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Endogenous production of nitric oxide by iNOS in human cells restricts inflammatory activation and cholesterol/fatty acid biosynthesis

GSE280802 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2025/11/07 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 16 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
16 samples: 4 × A549 cells, 1400W treated, vs 4 × A549 cells, cytokine treated, vs 4 × A549 cells, cytokine+1400W treated, vs 4 × A549 cells, untreated,Groups 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)
Nitric oxide (NO) is a bioactive gas that is known to control many physiological processes. In human parenchymal cells, the function of iNOS-derived NO is incompletely understood. Here, we used RNA-seq to examine the role of iNOS-derived NO in the control of gene expression in a human lung epithelial cell line treated with inflammatory cytokines.
Read the full summary ↓
iNOS-derived NO restricted the expression of genes involved in immune signaling, including the immune-related genes CXCL9 and E-selectin that were not previously known to be inhibited by iNOS. We also determined that iNOS-derived NO inhibits the expression of genes needed for cholesterol/fatty acid biosynthesis in response to cytokine stimulation, a process not previously known to be affected by NO. These findings establish the regulation of immune activation and cholesterol/fatty acid biosynthesis as main functions of iNOS in human parenchymal cells.
This dataset
Open GSE280802 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 GSE280802_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 PRJNA1180565 and SRA study SRP542402. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
4 × A549 cells, 1400W treated, vs 4 × A549 cells, cytokine treated, vs 4 × A549 cells, cytokine+1400W treated, vs 4 × A549 cells, untreated,

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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.