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Bridging Silos in Biomarker Discovery: Integrating Omic Data
June 23, 2009
1:00 p.m. – 3:00 p.m. EST

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1:00-1:10 Chairperson’s Opening Remarks

1:10-1:40 Systems Biology of Colon Cancer: Bridging the Silos in High-Throughput Data
Mark R. Chance, Ph.D., Director, Center for Proteomics & Synchrotron Biosciences, Physiology & Biophysics, School of Medicine, Case Western Reserve University
Data integration is increasingly important to maximize value in biomarker discovery and identify high value targets for therapeutic intervention. We employed a systems biology approach to identify and score protein interaction sub-networks whose activity patterns are discriminative of late stage human colorectal cancer (CRC) versus control in colonic tissue. We conducted two gel-based proteomic experiments to identify significantly changing proteins between normal and late stage tumor tissues obtained from an adequately sized cohort of human patients. A total of 67 proteins identified by these experiments were used to seed a search for protein-protein interaction sub-networks. A scoring scheme based on mutual information, calculated using gene expression data as a proxy for sub-network activity, was developed to score the targets in the sub-networks. Based on this scoring, the sub-network was pruned to identify the specific protein combinations that were significantly discriminative of late stage cancer versus control. These combinations could not be discovered using only proteomic data, or by merely clustering the gene expression data.  We then analyzed the resultant pruned sub-network for biological relevance to human CRC. A number of the proteins in these smaller sub- networks have been associated with the progression (CSNK2A2, PLK1, IGFBP3) or metastatic potential (PDGFRB) of CRC. Others have been recently identified as potential markers of CRC (IFITM1), and the role of others is largely unknown in this disease (CCT3, CCT5, CCT7, GNA12). The functional interactions represented by these signatures provide new experimental hypotheses that merit follow-on validation for biological significance in this disease. Overall, the method outlines a quantitative approach for integrating proteomic data, gene expression data, and the wealth of accumulated legacy experimental data to discover significant protein sub-networks specific to disease.

1:40-1:50 Sponsored Presentation
Opportunity available. Contact Ilana Quigley, Business Development, 781-972-5457 or iquigley@healthtech.com.

1:50-2:20 An Integrated Approach to Biomarker Discovery
Karin D. Rodland, Ph.D., Science Lead, NIH Programs, Biological Sciences, Pacific Northwest National Laboratory
Efforts to identify biomarkers for early diagnosis or prognosis of cancer and other disease have often focused on a singular molecular species, with preference given to mRNA, micro RNA, proteins, auto-antibodies or metabolites based on available technologies and model systems. Each one of these measurements provides a snapshot of cell function, but a dynamic understanding of disease processes really requires the integration of all these modalities to the extent possible. Particularly in the context of using biomarkers to guide therapeutic interventions, it is necessary to understand the relationship between changes in expression, and changes in function. One aspect of systems biology is the integration of heterogeneous datasets to define relationships that predict function.

2:20-2:30 Sponsored Presentation
Opportunity available. Contact Ilana Quigley, Business Development, 781-972-5457 or iquigley@healthtech.com.

2:30-3:00 Discussion with the Speakers


About the Speakers:

Mark R. Chance, Ph.D., Director, Center for Proteomics & Synchrotron Biosciences, Physiology & Biophysics, Case Western Reserve University School of Medicine
Dr. Mark Chance received his bachelor's degree in Biology from Wesleyan University and his Ph.D. degree in Biophysics from the University of Pennsylvania.  Dr. Chance furthered his training as a Postdoctoral Research Associate at AT&T Bell Laboratories.  He went on to become Assistant Professor in the Department of Chemistry at Georgetown University.  He then served as Assistant Professor at Albert Einstein College of Medicine in Bronx, New York and was soon promoted to Associate Professor of the Departments of Physiology & Biophysics and Biochemistry.  He was Professor at AECOM when he moved to the Case School of Medicine in 2005, where he is currently the Director of both the Case Center for Proteomics and Bioinformatics and Case Center for Synchrotron Biosciences and Professor of Physiology and Biophysics.  Dr. Chance is an internationally renowned scientist in the field of mass spectrometry. He is an expert in the quantitative mass spectrometry and 2-D Gel techniques that enable scientists to identify biomarkers and regulatory pathways in colon cancer, diabetes, radiation exposure, and HIV infection.


Karin D. Rodland, Ph.D., Science Lead, NIH Programs, Biological Sciences, Pacific Northwest National Laboratory

Karin Rodland joined the Biological Sciences Division in October 2001, after seventeen years on the faculty of Oregon Health Sciences University.  As Science Lead for NIH Programs at PNNL, she has promoted the application of PNNL’s traditional strengths in mass spectrometry, proteomics, and systems biology to important problems in biomedical research. She has fostered the development of PNNL staff and played a key role in organizing and coordinating interdisciplinary teams within PNNL and between PNNL and academic medical centers to build a significant and self-sustaining program in biomedical research.
 
Dr. Rodland’s own research focuses on signal transduction pathways that regulate proliferation in normal and malignant cells, and she was the first to recognize the role of the calcium-sensing receptor in modulating proliferation in response to small molecules in the extracellular environment. Since joining PNNL she has adopted a systems biology approach to signal transduction, and has become a recognized expert in the field of proteomics and cancer biomarkers.  She is a full member of the National Cancer Institute’s Early Detection Research Network and serves on the Department of Defense Congressionally Directed Medical Research Program Integration Panels for both Ovarian and Breast Cancer Research.

Please check back soon for updated information.