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Tuesday, May 20

1:00 Registration

Protein Microarrays

1:55 Chairperson’s Opening Remarks

2:00 Protein Microarray-Based Diagnostic Immunoassays of Tumor Specific Autoantibodies for the Early Detection of Cancer
Michael Tainsky, M.D., Professor, Pathology, Wayne State University School of Medicine
The humoral immune response is an exquisite biosensor of novel proteins expressed by tumor cells. Panels of tumor antigens could provide a sensitive and specific multianalyte immunoassay for the presymptomatic of cancer by measuring antitumor autoantibodies in serum. The development of early detection tests for cancers has previously depended on single biomarker molecules. Using a high-throughput cloning method, a panel of epitopes/antigens that react with autoantibodies to tumor proteins in the serum of patients with cancer have been isolated. The binding properties of these serum antitumor antibodies on microarrays and advanced bioinformatics tools led to a panel of diagnostic antigens. The sequences that were identified using high-throughput phage display cloning technology have led to the discovery of novel disease-related proteins. There are numerous advantages of employing serum antibodies as the analytes, not the least of which is the ability to readily adapt these assays to standard clinical immunoassay platforms.

2:30 Protein Microarrays and Quantum Dot-Probes for Cancer Biomarkers Early Detection
Tatyana Zhukov, M.D., Assistant Professor, Cancer Prevention and Control Division, H. Lee Moffitt Cancer Center & Research Institute
Combinations of highly fluorescent quantum dots with protein microarrays offer unique features for ultra low level detection of cancer markers in biological specimens (serum, plasma, body fluids). Protein microarrays allow highly parallel quantitation of specific proteins in a rapid, low-cost and low sample volume format. Furthermore the multiplexed assay enables detection of many proteins in one sample, making it a powerful tool for biomarker analysis and early cancer diagnostics.

3:00 Towards Label-Free Protein Microarrays
Paul Ko Ferrigno, Ph.D., Senior Lecturer, Experimental Therapeutics, Leeds Institute of Molecular Medicine
Peptide aptamers were conceived as artificial antibodies that could be used for drug target validation in human cells. It is somewhat surprising that their use as diagnostic probes has not been previously explored. We will show that peptide aptamer microarrays can be used to detect the expression of viral proteins in lysates of infected human cell, as well as surprising changes in human protein expression caused by infection. We will also present data using electrical measurements on ultra-high density, micron-scale semi-conductor electrode arrays to detect human proteins in yeast cell lysates, with a sensitivity in the femtomolar range.

3:30 Networking Refreshment Break, Exhibit and Poster Viewing

Proteomics as a Tool

4:15 Protein Microarrays for off-target Screening for Faster and Better Antibodies Lead Nomination of Antibodies
Stefan Müllner, Ph.D., CSO, Protagen AG
Oridis-Biomed has developed an integrated approach of screening i.e. antibodies for
faster and better lead nomination in pre-clinical and clinical development. Results will be discussed applying human tissue microarrays (TMA) for addressing on-target reactivity and off-target reactivity of antibodies for diagnostic and therapeutic applications. Such information combined with conventional in-vitro and/or in-vivo data can give powerful insights in the decision process.

4:45 Solution Showcase (Sponsorship Available)

5:00 Analytical Issues in 2D Gel-Based Proteomic Studies
Howard Gutstein, M.D., Associate Professor, Anesthesiology and Molecular Genetics, MD Anderson Cancer Center
One of the major limitations in proteomics is the time consuming and highly subjective data analysis. We have developed a new method for the analysis of large 2D gel data sets called "Pinnacle" that automates spot detection and quantification. In addition to reducing analysis time from weeks to minutes, subjectivity in spot detection and matching is eliminated. Also, there are no missing values, eliminating potential statistical bias. This method is also applicable to mass spectrometry data. Statistical (false discovery rate) and experimental design considerations (block design, randomization), will also be discussed.

5:30 Proteomic Tools as Diagnostics for Pregnancy Disorders: Proteomic Patterns versus Identities
Irina Buhimschi, M.D., Assistant Professor, Ob./Gyn. & Reproductive Sciences, Yale University School of Medicine
In current clinical medicine assignment of individual cases to diagnostic categories is critical as it frequently dictates treatment choices.
Personalized medicine, stands at the opposite end of the current "one size fits all" approach and relies heavily on development of classification algorithms based on biomarkers. Our laboratory has developed a series of proteomic algorithms for prediction of preterm birth and preeclampsia syndromes, which are the most important determinants of maternal and perinatal morbidity and mortality. Our approach is to combine proteomic pattern-based approached with identification-centered techniques is a step-wise fashion. The presentation will detail on the advantages and disadvantages of each approach and will summarize the development and validation steps necessary to produce a clinically and biologically relevant diagnostics tool.

6:00 End of Day One


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