Many compounds that cause DNA damage and related perturbations share common features in their structure and biochemical effects, and these parameters can be used to help categorize agents by mechanisms of action. From the view of bond force and structure, interactions between a compound and DNA can be either covalent or non-covalent. A covalent interaction is irreversible, although there are some exceptions. In addition, covalent bulky adducts can cause

DNA backbone distortion, which in turn can affect both transcription and replication, such as by disrupting protein complex recruitment. Interactions between DNA and non-covalent agents are through van der Waals forces, hydrogen bonding, hydrophobic, and/or charge transfer forces and as such are reversible. Noncovalent agents can be classified into groove binding agents and DNA intercalators. Both general types of interactions lead to genetic changes such as stalled replication, cell cycle delays, cytotoxicity, mutations, and consequent genomic instability that can contribute to cancer development. Thus, genotoxicity testing has become a crucial component of safety evaluation for new drugs and chemicals. Compared to 2-year animal carcinogenicity trials, the genotoxicity testing battery provides sensitive, relatively simple, fast and economical tools for detection of genetic damage. Since its conception in 1970s, the genotoxicity battery has effectively assured genetic safety of consumer chemicals and/or drugs. However, it has been pointed out that the current testing paradigm features relatively low specificity for predicting carcinogenicity, particularly in case of in vitro mammalian mutation and/or chromosome damage assays. Thus, the interpretation and risk assessment of positive findings in the in vitro mammalian mutation and/or chromosome damage assays is a major challenge to both industry and regulatory agencies.

Historically, transcriptional activation has been utilized in the development of a variety of molecular toxicology assays. For instance, transcriptional activation of the SOS pathway in bacteria and RAD54 pathway in yeast has been used to monitor for genotoxicity using single-gene promoter–reporter assay systems. In mammalian cells, discovery of the gadd and other stress-genes, and an appreciation of the central role for p53 in many DNA damage response pathways and cancer development provided the foundation for development of pre-genomic approaches for detection of genotoxicity in mammalian cells. Therefore, application of broad mechanisms-based scientific approaches such as “–omic” methodology might be advantageous for providing insights into the multifaceted nature of toxic mechanisms of new drugs and chemicals.

Agilent Certified Service Provider Program

Our toxicogenomics facility has extensive experience in stress signaling, injury responses, and development of biomarkers based on gene expression. A major focus is delineation of transcriptomic responses to genotoxic stress as well as to a variety of other classes of toxic agents with environmental and/or pharmacologic importance. We also have advanced data analysis and bioinformatic capabilities for integrating omics results into systems biology and systems medicine.

We are certified in Agilent single color expression microarray analysis and also have in-depth experience with 2-color microarrays. Our staff has had rigorous training and expertise in transcriptomics, and all assays are carried out under strict quality control. Contract service is available for wide-ranging applications in molecular toxicology and cancer research.



Li HH, Chen R, Hyduke DR, Williams A, Frötschl R, Ellinger-Ziegelbauer H, O'Lone R, Yauk CL, Aubrecht J, Fornace AJ Jr. Development and validation of a high-throughput transcriptomic biomarker to address 21st century genetic toxicology needs. Proc Natl Acad Sci U S A. 2017 Dec 19;114(51):E10881-E10889. doi: 10.1073/pnas.1714109114. Epub 2017 Dec 4. PubMed PMID: 29203651; PubMed Central PMCID: PMC5754797.

Buick JK, Williams A, Kuo B, Wills JW, Swartz CD, Recio L, Li HH, Fornace AJ Jr., Aubrecht J, Yauk CL. Integration of the TGx-28.65 genomic biomarker with the flow cytometry micronucleus test to assess the genotoxicity of disperse orange and 1,2,4-benzenetriol in human TK6 cells. Mutat Res. 2017 Dec;806:51-62. doi: 10.1016/j.mrfmmm.2017.09.002. Epub 2017 Sep 13. PubMed PMID: 29017062.


Yauk CL, Buick JK, Williams A, Swartz CD, Recio L, Li HH, Fornace AJ Jr, Thomson EM, Aubrecht J. Application of the TGx-28.65 transcriptomic biomarker to classify genotoxic and non-genotoxic chemicals in human TK6 cells in the presence of rat liver S9. Environ Mol Mutagen. 2016 May;57(4):243-60. doi: 10.1002/em.22004. Epub 2016 Mar 4. PubMed PMID: 26946220; PubMed Central PMCID: PMC5021161.


Williams A, Buick JK, Moffat I, Swartz CD, Recio L, Hyduke DR, Li HH, Fornace AJ Jr, Aubrecht J, Yauk CL. A predictive toxicogenomics signature to classify genotoxic versus non-genotoxic chemicals in human TK6 cells. Data Brief. 2015 Aug 24;5:77-83. doi: 10.1016/j.dib.2015.08.013. eCollection 2015 Dec. PubMed PMID: 26425668; PubMed Central PMCID: PMC4564388.

Bouhifd M, Andersen ME, Baghdikian C, Boekelheide K, Crofton KM, Fornace AJ Jr, Kleensang A, Li H, Livi C, Maertens A, McMullen PD, Rosenberg M, Thomas R, Vantangoli M, Yager JD, Zhao L, Hartung T. The human toxome project. ALTEX. 2015;32(2):112-24. doi: 10.14573/altex.1502091. Epub 2015 Mar 4. PubMed PMID: 25742299; PubMed Central PMCID: PMC4778566.

Buick JK, Moffat I, Williams A, Swartz CD, Recio L, Hyduke DR, Li HH, Fornace AJ Jr, Aubrecht J, Yauk CL. Integration of metabolic activation with a predictive toxicogenomics signature to classify genotoxic versus nongenotoxic chemicals in human TK6 cells. Environ Mol Mutagen. 2015 Jul;56(6):520-34. doi: 10.1002/em.21940. Epub 2015 Mar 2. PubMed PMID: 25733247; PubMed Central PMCID: PMC4506226.

Li HH, Hyduke DR, Chen R, Heard P, Yauk CL, Aubrecht J, Fornace AJ Jr. Development of a toxicogenomics signature for genotoxicity using a dose-optimization and informatics strategy in human cells. Environ Mol Mutagen. 2015 Jul;56(6):505-19. doi: 10.1002/em.21941. Epub 2015 Mar 2. PubMed PMID: 25733355; PubMed Central PMCID: PMC4506269.


Li, H-H.*, Tyburski, J.B., Wang, Y-W., Strawn, S., Moon, B-H., Kallakury, B.B. V. S., Gonzalez, F., and Fornace, A. J.. "Modulation of fatty acid and bile acid metabolism by PPARa protects against alcoholic liver disease." Alcoholism: Clinical and Experimental Research 38.6 (2014): 1520-31.


Li, H-H., Doiron, K., Patterson, A. D., Gonzalez, F. J., & Fornace Jr, A. J.. "Identification of serum insulin-like growth factor binding protein 1 as diagnostic biomarker for early-stage alcohol-induced liver disease." Journal of Translational Medicine 11.1 (2013): 266.


Goodsaid, F. M., Amur, S., Aubrecht, J., Burczynski, M. E., Carl, K., Catalano, J., Charlab, R., Close, S., CornuArtis, C., Essioux, L., Fornace, A. J., Hinman, L., Hong, H., Hunt, I., Jacobson-Kram, . "Voluntary exploratory data submissions to the US FDA and the EMA: experience and impact." Nature Reviews. Drug Discovery 9.6 (2010): 435-45.


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