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(American Journal of Pathology. 2001;159:837-843.)
© 2001 American Society for Investigative Pathology

Technical Advances

Relational Database Structure to Manage High-Density Tissue Microarray Data and Images for Pathology Studies Focusing on Clinical Outcome

The Prostate Specialized Program of Research Excellence Model

Sargum Manley*, Neil R. Mucci{dagger}, Angelo M. De Marzo{ddagger} and Mark A. Rubin*§

From the Departments of Pathology,*
Internal Medicine–Division of Hematology/Oncology,{dagger}
and Urology,§
University of Michigan Comprehensive Cancer and Geriatrics Center, Ann Arbor, Michigan; and the Department of Pathology,{ddagger}
Johns Hopkins University School of Medicine, Baltimore, Maryland

With the completion of the Human Genome Project and high-throughput screening methods using cDNA array and tissue microarray (TMA) technology, there is a pressing need to manage the voluminous data sets generated from these types of investigations. Herein is described a database model to handle 1) clinical and pathology data, 2) TMA location information, and 3) web-based histology results. The model is useful for managing clinical, pathology, and molecular data on >1300 prostate cancer patients dating back to 1995 from the University of Michigan Specialized Program of Research Excellence for prostate cancer. The key components in this multidatabase model are 1) the TMA database, 2) the TMA-image database (TMA-I DB), and 3) the prostate pathology and clinical information databases. All databases were created in Microsoft Access (Microsoft, Redmond, WA). Desired patient, tissue, block, diagnosis, array location, and respective clinical and pathology information is obtained by linking the unique identifier fields among database tables. The TMA database is comprised of interrelated data from 336 prostate cancer patients transferred into 19 TMA blocks with 5451 TMA biopsy cores. Tissue samples include 1695 normal prostate, 3171 prostate cancer, 464 prostatic intraepithelial neoplasia, and 121 atrophy. All 19 TMA blocks have been analyzed over the Internet for several immunohistochemical biomarkers including E-cadherin, prostate-specific antigen, p27Kip1, and Ki-67 labeling index. This system facilitates the statistical analysis of high-density TMA data with clinical and pathology information in an efficient and cost-effective manner. Because the review is performed over the Internet, this system is ideal for collaborative multi-institutional studies.




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