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2006 Scientific Report

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Van Andel Research

Van Andel Research Institute | Scientific Report Prostate cancer A great need also exists for improved tests for prostate cancer, which is the most prevalent cancer among men. A blood test—the prostate-specific antigen (PSA) test—is in wide use for prostate cancer detection, but it suffers from a high rate of false positives and the inability to detect many fast-growing cancers at early stages. We are taking several approaches toward improving prostate cancer diagnostics. In a collaboration with Alan Partin (Johns Hopkins University), we have used array-based screening to identify proteins having altered abundances in prostate cancer. One of the proteins identified in our screens, thrombospondin-1 (TSP-1), may be valuable in differentiating prostate cancer from benign prostatic disease, which are sometimes indistinguishable by conventional methods. We have found that TSP-1 is elevated in 80% of patients with benign disease relative to patients with malignant disease, and it is repressed in prostate cancer patients relative to healthy individuals. One of the functions of TSP-1 is to suppress the growth of new blood vessels (angiogenesis), which is a crucial process in the growth and progression of tumors. We are investigating the glycosylation states and protein-protein interactions of this molecule and the functional consequences of those states. In another approach to improving prostate cancer diagnostics, we are investigating the use of longitudinal measurements (serial measurements over time) to develop and improve existing diagnostic markers. We hypothesize that the use of individualized thresholds of “abnormal” protein levels, defined by each person’s history of measurements, will yield improved diagnostic accuracy over the use of single thresholds based on levels across the population. In a collaboration with William Catalona (Northwestern University), Robert Vessella (University of Washington), and Ziding Feng (Fred Hutchinson Cancer Research Center), we are looking at changes over time in the concentration of a number of serum proteins leading up to disease recurrence in prostate cancer patients. Our hypothesis has been supported in some individual demonstrations, but we now have a means for systematically exploring it for a large number of proteins and many patients, laying the groundwork for broader application of the approach. 30 Our cell culture studies complement the above work, using clinical samples from cancer patients in order to study in a more controlled environment the protein alterations observed in the blood. We are investigating the conditions that reproduce what is observed in the blood, and we are studying the functional consequences of certain cancer-related alterations. This mechanistic understanding will be important in identifying additional protein alterations that have diagnostic value and in devising blood-based strategies to interfere with cancer processes. We hope to translate these developments into improved care for cancer patients. From left to right: Nelson, Mistry, Wu, Bergsma, Chen, LaRoche, Shafer, Haab

VARI | 2006 Recent Publications Haab, B.B., and P.M. Lizardi. 2006. RCA-enhanced protein detection arrays. In New and Emerging Proteomic Techniques, D. Nedelkov and R.W. Nelson, eds. Methods in Molecular Biology series, Totowa, N.J.: Humana Press, pp. 15–29. Sanchez-Cabayo, M., N.D. Socci, J.J. Lozano, B.B. Haab, and C. Cordon-Cardo. 2006. Profiling bladder cancer using targeted antibody arrays. American Journal of Pathology 168(1): 93–103. Gao, Wei-Min, Rork Kuick, Randal P. Orchekowski, David E. Misek, Ji Qiu, Alissa K. Greenberg, William N. Rom, Dean E. Brenner, Gilbert S. Omenn, Brian B. Haab, and Samir M. Hanash. 2005. Distinctive serum protein profiles involving abundant proteins in lung cancer patients based upon antibody microarray analysis. BMC Cancer 5: 110. Haab, Brian B. 2005. Antibody arrays in cancer research. Molecular & Cellular Proteomics 4(4): 377–383. Haab, Brian B. 2005. Multiplexed protein analysis using antibody microarrays and label-based detection. In Microarrays in Clinical Diagnostics, T.O. Joos and P. Fortina, eds. Methods in Molecular Medicine series, Totowa, N.J.: Humana Press, pp. 183–194. 31 Haab, Brian B., Bernhard H. Geierstanger, George Michailidis, Frank Vitzthum, Sara Forrester, Ryan Okon, Petri Saviranta, Achim Brinker, Martin Sorette, Lorah Perlee, Shubha Suresh, Garry Drwal, Joshua N. Adkins, and Gilbert S. Omenn. 2005. Immunoassay and antibody microarray analysis of the HUPO Plasma Proteome Project reference specimens: systematic variation between sample types and calibration of mass spectrometry data. Proteomics 5(13): 3278–3291. Hamelinck, Darren, Heping Zhou, Lin Li, Cornelius Verweij, Deborah Dillon, Ziding Feng, Jose Costa, and Brian B. Haab. 2005. Optimized normalization for antibody microarrays and application to serum-protein profiling. Molecular & Cellular Proteomics 4(6): 773–784. Omenn, Gilbert S., David J. States, Marcin Adamski, Thomas W. Blackwell, Rajasree Menon, Henning Hermjakob, Rolf Apweiler, Brian B. Haab, Richard J. Simpson, James S. Eddes, Eugene A. Kapp, Robert L. Moritz, Daniel W. Chan, Alex J. Rai, Arie Admon, et al. 2005. Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly available database. Proteomics 5(13): 3226–3245. Orchekowski, Randal, Darren Hamelinck, Lin Li, Ewa Gliwa, Matt VanBrocklin, Jorge A. Marrero, George F. Vande Woude, Ziding Feng, Randall Brand, and Brian B. Haab. 2005. Antibody microarray profiling reveals individual and combined serum proteins associated with pancreatic cancer. Cancer Research 65(23): 11193–11202. Rai, Alex J., Craig A. Gelfand, Bruce C. Haywood, David J. Warunek, Jizu Yi, Mark D. Schuchard, Richard J. Mehigh, Steven L. Cockrill, Graham B.I. Scott, Harald Tammen, Peter Schulz-Knappe, David W. Speicher, Frank Vitzthum, Brian B. Haab, Gerard Siest, and Daniel W. Chan. 2005. HUPO-PPP Specimen Collection and Handling Committee report: towards the standardization of parameters for proteomic analyses. Proteomics 5(13): 3262–3277. Steel, Laura F., Brian B. Haab, and Samir M. Hanash. 2005. Methods of comparative proteomic profiling for disease diagnostics. Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences 815(1–2): 275–284.

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