A transcriptomic biomarker predictive of cell proliferation for use in adverse outcome pathway-informed testing and assessment

Author:

Corton J Christopher1ORCID,Ledbetter Victoria1,Cohen Samuel M2ORCID,Atlas Ella3ORCID,Yauk Carole L4ORCID,Liu Jie1

Affiliation:

1. Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park , NC 27711, United States

2. Department of Pathology and Microbiology and Buffett Cancer Center, University of Nebraska Medical Center , Omaha, NE 69198-3135, United States

3. Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada , Ottawa, ON K2K 0K9, Canada

4. Department of Biology, University of Ottawa , Ottawa, ON, Canada

Abstract

Abstract High-throughput transcriptomics (HTTr) is increasingly being used to identify molecular targets of chemicals that can be linked to adverse outcomes. Cell proliferation (CP) 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 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 CP in (i) 308 out of 367 tumor vs. normal surrounding tissue comparisons from 6 human organs, (ii) MCF-7 cells after activation of ER, (iii) after partial hepatectomy in mice and rats, and (iv) the livers of mice and rats after exposure to nongenotoxic hepatocarcinogens. The biomarker identified suppression of CP (i) under conditions of p53 activation by DNA damaging agents in human cells, (ii) in human A549 lung cells exposed to therapeutic anticancer kinase inhibitors (dasatinib, nilotnib), and (iii) 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 CP status after exposure to chemicals in human cells or in rodent tissues.

Publisher

Oxford University Press (OUP)

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