Mathematical modeling to fight breast cancer
Virginia Tech researchers have developed a model that may eventually help explain and overcome drug resistance in breast cancer treatment.
MEET OUR TEAM
Cancer Systems Biology draws people from many different backgrounds. Clinical doctors, biological researchers, mathematicians, engineers, computer scientists, and physical chemists all have different skills and perspectives needed to tackle the problems involved. Working together, they have learned concepts and vocabulary from each other’s disciplines, which is critical to their success.
Our team reflects the diverse backgrounds and skills in the Cancer Systems Biology community.
Dr. Robert Clarke, head of the Lombardi Center for Cancer Systems Biology, is an internationally recognized leader in breast cancer research and leader in applying the Systems Biology approach to cancer issues. An advocate of tapping the potential of bioinformatics and mathematical modeling, he began collaborations with engineers and computer scientists for more than 15 years.
Dr. Clarke studies how hormones, growth factors, and other related molecules affect breast cancer, and how breast cancers become resistant to hormonal and cytotoxic chemotherapies. He has expertise in the fields of estrogens, antiestrogens, aromatase inhibitors, cell signaling, drug resistance, bioinformatics, and signal transduction.
Dr. Clarke has developed a series of hormone resistant breast cancer models that are widely used in the field and he continues to develop new experimental models. He is actively supporting the development of mathematical models and applying them to experimental data. He is also currently working on developing and applying genomic and novel bioinformatic methods to data from ongoing studies in both humans and experimental models. In other research, Dr. Clarke and his colleagues have recently identified a new molecular signaling network in breast cancer that involves several novel oncogenes and suppressor genes. Ultimately, this network determines if a breast cancer cell will grow, differentiate, or die, in response to therapy.
Dr. Clarke is Dean for Research at Georgetown University Medical Center and co-lead of the In Silico Research Center of Excellence. He earned a B.Sc. degree in biochemistry from the University of Ulster at Jordanstown, UK in 1980; and an M.Sc., Ph.D. and D.Sc. in biochemistry from The Queen’s University of Belfast, UK, in 1982, 1986, and 1999 respectively. He completed a postdoctoral fellowship in 1987-1988 at the National Cancer Institute of the NIH.
Dr. William Baumann comes to Cancer Systems Biology from an electrical engineering background. He is an associate professor of electrical engineering at Virginia Tech, with expertise in mathematical and computer modeling of dynamic systems. He is applying a systems approach to modeling and understanding biological systems. He and his colleagues are developing mathematical models of breast cancer cells to understand how they become resistant to therapy. Their goal is to develop a virtual computer model of human cancer cells that can be used to precisely target each patient’s therapy. Another project involves stochastic modeling of the yeast cell to understand the impact of molecular noise on cell cycle progression.
Dr. Baumann earned a B.S. in electrical engineering from Lehigh University in 1978, an M.S. in electrical engineering from MIT in 1980, and a Ph.D. from The Johns Hopkins University in 1985.
Dr. Milton Brown is director of Drug Discovery at Georgetown Lombardi Comprehensive Center. Dr. Brown has more than 15 years of experience in developing new drugs in the fields of cancer and neuroscience. Under his leadership, Georgetown Lombardi’s Drug Discovery Program was selected as a Chemical Diversity Center in the National Cancer Institute’s Chemical Biology Program. His laboratory is equipped to design and synthesize new compounds, evaluate the compounds against targeted proteins and human cancer cell lines, characterize the maximal tolerated dose (MTD) in small animals and to evaluate candidate compounds in mouse xenograft models.
Dr. Brown earned a B.S. in biology from Oakwood University in 1987 and a Ph.D in organic chemistry from the University of Alabama at Birmingham in 1995. He then earned an M.D. from the University of Virginia in 1999, received postdoctoral training in the department of chemistry there in 2000.
