GEO series

Mesenchymal-epithelial transition reduces proliferation but increases immune evasion in tumor spheroids

GSE289535 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/06/10 Platform GPL21697

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)
Samples: 12 samples: 12 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: Mesenchymal-epithelial transition reduces proliferation but increases immune evasion in tumor spheroidsiScience · 2025

Summary (written by the submitters)

The mesenchymal-epithelial transition (MET) has been implicated in secondary tumor growth during metastasis, yet the underlying mechanisms remain unclear. Here, we explore whether MET enhances tumor outgrowth by boosting proliferation, using MET-inducible mesenchymal breast cancer cells. Surprisingly, we found that crowding inhibition of proliferation persists both before and after MET, with mesenchymal cells exhibiting a proliferative edge through more effective escape from crowded cell islands.

Read the full summary ↓

In three-dimensional culture, MET caused a reduction in proliferation, accompanied by distinct changes in proliferative signalling of focal adhesions and actomyosin. However, Src inhibition led to enhanced proliferation upon MET. Furthermore, co-culture experiments with peripheral blood mononuclear cells reveal that MET-induced spheroids demonstrate an increased ability to evade immune cell attacks. This effect is likely mediated by the confined epithelial morphology and alterations in the expression of key immunomodulatory molecules. Together, these findings suggest that MET may contribute to secondary tumor outgrowth, not by boosting proliferation, but by enhancing survival in immune-challenging environments.

Published in

Mesenchymal-epithelial transition reduces proliferation but increases immune evasion in tumor spheroids

Dimari G, Hu Y, Frenzel A et al. · iScience 2025 · PMID 40777056 · doi:10.1016/j.isci.2025.113023

This dataset

Open GSE289535 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 GSE289535_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 PRJNA1223394 and SRA study SRP563730. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40777056) ↗

Study design

12 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 6 samples read as cases, 6 as controls.

How we read this: Read from 12 sample titles: 12 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

GSM8793784 MDA-MB-231_Control_1st_Rep
GSM8793785 MDA-MB-231_MET-induced_1st_rep
GSM8793786 MDA-MB-231_Control_2nd_Rep
GSM8793787 MDA-MB-231_MET-induced_2nd_Rep
GSM8793788 MDA-MB-231_Control_3rd_Rep
GSM8793789 MDA-MB-231_MET-induced_3rd_Rep
GSM8793790 ES-2_Control_1st_Rep
GSM8793791 ES-2_MET-induced_1st_rep
GSM8793792 ES-2_Control_2nd_Rep
GSM8793793 ES-2_MET-induced_2nd_Rep
GSM8793794 ES-2_Control_3rd_Rep
GSM8793795 ES-2_MET-induced_3rd_Rep

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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.