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Time- and Dose-Dependent Effects of Irradiation on Endothelial and Tumor Endothelial Cells: Transcriptional, Molecular, and Functional Changes Driving Activation In Vitro and In Vivo

GSE287078 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2025/06/01 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 30 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
30 samples: 6 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
Time- and Dose-Dependent Effects of Irradiation on Endothelial and Tumor Endothelial Cells: Transcriptional, Molecular, and Functional Changes Driving Activation In Vitro and In VivoCancers · 2025
Summary (written by the submitters)
Background: Irradiation (IR) targets cancer cells, but also the tumor microenvironment, including the tumor’s blood vessels. In addition to tumor endothelial cell (TEC) apoptosis, IR can lead to TEC activation, potentially increasing immune cell infiltration. However, the changes underlying the IR-induced activation of endothelial cells (ECs) are poorly understood.
Read the full summary ↓
This study investigated dose- and time-dependent molecular and functional responses of murine and human EC lines to IR in vitro and TECs in vivo in murine tumor models of colorectal carcinoma. Methods: HUVEC, EA.hy926, and Hulec5a, as well as murine bEND.3, 2H11, and SVEC4-10 EC lines, were irradiated with single doses of 2–10 Gy. EC proliferation and survival after IR were assessed by staining all nuclei (Hoechst 33342) and dead cells (propidium iodide) every 24 h for 5 days using the Cytation 1 Cell Imaging Multi-Mode Reader. RNA sequencing analysis of HUVECs irradiated with 2 Gy and 5 Gy at 24 h and 72 h after IR was conducted, focusing on processes related to EC activation. To validate the RNA sequencing results, immunofluorescence staining for proteins related to EC activation, including Stimulator of Interferon Response cGAMP Interactor 1 (STING), Nuclear factor kappa B (NF-κβ), and Vascular cell adhesion molecule 1 (VCAM-1), was performed. To validate the in vitro results, the response of TEC in vivo was analyzed using publicly available RNA sequencing data of TECs isolated from MC38 colon carcinoma irradiated with a single dose of 15 Gy. Finally, murine CT26 colon carcinoma tumors were immunofluorescently stained for STING and NF-κβ 24 and 48 h after IR with a clinically relevant fractionated regimen of 5 × 5 Gy. Results: Doses of 2, 4, 6, 8, and 10 Gy led to a dose-dependent decrease in proliferation and increased death of ECs. RNA sequencing analysis showed that the effects on the transcriptome of HUVECs were most pronounced 72 h after IR with 5 Gy, with 1014 genes (661 down-regulated and 353 up-regulated) being significantly differentially expressed. Irradiation with 5 Gy resulted in HUVEC activation, with up-regulation of the immune system and extracellular matrix genes, such as STING1 (log2FC = 0.81) and SELE (log2FC = 1.09), respectively; and down-regulation of cell cycle markers. Furthermore, IR led to the up-regulation of immune response- and extracellular matrix (ECM)-associated signaling pathways, including NF-κβ signaling and ECM–receptor interaction, which was also observed in the transcriptome of irradiated murine TECs in vivo. This was confirmed at the protein level with higher expressions of the EC activation-associated proteins STING, NF-κβ, and VCAM-1 in irradiated HUVECs and irradiated TECs in vivo. Conclusions: IR induces changes in ECs and TECs, supporting their activation in dose- and time-dependent manners, potentially contributing to the anti-tumor immune response, which may potentially increase the infiltration of immune cells into the tumor and thus, improve the overall efficacy of RT, especially in combination with immune checkpoint inhibitors.
Published in
Time- and Dose-Dependent Effects of Irradiation on Endothelial and Tumor Endothelial Cells: Transcriptional, Molecular, and Functional Changes Driving Activation In Vitro and In Vivo
Santek I, Sersa G, Markelc B · Cancers 2025 · PMID 40940937 · doi:10.3390/cancers17172842
This dataset
Open GSE287078 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 GSE287078_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 PRJNA1211095 and SRA study SRP559143. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40940937) ↗
Study design
6 conditions, mostly with about 5 replicates each
Ctrl_24h ×5 IR_2Gy_24h ×5 IR_5Gy_24h ×5 Ctrl_72h ×5 IR_2Gy_72h ×5 IR_5Gy_72h ×5

Supports a between-group comparison across 30 samples.

How we read this: 6 replicated groups read from 30 sample titles; they account for 30 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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