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Nuclear translocation of TfR1 facilitating tumor progression via p53-mediated gene regulation [Cut&Tag]

GSE271110 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 30 samples Submitted 2024/12/27 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 30 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
30 samples: 10 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)
It is well-known that p53-mediated gene regulation exerts a profound impact on the occurrence, progression, metastasis, and various other facets of tumor. Wherein, activation of p53 downstream DNA damage repair-related genes is able to promote the survival of cancer cells during tumor progression.Notably, it has been substantiated that the transcriptional activity of p53 could be modulated by interactions with other proteins.Therefore, we asked whether the interaction with TfR1 was relevant to the transcriptional regulation of p53 target genes.
Read the full summary ↓
Our results support the positive regulation of nuclear TfR1 on DNA damage repair-related genes, especially for the NER pathway.
This dataset
Open GSE271110 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE271110_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1129876 and SRA study SRP517035. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 conditions, mostly in triplicate
HCT-116-TfR1 ×3 HCT-116-p53 ×3 HCT-116-rIgG ×3 HCT-116-mIgG ×3 shscr-TfR1 ×3 shscr-rIgG ×3 shTP53-TfR1 ×3 shTP53-rIgG ×3 +2 more

Supports a between-group comparison across 30 samples.

How we read this: 10 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
Datasets on a similar topic

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