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Toward More Translational Tumor Models: Breast dECM-Based 3D Systems Capture Native Microenvironmental Cues

GSE328288 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2026/07/01 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 15 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
Breast cancerThis series is part of our curated briefing on it.
Samples
15 samples: 5 conditions, mostly in triplicateGroups 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
Toward More Translational Tumor Models: Breast dECM-Based 3D Systems Capture Native Microenvironmental CuesBioengineering (Basel, Switzerland) · 2026
Summary (written by the submitters)
Current 3D tumor models for aggressive breast cancers inadequately recapitulate the native tumor microenvironment (TME), leading to poor translational potential. There is a critical need for models capable of mimicking the unique biochemical signals present in the TME. To address this gap, breast tissue and a patient derived xenograft tumor were decellularized and processed to produce breast tissue and tumor decellularized ECM (dECM).
Read the full summary ↓
Decellularized breast tissue histology confirmed complete cellular removal and maintained extracellular matrix (ECM). Further, DNA content was significantly reduced and ECM composition (POSTN, COLI, FN1) retained. Breast dECM was incorporated (0, 5, 10, and 20 µg/mL) with triple negative breast cancer cell lines to form spheroids. Imaging and histology demonstrated that cells in low dECM (5 and 10 µg/mL) formed compact singular spheres while higher dECM concentrations (20 and 50 µg/mL) resulted in cells concentrated on the outer edge of the sphere and irregular sphere circularity. RNA-sequencing of cells seeded in dECM demonstrated gene changes mediated by both dECM inclusion in spheroids and the composition of dECM. High-density tumor dECM enhanced genes associated with metastasis while high-density breast dECM enhanced tumor suppressors and anti-metastasis genes. These findings indicate dECM as a translational model with enhanced TME inclusion.
Published in
Toward More Translational Tumor Models: Breast dECM-Based 3D Systems Capture Native Microenvironmental Cues
Hebert KL, Savoie JJ, Hawes ML et al. · Bioengineering (Basel, Switzerland) 2026 · PMID 42351956 · doi:10.3390/bioengineering13060712
This dataset
Open GSE328288 in finder → Find more human RNA-seq datasets → Breast 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 GSE328288_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 PRJNA1454498 and SRA study SRP692498. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42351956) ↗
Study design
5 conditions, mostly in triplicate
231spheres_CNTL_noECM ×3 231spheres_adipose_10ug_mL_dECM ×3 231spheres_adipose_20ug_mL_dECM ×3 231spheres_4IC_10ug_mL_PDX_dECM ×3 231spheres_4IC_20ug_mL_PDX_dECM ×3

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 15 sample titles; they account for 15 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 Breast 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.