← BioTransfer GEO Dataset Finder
GEO series

Isoliensinine promotes the clearance of senescent vascular smooth muscle cells by natural killer cells [MOVAS]

GSE318401 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/02/07 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 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
Mus musculus (mouse)
Samples
18 samples: 6 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.
Summary (written by the submitters)
Atherosclerosis (AS) is an age-related disease whose incidence increases with advancing age. During disease pathogenesis, vascular smooth muscle cells (VSMCs) undergo senescence within the plaques and secrete senescence-associated secretory phenotype (SASP) factors, which contributes to the development and destabilization of atherosclerotic plaques.
Read the full summary ↓
As key effector cells of the innate immune system, natural killer (NK) cells can specifically recognize and eliminate senescent cells; however, their role in inhibiting AS progression and the underlying mechanisms remain unclear. Isoliensinine (IsoL) is a bisbenzylisoquinoline alkaloid extracted from lotus plumule, which exerts anti-inflammatory and immunomodulatory effects. Studies have shown that IsoL can effectively enhance the immune clearance of tumor cells by NK cells, suggesting that this compound may also have the potential to inhibit AS progression by regulating the recognition and elimination of abnormal target cells by immune cells.
This dataset
Open GSE318401 in finder → Find more mouse 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 GSE318401_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 PRJNA1418687 and SRA study SRP674609. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
B_I ×3 Blank ×3 H_I ×3 H2O ×3 D_I ×3 Dox ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.