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RNA-Seq analysis of cancer models with altered SLX4/XPF reveals links to migration, DNA damage response, EMT, and drug sensitivity

GSE309364 Homo sapiens (human) RNA-seq (gene expression) 60 samples Submitted 2025/10/01 Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 60 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
60 samples
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)
SLX4 and XPF are two proteins involved in DNA repair mechanisms, but for which other properties are possible. After a study on phenotypes of cell models with various expressions of the two proteins, we conducted RNA sequencing analysis on five cell models of different origin (A549, NCI-H1703, COLO-357, HT-29 and HEK-293T). Our results show a much higher transcriptional impact on p53 mutant cell lines than on p53 wild type cells.
Read the full summary ↓
We also present various signatures or scores based on selected genes, and although interesting differences are observed, no general conclusions can be made for all cell lines. Our study and results add data and knowledge to the roles of SLX4 and XPF in cell biology and represent an important background for new and confirmational studies.
This dataset
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.

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 GSE309364_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1335242 and SRA study SRP628321. Searching any of these in the dataset finder brings you back here.

Samples in this study

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