium signaling and ion-channel activity, that can be linked to dielectric signatures. Overall, UHF-DEP coupling to SdFFF permit to enrich, characterize and quantify stem cell-like subpopulation within heterogeneous population of cancer cells.
This dataset
Open GSE342462 in finder → Find more human RNA-seq datasets → Colorectal cancer landscape →
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 GSE342462_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1507902 and SRA study SRP724360. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
4 × F1 subpopulation derived from SdFFF sorting of SW480 cells, vs 4 × F3 subpopulation derived from SdFFF sorting of SW480 cells, vs 4 × PT subpopulation derived from SdFFF sorting of SW480 cells,

Supports a between-group comparison across 12 samples.

How we read this: 3 replicated groups read from 12 sample titles; they account for 12 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 Colorectal cancer datasets

Search all human RNA-seq datasets in GEO →

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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.