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Bioprinted spatially defined breast tumor microenvironment models of intratumoral heterogeneity and drug resistance

GSE269415 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/06/13 Platform GPL23227
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 18 samples, each with a distinct title — no replicated groupsGroups 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
Bioprinted, spatially defined breast tumor microenvironment models of intratumoral heterogeneity and drug resistanceTrends in biotechnology · 2024
Summary (written by the submitters)
Cellular extracellular matrix (ECM) and spatial heterogeneity of tumor microenvironments (TME) regulate disease progression and treatment efficacy. Developing in vitro models that recapitulate the TME promises to accelerate studies of tumor biology and identify new targets for therapy. Here, we employed extrusion-based, multi-nozzle three-dimensional (3D) bioprinting to spatially pattern triple-negative MDA-MB-231 breast cancer cells, endothelial cells, and human mammary cancer-associated fibroblasts with biomimetic ECM inks.
Read the full summary ↓
Bioprinted models captured key features of the spatial architecture of human breast tumors, including varying-sized dense regions of cancer cells and surrounding microvessel-rich stroma. Angiogenesis and ECM stiffening occurred in the stromal area but not the cancer cell rich regions, mimicking pathological changes in patient samples. Transcriptomic analyses revealed upregulation of angiogenesis-related and ECM remodeling-related signatures in the stroma region and identified potential ligand-receptor mediators of these processes. Breast cancer cells in distinct parts of the bioprinted TME showed differing sensitivities to chemotherapy, highlighting environmentally mediated drug resistance. In summary, our 3D bioprinted tumor model will act as a platform to discover integrated functions of the TME in cancer biology and therapy.
Published in
Bioprinted, spatially defined breast tumor microenvironment models of intratumoral heterogeneity and drug resistance
Yuan T, Fu X, Hu R et al. · Trends in biotechnology 2024 · PMID 39112274 · doi:10.1016/j.tibtech.2024.06.007
This dataset
Open GSE269415 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 GSE269415_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 PRJNA1121410 and SRA study SRP512509. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39112274) ↗
Study design
18 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 18 sample titles: 18 distinct titles with little repetition. 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.