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The effect of Ndufa5 expression on bystander cells cultured in conditioned media of chemotherapy-induced senescent cells

GSE305033 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/08/13 Platform GPL21103
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)
Cellular senescence has been shown to contribute to deliterious cancer phenotyores through modulation of the tumor microenvironment through the senescence assosciated sectretome (SAS). Senescence is induced in ovarian cancer by chemotherapy. We found that bystander cells exposed to the SAS from chemotherapy indiuced cells weakens adhesion and and promotes dissemination.
Read the full summary ↓
We further identified expression of the complex I subunit Ndufa5 is required for this process. Understanding how the SAS modulates gene expression downstream of Ndufa5 expression is important to linking complex I activity to adhesion and may lead to novel targets to exploit to increase chemotherapeutic efficacy.
This dataset
Open GSE305033 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 GSE305033_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 PRJNA1304261 and SRA study SRP608225. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
shControl_PCM ×3 shNdufa5_1_PCM ×3 shNdufa5_2_PCM ×3 shControl_SCM ×3 shNdufa5_1_SCM ×3 shNdufa5_2_SCM ×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

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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.