Toxicogenomic Approaches to Understanding Human Benzene Toxicity and Susceptibility

Toxicogenomic approaches to understanding human benzene toxicity and susceptibility

Cliona M. McHale¹, Luoping Zhang¹, Qing Lan², Reuben Thomas¹, Alan E. Hubbard¹, Roel Vermeulen³, Guilan Li⁴, Stephen M. Rappaport¹, Songnian Yin⁴, Martyn T. Smith¹, and Nathaniel Rothman².

¹School of Public Health, University of California, Berkeley, CA^{_; 2}Division of Cancer Epidemiology and Genetics, NCI, NIH, DHHS, Bethesda, MD^{_; 3}Institute of Risk assessment Sciences, Utrecht University, Utrecht, the Netherlands^{_{; and} 4}Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China

Benzene is an established cause of acute myeloid leukemia (AML) and may cause one or more lymphoid malignancies in humans. Occupational exposure to benzene, even at levels below the current U.S. occupational standard of 1 ppm, causes hematotoxicity. Toxicogenomics (e.g. genomics, transcriptomics and epigenomics) and systems biology (study of the interactions among toxicogenomic endpoints using bioinformatics) approaches in human populations, animals, and in vitromodels, exposed to a range of benzene levels, are key to understanding gene-environment interactions in benzene toxicity and can identify biomarkers of exposure, early effect and susceptibility. Through analysis of the peripheral blood mononuclear cell (PBMC) transcriptomes of 125 workers exposed to a wide range of benzene levels, we recently reported highly significant widespread perturbation of gene expression at all exposure levels, as well as alterations in acute myeloid leukemia and immune response pathways. Sequencing of the PBMC transcriptomes from a subset of the study subjects revealed additional alterations in gene expression. From preliminary epigenomic data in the human subjects, we have identified benzene-induced alterations in the DNA methylome and miRNome. Using genomic screens in yeast and human screening systems, with subsequent confirmation in human cells, we have identified potential biomarkers of susceptibility. We are developing bioinformatic methods to integrate these and future toxicogenomic datasets, in a systems biology approach, to further understand pathways of benzene toxicity and to reveal potential biomarkers associated with a range of exposures.

Supported by NIH grant P42ES04705.