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.