Dr. Chun Chen is a postdoctoral fellow at Virginia Tech. His research focuses on applying computational techniques to study dynamics of biological systems, to improve understanding of the underlying mechanisms behind complex diseases such as cancer. He is particularly interested in the cell life/death decision mechanism and he is currently working on a mechanistic model of the estrogen receptor-growth factor receptor survival switch. The ultimate goal is to build mathematical models that can be used to optimize therapy protocols to prevent the onset of resistance.
Dr. Chen earned a B.S. in biotechnology and an M.S. in biochemistry and molecular biology from Nanjing University in 2005 and 2008 respectively. He earned a Ph.D. in genetics, bioinformatics, and computational biology from Virginia Tech in 2013.
Dr. Katherine Cook is a postdoctoral research fellow in the Department of Oncology at Georgetown University Medical Center. Her research focuses on antiestrogen resistance, which appears in more than 50 percent of patients treated with antiestrogen therapy. Dr. Cook is investigating the interaction between the estrogen receptor, the unfolded protein response, autophagy, and cell death. The goal is to construct a mathematical model of antiestrogen resistance that connects cellular stress, metabolism, and survival pathway. These models will highlight critical components of resistance and allow researchers to better target and treat endocrine-resistant breast cancer.
Dr. Cook earned a B.S. in biochemistry in 2006 from the University of New York at Oswego and a Ph.D. in molecular medicine and translational science from Wake Forest University in 2010.
Dr. Leena Hilakivi-Clarke is a professor of Oncology at Georgetown University Medical Center. Her research involves studying the role of estrogens and diet in breast cancer. She currently investigates transgenerational effects of maternal dietary estrogenic exposures during pregnancy on offspring’s breast cancer risk, focusing on alterations in the epigenome as causing the increase in breast cancer risk among daughters, granddaughters and great granddaughters. In addition, her laboratory is investigating the mechanisms explaining how dietary estrogenic exposures in utero or during childhood can impact the biology of later mammary tumors, and their response to antiestrogen therapy. She collaborates closely with computational engineers at Virginia Tech and therefore her studies have a strong Systems Biology component.
Dr. Hilakivi-Clarke was educated at the University of Helsinki, Finland. She earned a B.A. in biology and experimental psychology in 1982, an M.A in physiology and experimental psychology in 1983 and a Ph.D. in 1987. She completed a postdoctoral fellowship in 1990 at the National Institutes of Health, NIAAA, pharmacology.
Dr. Subha Madhavan is the Director of Clinical Research Informatics at the Lombardi Comprehensive Cancer Center at Georgetown University and Director of the Innovation Center for Biomedical Informatics. She also leads the In Silico Research Center for Excellence, the Breast and Colon Cancer Family Registries, and the Georgetown Database of Cancer. She is an information scientist who has worked in the field of biomedical informatics and clinical data management and analysis for almost 15 years. A current research project involves developing a mathematical model to predict which stage-two colorectal cancer patients are likely to benefit from chemotherapy, and which would likely relapse. Another project involves mining through the records of pediatric cancer patients to predict side effects from treatment that occur later in life.
Dr. Madhavan earned a B.S. in chemical engineering from the Birla Institute of Technology and Service in 1986 and an M.Sc. in biological sciences in 1996. She earned a Ph.D. in biological sciences from the Uniformed Services University for Health Sciences in 2000.
Dr. Ayesha Shajahan-Haq is an assistant professor of research at the Lombardi Comprehensive Cancer Center at Georgetown University and co-director of the M.S. program in Tumor Biology. Her research in Cancer Systems Biology focuses on reprogramming cellular metabolic pathways mediated through the unfolded protein response (UPR) in cancer cells that are resistant to antiestrogen therapies. Results show that a change in the genetic makeup of resistant breast cancer cells allows increased production of a protein (MYC) that can directly influence the biochemical pathways and promote cell survival. The goal is to construct a model that connects the altered state of cellular metabolism with survival pathways in drug resistant cancer. Knowledge of the reprogramed pathways will help researchers use new or existing therapeutic agents to successfully treat drug-resistant breast cancer.
