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Expression profiling by high-throughput sequencing to evaluate effects of aroylated phenylenediamine HO53 on transcriptome in human undifferentiated bronchial epithelial cells (BCi-NS1.1 cell line).

GSE201157 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/04/20 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × m_Ctrl-24h vs 3 × m_HO53-4H vs 3 × m_HO53-8H vs 3 × m_HO53-24HGroups 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)
We used RNA sequencing to exploit molecular mechanisms behind HO53-induced innate immune responses in undifferentiated human bronchial epithelial cells (BCi-NS1.1 cell line). We performed transcriptome analysis of undifferentiated bronchial epithelial cells (BCi-NS1.1 cell line) treated with aroylated phenylenediamine HO53 for different time points 4 h, 8 h and 24 h and compared it to transcriptome of untreated cells.
Read the full summary ↓
The broad effect of HO53 on the gene expression in undifferentiated human lung epithelial cells (BCi-NS1.1) points towards an epigenetic event. Furthermore, genes involved in metabolic pathways (glycolysis, TCA cycles, pentose phosphate, glycosylation and gluconeogenesis) were particularly affected by HO53 treatement. The expression pattern for few relevant selected genes was reconfirmed by qRT-PCR using SYBR Green reagent.
This dataset
Open GSE201157 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 GSE201157_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 PRJNA828558 and SRA study SRP371344. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × m_Ctrl-24h vs 3 × m_HO53-4H vs 3 × m_HO53-8H vs 3 × m_HO53-24H

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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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.