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Charting the regulatory landscape of TP53 on transposable elements in cancer [RNA-seq]

GSE262053 Homo sapiens (human) RNA-seq (gene expression) 72 samples Submitted 2024/10/20 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 72 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
72 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.
Paper
Charting the regulatory landscape of TP53 on transposable elements in cancerGenome research · 2025
Summary (written by the submitters)
The relationship between p53 and transposable elements (TEs) has been obscure. Thus, comprehensive profiling of TE-derived transcripts dynamics under the regulation of p53 provides valuable resources for more clarity in p53’s roles in cancer. In this study, we created three cancer cell lines with p53 genetic status as the only variable and combined long-read RNA-seq and short-read RNA-seq to define TE and TE-derived transcripts’ regulatory dynamics.
Read the full summary ↓
We identified in total 2,503 transcripts that use TE as potential promoters, among which, 141 to 210 are activated by p53. We found ERVs to be a main driver of potential promoters, followed by LINEs. Epigenomic profiling including chromatin accessibility and DNA methylation provided additional support for active promoter potential for p53 upregulated TE-derived transcripts. Short-term restoration of p53 partially recovered chronic p53-regulated TE-derived transcript profile but gain of function TP53 mutations, R175H and R273H, did not show evidence to act via TE network. Overall, we provide a controlled isogenic cancer cell line system with TP53 mutation status as the only genetic variable, deliver a high confidence TE and TE-derived transcript atlas and comprehensively identify active TE promoters that are direct and indirect targets of p53.
Published in
Charting the regulatory landscape of TP53 on transposable elements in cancer
Qu X, Liang Y, McCornack C et al. · Genome research 2025 · PMID 40360186 · doi:10.1101/gr.279398.124
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 GSE262053_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 PRJNA1090101 and SRA study SRP496723. Searching any of these in the dataset finder brings you back here.

Samples in this study

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