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Role of plasma extracellular vesicles in lung cancer pre-metastatic niche formation

GSE302138 Homo sapiens (human) RNA-seq (gene expression) 35 samples Submitted 2026/07/15 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 35 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
35 samples: 7 conditions, mostly with about 5 replicates eachGroups 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
Circulating extracellular vesicles from early-stage lung cancer patients trigger endothelial activation to drive pre-metastatic niche formation through synergistic miR-29a and C4A signalingJournal of experimental & clinical cancer research : CR · 2026
Summary (written by the submitters)
Lung cancer is the deadliest cancer worldwide, primarily due to metastatic spread. Tumor-derived extracellular vesicles (EVs) play a crucial role in the formation of pre-metastatic niches (pMNs), facilitating the spread and expansion of circulating cancer cells. So far, little is known about the role of plasma EVs in lung cancer pMN formation.
Read the full summary ↓
We aim to elucidate the EV role in pMN formation and identify new prognostic biomarkers for early-stage lung cancer.Plasma-derived EVs were obtained by ultracentrifugation from early-stage lung cancer patients who survived at 5 years (ESA-EVs) and patients who died within two years (ESD-EVs). Heavy-smokers cancer free individuals were used as control (HS-EVs). Functional in vitro experiments on endothelial cells were carried out using 15ug of EVs from different groups for 48h. We observed that ESD-EVs significantly induced a “pro-inflammatory” endothelial phenotype. Characterization of ESD-EV revealed higher levels of miR-29 and C4a compared to ESA and HS-EVs. Concomitant miR-29 transfection and C4a administration in endothelial cells recapitulated the pro-inflammatory activation observed with EVs. In conclusion, we showed that plasma EVs could drive lung pMN formation, conferring a pro-inflammatory phenotype to endothelial cells to favour metastasis outgrowth
Published in
Circulating extracellular vesicles from early-stage lung cancer patients trigger endothelial activation to drive pre-metastatic niche formation through synergistic miR-29a and C4A signaling
Pontis F, Ghidotti P, Ferrario N et al. · Journal of experimental & clinical cancer research : CR 2026 · PMID 42129855 · doi:10.1186/s13046-026-03732-4
This dataset
Open GSE302138 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 GSE302138_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 PRJNA1289053 and SRA study SRP599636. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42129855) ↗
Study design
7 conditions, mostly with about 5 replicates each
HUVEC_SC ×5 HUVEC_mim29 ×5 HUVEC_C4 ×5 HUVEC_C4+mim29 ×5 HUVEC_NT ×5 HUVEC_ESA ×5 HUVEC_ESD ×5

Supports a between-group comparison across 35 samples.

How we read this: 7 replicated groups read from 35 sample titles; they account for 35 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
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