11 months ago

2007 Scientific Report

  • Text
  • Report
  • Institute
  • Protein
  • Signaling
  • Tumor
  • Michigan
  • Molecular


VARI | 2007 Cancer biomarkers Improved methods of detecting and diagnosing cancer could significantly improve outcomes for many patients. We are seeking to identify and validate protein biomarkers that could form the basis of clinical cancer diagnostics. The antibody-based assays that we are using are valuable for this work because they are very reproducible, inexpensive, and high-throughput. In addition, the use of miniaturized arrays of antibodies allows us to efficiently test many antibodies and samples and to rapidly develop new assays. We are applying these capabilities in novel approaches to biomarker discovery and validation. Mouse models of cancer may provide a good resource for biomarker discovery because the genetic and experimental variation between samples can be closely controlled, thus making the identification of abnormal protein levels easier than with human clinical specimens. Mass spectrometry studies performed by other members of an NCI-sponsored consortium have identified candidate biomarkers in mouse models of ovarian and pancreatic carcinomas. Using newly generated antibodies that target those proteins, we are developing assays to determine the levels of these candidate biomarkers in the mouse models and to assess their diagnostic value for human cancer. Low-volume methods are crucial for these studies because only a small sample is available from each mouse. These studies could establish a new paradigm for biomarker discovery and validation. Longitudinal biomarkers An NCI-sponsored project in our laboratory focuses on the hypothesis that the diagnostic performance of particular biomarkers can be improved by using measurements collected on multiple occasions (longitudinal measurements) rather than at just a single point in time. By looking at changes over time, it may be possible to more accurately distinguish abnormal levels in a given individual, since that person’s normal level could be used as a reference point. In a collaboration with Robert Vessella and William Catalona, we are investigating this question for the detection of prostate cancer recurrence. By using various formats of antibody arrays, we can explore different data types and multiple proteins, which we hope will establish the extent of diagnostic improvement using longitudinal information. Another collaborator, Ziding Feng, is developing the statistical methods for analyzing the data, which may have value for other applications of this approach. 29 Tumor-reactive antibodies We and others have investigated measurements of tumor-reactive antibodies as biomarkers. Certain tumor proteins elicit an antibody-based immune response in a high percentage of cancer patients. In collaboration with Samir Hanash, Gilbert Omenn, and others, we have further developed the experimental methods for identifying tumor-reactive antibodies using protein arrays. We are applying this method to the detection of prostate cancer and prostate cancer recurrence. The changes in the tumor-reactive antibodies are being assessed using the longitudinal approach described above, which may improve the diagnostic performance of those biomarkers and give insight into the role of immune response in determining the likelihood of cancer recurrence. Pancreatic cancer biomarkers Other biomarker studies in our lab are focused on pancreatic cancer in collaboration with Anna Lokshin, Michael Hollingsworth, and others in the Early Detection Research Network (EDRN), which is an NCI-sponsored consortium dedicated to discovering and validating cancer biomarkers. We use the glycan and protein detection technologies described above to identify and study biomarkers for the early detection or more accurate diagnosis of pancreatic cancer. We have shown that, in certain cases, the measurement of a glycan on a protein is more accurate for detecting cancer than the measurement of the protein alone in traditional antibody assays. We are now seeking to define which protein and glycan alterations have the highest diagnostic and prognostic significance.

Van Andel Research Institute | Scientific Report External Collaborators Philip Andrews, University of Michigan, Ann Arbor Randall Brand, Evanston Northwestern Healthcare, Evanston, Illinois William Catalona, Northwestern University, Evanston, Illinois Ziding Feng, Fred Hutchinson Cancer Research Center, Seattle, Washington Irwin Goldstein, University of Michigan, Ann Arbor Samir Hanash, Fred Hutchinson Cancer Research Center, Seattle, Washington Michael A. Hollingsworth, University of Nebraska, Omaha Anna Lokshin, University of Pittsburgh, Pennsylvania Gilbert Omenn, University of Michigan, Ann Arbor Alan Partin, Johns Hopkins University, Baltimore, Maryland Diane Simeone, University of Michigan, Ann Arbor Robert Vessella, University of Washington, Seattle Recent Publications From left: Forrester, Porter, Nelson, Haab, Bergsma, Collins, Lundquist, Chen, Yue, Wu, Turner 30 Chen, S., and B.B. Haab. In press. Antibody microarrays for protein and glycan detection. In Clinical Proteomics, Wiley-VCH. Chen, S., T. LaRoche, D. Hamelinck, D. Bergsma, D. Brenner, D. Simeone, R.E. Brand, and B.B. Haab. In press. Multiplexed analysis of glycan variation on native proteins captured by antibody microarrays. Nature Methods. Forrester, S., J. Qiu, L. Mangold, A.W. Partin, D. Misek, B. Phinney, D. Whitten, P. Andrews, E. Diamandis, G.S. Omenn, S. Hanash, and B.B. Haab. In press. An experimental strategy for quantitative analysis of the humoral immune response to prostate cancer antigens using natural protein microarrays. Proteomics. Omenn, Gilbert S., Raji Menon, Marcin Adamski, Thomas Blackwell, Brian B. Haab, and Weimin Gao, and David J. States. 2007. The human plasma proteome. In Proteomics of Human Body Fluids: Principles, Methods, and Applications, V. Thongboonkerd, ed. Totowa, N.J.: Humana Press. Shafer, Michael W., Leslie Mangold, Alam W. Partin, and Brian B. Haab. 2007. Antibody array profiling reveals serum TSP-1 as a marker to distinguish benign from malignant prostatic disease. The Prostate 67: 255–267. Haab, B.B. 2006. Applications of antibody array platforms. Current Opinion in Biotechnology 17(4): 415–421. Haab, B.B. 2006. Using array-based competitive and noncompetitive immunoassays. In American Association of Cancer Research Annual Meeting Education Book, Phildelphia: American Association of Cancer Research. Haab, Brian B., Amanda G. Paulovich, N. Leigh Anderson, Adam M. Clark, Gregory J. Downing, Henning Hermjakob, Joshua LaBaer, and Mathias Uhlen. 2006. A reagent resource to identify proteins and peptides of interest for the cancer community: a workshop report. Molecular & Cellular Proteomics 5(10): 1996–2007. Hung, Kenneth E., Alvin T. Kho, David Sarracino, Larissa Georgeon Richard, Bryan Krastins, Sara Forrester, Brian B. Haab, Isaac S. Kohane, and Raju Kucherlapati. 2006. Mass spectrometry–based study of the plasma proteome in a mouse intestinal tumor model. Journal of Proteome Research 5(8): 1866–1878.

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