Tris(2-chloroethyl) Phosphate (TCEP) Elicits Hepatotoxicity by Activating Human Cancer Pathway Genes in HepG2 Cells.
Abdullah M Al-SalemQuaiser SaquibMaqsood A SiddiquiJaved AhmadAbdulaziz A Al-KhedhairyPublished in: Toxics (2020)
Tris(2-chloroethyl) phosphate (TCEP) is one of the organophosphorus flame retardants (OPFRs) used in consumer commodities and have been detected in human body fluids. Research on TCEP-induced transcriptomic alterations and toxicological consequences in liver cells is still lacking. Herein, human hepatocellular (HepG2) cells were treated with 100, 200, and 400 μM TCEP for 3 days to quantify hepatotoxicity by MTT, NRU, and comet assays. Apoptosis, mitochondrial membrane potential (ΔΨm), oxidative stress, and Ca2+ influx were measured by flow cytometry. A qPCR array was employed for transcriptomic analysis. MTT and NRU data showed 70.92% and 75.57% reduction in cell survival at 400 μM. In addition, 20-fold greater DNA damage was recorded at 400 μM. Cell cycle data showed 65.96% subG1 apoptotic peak in 400 μM treated cells. An elevated level of oxidative stress, esterase, Ca2+ influx, and ΔΨm dysfunction were recorded in TCEP-treated cells. Out of 84 genes, the qPCR array showed upregulation of 17 genes and downregulation of 10 key genes belonging to human cancer pathways. Our study endorses the fact that TCEP possesses hepatotoxic potential at higher concentrations and prolonged exposure. Hence, TCEP may act as a cancer-inducing entity by provoking the gene network of human cancer pathways.
Keyphrases
- oxidative stress
- endothelial cells
- induced apoptosis
- dna damage
- cell cycle
- cell cycle arrest
- genome wide
- induced pluripotent stem cells
- cell proliferation
- pluripotent stem cells
- cell death
- flow cytometry
- signaling pathway
- squamous cell
- healthcare
- single cell
- pi k akt
- dna methylation
- high resolution
- mass spectrometry
- climate change
- risk assessment
- big data
- machine learning
- drug induced
- social media
- data analysis
- rna seq
- copy number
- artificial intelligence
- deep learning
- heat shock
- network analysis