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Comparative toxicogenomic profiling of human epithelial cell lines exposed to hazardous chemicals

GSE336490 Homo sapiens (human) RNA-seq (gene expression) 120 samples Submitted 2026/07/01 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 120 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
120 samples: 40 conditions, mostly in triplicateGroups 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)
Human exposure to chemically diverse hazardous substances has increased the need for human-relevant models for toxicity assessment. In this study, we performed bulk RNA sequencing of four human epithelial cell lines representing major exposure-relevant tissues: HIEC-6 intestinal epithelial cells, HL7702 hepatic epithelial cells, BEAS-2B bronchial epithelial cells, and HaCaT keratinocytes.
Read the full summary ↓
Cells were exposed to nine hazardous chemicals, including DBP, DINCH, BPA, BPS, PFOA, PFTeDA, DEHP, NiCl2, and AlCl3, at cell line-specific IC01 concentrations, with vehicle controls included for each cell line. Biological triplicates were generated for all conditions, resulting in 120 samples. Comparative transcriptomic analysis was used to evaluate shared and cell line-dependent responses to hazardous chemical exposure. The dataset provides a toxicogenomic resource for investigating chemical-induced molecular perturbations across human epithelial models.
This dataset
Open GSE336490 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 GSE336490_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 PRJNA1481701 and SRA study SRP712350. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
40 conditions, mostly in triplicate
HIEC6 cells, control ×3 HIEC6 cells, AlCl3 ×3 HIEC6 cells, BPA ×3 HIEC6 cells, BPS ×3 HIEC6 cells, DBP ×3 HIEC6 cells, DEHP ×3 HIEC6 cells, DINCH ×3 HIEC6 cells, NiCl2 ×3 +32 more

Supports a between-group comparison across 120 samples.

How we read this: 40 replicated groups read from 120 sample titles; they account for 120 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

+ 80 more — browse all 120 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.