Dr. Shajahan-Haq is a member of the Education and Outreach Program of the Integrative Cancer Biology Program of the NIH. She earned a B.S. and M.S. in biological sciences from Wright State University in 1997 and 1999 respectively. She earned a Ph.D. in pharmacology in 2004 from the University of Illinois at Chicago.
Dr. John Tyson is a University Distinguished Professor in the Department of Biology at Virginia Tech. Tyson is a computational cell biologist, interested in the molecular mechanisms underlying the control of cell growth, division and death. His research investigates biological control systems from a rigorous mathematical perspective, building realistic models to gain a deeper understanding of cell physiology. His extensive experience in the mechanisms controlling the cell division cycle in yeast has provided the most comprehensive and accurate cell cycle models available. His group has developed some basic mathematical models of cancer cell response to estrogen therapy. The team is now working with experimental results to refine and improve the models.
Dr. Tyson earned a B.S. in chemistry from Wheaton College in 1969 and a Ph.D. in chemical physics from the University of Chicago in 1973. He completed a postdoctoral fellowship at the Max-Planck-Institute for Biophysical Chemistry in 1974.
Dr. Joseph Wang s the Grant A. Dove Professor of Electrical and Computer Engineering and the Director of the Computational Bioinformatics and Bioimaging Laboratory at Virginia Tech, in Arlington, Virginia. He has expertise in machine learning, pattern recognition, signal/image processing, data visualization, with applications to computational bioinformatics, computational systems biology/genetics, and medical imaging. He has collaborated with researchers from the Lombardi Comprehensive Cancer Center for almost 15 years, bringing computational and bioinformatics perspective to many projects. One recent project found that breast cancer risks acquired in pregnancy may pass to great-granddaughters. Wang’s group developed mathematical models and machine-learning techniques to analyze the changes in DNA methylation status to understand how an increased cancer risk is transmitted without genetic mutation.
Wang earned a B.S. in computer science and an M.S. in electrical engineering from Shanghair Jiaotong Unversity in 1984 and 1987 respectively. He earned a Ph.D. in electrical engineering from the University of Maryland in 1995 and completed a postdoctoral fellowship at Georgetown University School of Medicine in 1996.
Dr. Louis Weiner s Professor and Director of the Lombardi Comprehensive Cancer Center, and holds the Francis L. and Charolotte G. Gragnani Chair in the Department of Oncology. He also serves as Associate Vice President of the Georgetown University Medical Center, and Clinical Director of Cancer Services at Georgetown University Hospital. Dr. Weiner is a medical oncologist who specializes in gastrointestinal cancers. His research focuses on helping a patient’s immune system fight cancer with monoclonal antibodies, which are proteins that target specific cancer cells. His research is responsible for the observation that it’s possible for antibodies to attach too closely to a tumor, thus hurting tumor targeting. He has also developed “bispecific” antibodies and related proteins that both recognize cancer cells and stimulate the patient’s immune system to attack them.
Dr. Weiner earned a B.A. in biology from the University of Pennsylvania in 1973. He then earned an M.D. from Mount Sinai School of Medicine in 1977 and completed his residency in 1981 at the Medical Center Hospital of Vermont. He also completed a fellowship at the New England Medical Center Hospital in hematology/oncology in 1984.
Dr. Jason Xuan is an associate professor in Virginia Tech’s department of electrical and computer engineering and associate director of Virginia Tech’s Computational Bioinformatics and Bioimaging Laboratory at the Advanced Research Institute in Arlington, Virginia. He applies computational systems biology, bioinformatics, intelligent computing, and information visualization to cancer research. His research projects include uncovering estrogen receptor-signaling networks to overcome endocrine resistance, the effects of a high-fat diet during pregnancy on breast cancer for several generations of descendants, and applying mathematical modeling and machine learning approaches to understand the causes of drug resistance in breast cancer treatment.
Dr. Xuan earned his B.S., M.S., and Ph.D. in electrical engineering from the University of Zhejiang in 1985, 1988, and 1991 respectively. He also earned a Ph.D. in electrical engineering and computer science from the University of Maryland in 1997.