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Effect of long-term abemaiclicb and deletion of TP53 on gene expression in MCF7 cells

GSE248294 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2024/08/31 Platform GPL21290
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 12 conditions, mostly in duplicateGroups 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.
Paper
Long-term breast cancer response to CDK4/6 inhibition defined by TP53-mediated geroconversionCancer cell · 2024
Summary (written by the submitters)
CDK4/6 inhibitor, abemaciclib induced cell cycle arrest and senescence in breast cancer. We reported that deletion of TP53 prevented the senescence features. In this study, we knockout TP53 by CRISPR Cas9 system and treated MCF7 cells and p53 knockout cells with abemaciclib for up to 29 days to identify the difference of senescence associated secretary phenotype genes and cell cycle related genes. features.
Published in
Long-term breast cancer response to CDK4/6 inhibition defined by TP53-mediated geroconversion
Kudo R, Safonov A, Jones C et al. · Cancer cell 2024 · PMID 39393354 · doi:10.1016/j.ccell.2024.09.009
This dataset
Open GSE248294 in finder → Find more human 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 GSE248294_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 PRJNA1043175 and SRA study SRP473072. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39393354) ↗
Study design
12 conditions, mostly in duplicate
MCF7 parental, Day 0 ×2 MCF7 parental, Day 1 ×2 MCF7 parental, Day 3 ×2 MCF7 parental, Day 5 ×2 MCF7 parental, Day 21 ×2 MCF7 parental, Day 29 ×2 p53KO, Day 0 ×2 p53KO, Day 1 ×2 +4 more

Supports a between-group comparison across 24 samples.

How we read this: 12 replicated groups read from 24 sample titles; they account for 24 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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