Education:

B.S., Biology, Slippery Rock University of Pennsylvania, 1990
B.A., Philosophy, Slippery Rock University of Pennsylvania, 1990
Ph.D., Environmental and Occupational Health, University of Pittsburgh, 1998

Curriculum Vitae

Current Positions:

Associate Professor, Department of Medicine, University of Louisville School of Medicine
Member, James Graham Brown Cancer Center
Member, Institute for Molecular Diversity and Drug Design, University of Louisville
Associate Member, Department of Pharmacology and Toxicology, University of Louisville School of Medicine

Contact Information:

Clinical Translational Research Building, Room 222
University of Louisville
505 S. Hancock St.
Louisville, KY 40202, USA
Office 502-852-3346
Cell 502-794-5006
Fax 502-852-7979
Email: al.cunningham@louisville.edu

Research Description

Our individual and public health and the well-being of our economy are dependent upon the extraordinary properties of chemicals.  However, while many synthetic and natural chemicals have been beneficial to society, some have proven to be harmful to humans and the environment. 

From a toxicological point-of-view, the majority of chemicals in use today only have basic toxicological information associated with them and only a few have been studied adequately for their involvement in complex human and environmental health concerns such as cancer, birth defects, and ecosystem damage.  Due to time and cost constraints, accepted methods of toxicity testing cannot adequately assess the existing tens of thousands of chemicals for adverse human and environmental effects. 

From a pharmacological point-of-view, many chemicals have therapeutic activity but also have deleterious activity.  The identification of novel compounds and the subsequent synthesis of many analogs is often required to maximize efficacy and minimize toxicity.  However, in many instances even though the therapeutic target is known, the toxicological targets are not.  Thus, even at the cost of excessive safety testing, the toxic effects of some drugs are only realized after widespread use.

To address these points, the Cunningham lab continues to explore the toxicological and pharmacological activity of chemicals through computational structure-activity relationship (SAR) modeling.  Specifically, our lab has focused on chemical carcinogenesis, breast cancer, endocrine disrupting chemicals, and anticancer agents. 

Recent work entails the development of predictive and mechanistic models for chemicals that may induce cancer but are not directly damaging to DNA.  These are a particularly difficult class of carcinogens to identify since they likely do not attack a specific or unique target and therefore are not amicable to most standardized assays for carcinogen determination. 

Alternately, for carcinogens that do damage DNA, while this is a significant hallmark for carcinogens, we understand that DNA alone is often not sufficient to result cancer formation.  To address this problem, our lab is developing models based on carcinogen-protein interactions for site selective carcinogens with the intent of identifying new molecular targets associated with cancer.  Ultimately, while these targets may be useful for identifying unbeknownst carcinogens, it is envisioned that they may have a more significant role as targets for anticancer drug development.

Finally, the decades of large scale testing of chemicals for carcinogen determination has resulted in an important and overlooked result.  A significant number of chemicals, when tested for carcinogenicity, actually reduce the number of spontaneous cancers that might otherwise develop in the test animals.  These chemicals, therefore, have “anticancer” activity.  Since these chemicals were not intended as anticancer drugs but for use as industrial or commercial products, their potential anticancer activity is accompanied by significant toxicity.  For these agents, our goal is first to identify and separate the chemical aspects of anticancer activity from toxicity, and then develop a model that is capable of identifying new chemicals with anticancer activity but without significant toxicity.

Representative Publicatoins:

Modeling and Analysis of Environmental Carcinogens

Carrasquer CA, Batey K, Qamar S, Cunnigham SL, Cunningham AR.  Structure-activity relationship models for rat carcinogenesis and assessing the role mutagens play in model predictivity.  SAR & QSAR in Environmental Research 2014;25(6):489-506.  PMID: 24697549; PMCID: PMC4830131.

Rosenkranz HS, Cunningham SL, Mermelstein R, Cunningham AR.  The challenge of testing chemicals for potential carcinogenicity using multiple short term assays. An analysis of a proposed test battery for hair dyes.  Mutation Research/Genetic Toxicology and Environmental Mutagenesis 2007 Sep 1;633(1):55-66. PMID: 17625954.

Pollack N, Cunningham AR, Rosenkranz HS.  Environmental persistence of chemicals and their carcinogenic risks to humans. Mutation Research 2003 Jul 25;528(1-2):81-91.  Review. PMID: 12873726.

Modeling Organ/Tissue-Selective Carcinogens

Carrasquer CA, Malik N, States G, Qamar S, Cunningham SL, Cunningham AR.  Chemical structure determines target organ carcinogenesis in rats.  SAR & QSAR in Environmental Research 2012 Oct;23(7-8):775-95. PMID: 23066888; PMCID: PMC3547623.

Cunningham AR, Moss ST, Iype SA, Qian G, Qamar S, Cunningham SL.  Structure-activity relationship analysis of rat mammary carcinogens.  Chemical Research in Toxicology 2008 Oct;21(10):1970-82. PMID: 18759503.

Receptor-Based Structure-Activity Relationship Modeling

Cunningham AR, Carrasquer CA, Qamar S, Maguire JM, Cunningham SL, Trent JO.  Global structure-activity relationship model for non-mutagenic carcinogens using virtual ligand protein interactions as model descriptors. Carcinogenesis 2012 Oct;33(10):1940-45. doi: 10.1093/carcin/bgs197(10). PMID: 22678118; PMCID: PMC3463155.

Cunningham AR, Qamar S, Carrasquer CA, Holt PA, Maguire JM, Cunningham SL, Trent JO.  Mammary carcinogen-protein binding potentials:  Novel and biologically relevant structure-activity relationship model descriptors.  SAR & QSAR in Environmental Research 2010 Jul;21(5-6):463-79. PMID: 20818582; PMCID: PMC3383027.

Modeling Environmental Estrogens

Schultz DJ, Wickramasinghe NS, Ivanova MM, Isaacs SM, Dougherty SM, Imbert-Fernandez Y, Cunningham AR, Chen C, Klinge CM.  Anacardic acid inhibits estrogen receptor α–DNA binding and reduces target gene transcription and breast cancer cell proliferation.  Molecular Cancer Therapeutics 2010 Mar;9(3):594-605. PMID: 20197399; PMCID: PMC2837512.

Cunningham AR, Consoer DM, Iype SA, Cunningham SL.  A structure-activity relationship analysis for the identification of environmental estrogens:  The categorical-SAR (cat-SAR) approach.  In: Endocrine Disruption Modeling, J. Devillers, Editor. CRC Press, 2009, p. 173-98.

Cunningham AR, Cunningham SL, Rosenkranz HR.  Structure activity approach to the identification of environmental estrogens: The MCASE approach.  SAR & QSAR in Environmental Research 2004 Feb;15(1):55-67. PMID: 15113069.  

Modeling Differential Toxicity to Cancer Cell Lines

Qamar S, Carrasquer CA, Cunningham SL, Cunningham AR.  Anticancer SAR models for MCF-7 and MDA-MB-231 breast cell lines.  Anticancer Research 2011;10:3247-52.

Cunningham AR, Cunningham SL, Day BW.  Identification of structural components associated with cytostatic activity in MCF-7 but not in MDA-MB-231 cells.  Bioorganic & Medicinal Chemistry 2003 Nov 17;11(23):5249-58. PMID: 14604689.

PubMed Information