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Chronic PFOA and PFOS Exposure Triggers Cellular Oxidative Stress and Alters Lipid Levels as Revealed through Multi-omics Analysis

GSE320486 Homo sapiens (human) RNA-seq (gene expression) 27 samples Submitted 2026/02/26 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 27 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
27 samples: 27 samples, each with a distinct title — no replicated groupsGroups 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
Chronic PFOA and PFOS exposure triggers cellular oxidative stress and alters lipid levels as revealed through multi-omics analysisEnvironmental science. Advances · 2026
Summary (written by the submitters)
Per- and polyfluoroalkyl substances (PFAS), or "forever chemicals," are linked to metabolic, immune, and neurotoxic disorders, yet their long-term cellular effects remain unclear. Using a 24-week chronic exposure model with non-transformed human epithelial cells, we examined responses to low, environmentally relevant concentrations of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS).
Read the full summary ↓
Integrated transcriptomic and lipidomic analyses revealed that despite minimal cellular accumulation, molecular changes emerged around week 17, marked by transcriptional signatures indicative of oxidative stress responses, cell survival pathways, and lipid metabolism. Our data suggests a multi-faceted model in which long-term PFOA and PFOS exposure induces oxidative stress mediated by SESN2 and SOD3 , increases lipid biosynthesis via SREBP pathway, and causes compound-specific disruptions of membrane lipids. These findings highlight the importance of multi-omic, time-resolved approaches in uncovering the mechanisms of chronic low-dose chemical exposure and provide a foundation for future in vivo studies.
Published in
Chronic PFOA and PFOS exposure triggers cellular oxidative stress and alters lipid levels as revealed through multi-omics analysis
Paddayuman JZ, Cristobal JR, Landau LJB et al. · Environmental science. Advances 2026 · PMID 41777558 · doi:10.1039/d5va00353a
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 GSE320486_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 PRJNA1425030 and SRA study SRP678124. Searching any of these in the dataset finder brings you back here.

Study design
27 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 27 sample titles: 27 distinct titles with little repetition. 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.