A transcriptomic biomarker predictive of cell proliferation for use in adverse outcome pathway-informed testing and assessment.
Cell proliferation
DNA damage
Estrogen receptor α
Gene expression biomarkers
Gene expression compendium
Hepatocarcinogens
Journal
Toxicological sciences : an official journal of the Society of Toxicology
ISSN: 1096-0929
Titre abrégé: Toxicol Sci
Pays: United States
ID NLM: 9805461
Informations de publication
Date de publication:
13 Aug 2024
13 Aug 2024
Historique:
medline:
13
8
2024
pubmed:
13
8
2024
entrez:
13
8
2024
Statut:
aheadofprint
Résumé
High-throughput transcriptomics (HTTr) is increasingly being used to identify molecular targets of chemicals that can be linked to adverse outcomes. Cell proliferation is an important key event in chemical carcinogenesis. Here, we describe the construction and characterization of a gene expression biomarker that is predictive of the cell proliferation (CP) status in human and rodent tissues. The biomarker was constructed from 30 genes known to be increased in expression in prostate cancers relative to surrounding tissues and in cycling human MCF-7 cells after estrogen receptor (ER) agonist exposure. Using a large compendium of gene expression profiles to test utility, the biomarker could identify increases in cell proliferation in 1) 367 tumor vs. normal surrounding tissue comparisons from 6 human organs, 2) MCF-7 cells after activation of ER, 3) after partial hepatectomy in mice and rats, and 4) the livers of mice after exposure to nongenotoxic hepatocarcinogens. The biomarker identified suppression of CP 1) under conditions of p53 activation by DNA damaging agents in human cells, 2) in human A549 lung cells exposed to therapeutic anticancer kinase inhibitors (dasatinib, nilotnib) and 3) in the mouse liver when comparing high levels of CP at birth to the low background levels in the adult. The responses using the biomarker were similar to those observed using conventional markers of CP including PCNA, Ki67, and BrdU labeling. The CP biomarker will be a useful tool for interpretation of HTTr data streams to identify cell proliferation status after exposure to chemicals in human cells or in rodent tissues.
Identifiants
pubmed: 39137154
pii: 7732924
doi: 10.1093/toxsci/kfae102
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Published by Oxford University Press 2024.