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Effect of ferrostatin-1 and liproxstatin-1 during TNF-induced HT-29 cells apoptosis

GSE248867 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2024/06/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 14 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
14 samples: 6 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.
Summary (written by the submitters)
Ulcerative colitis (UC) is an inflammatory disease characterized by an uncontrolled inflammatory response. Previous study showed that the immunological impairment elicted the alteration of inflammatory mediators, and ferroptosis was implicated with the lethal accumulation of reactive oxygen species (ROS).We have already found that lipid ROS level was elevated in both murine DSS colitis model and TNF-a-induced cell apoptosis model in vitro.Then we here use two ferroptosis
Read the full summary ↓
inhibitors ferrostatin-1 and liproxstatin-1 trying to eliminate lipid ROS in order to relive the symptoms of colitis.But we strikingly notice that liproxstatin-1 could increase TNF-induced cell apoptosis instead of protecting cells from death as we expected before while the other inhibitor ferrostatin-1 could protect cells from death indeed.To evaluate the underlying mechanism, we performed the experiment using high-throughput sequencing and get data to explain the reason why liproxstatin-1 could increase TNF-induced cell apoptosis .
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 GSE248867_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 PRJNA1046138 and SRA study SRP474778. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in duplicate
HT-29 cells,control, ×3 HT-29 cells,TNF-a+20umferrostatin-1, ×3 HT-29 cells,control+20um ferrostatin-1, ×2 HT-29 cells,control+20umliproxstatin-1, ×2 HT-29 cells,TNF-a, ×2 HT-29 cells,TNF-a+20umliproxstatin-1, ×2

Supports a between-group comparison across 14 samples.

How we read this: 6 replicated groups read from 14 sample titles; they account for 14 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
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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.