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Open Access Research article

Internet-based profiler system as integrative framework to support translational research

Robert Kim1, Francesca Demichelis12, Jeffery Tang1, Alberto Riva3, Ronglai Shen4, Doug F Gibbs5, Vasudeva Mahavishno5, Arul M Chinnaiyan456 and Mark A Rubin127*

Author Affiliations

1 Department of Pathology, Brigham and Women's Hospital, Boston, USA

2 Harvard Medical School, Boston, USA

3 Children's Hospital Informatics Program, Children's Hospital, Boston, USA

4 Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, USA

5 Department of Pathology, University of Michigan, Ann Arbor, USA

6 Department of Urology, University of Michigan, Ann Arbor, USA

7 Dana Farber Harvard Comprehensive Cancer Center, Boston, USA

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BMC Bioinformatics 2005, 6:304  doi:10.1186/1471-2105-6-304

Published: 19 December 2005

Abstract

Background

Translational research requires taking basic science observations and developing them into clinically useful tests and therapeutics. We have developed a process to develop molecular biomarkers for diagnosis and prognosis by integrating tissue microarray (TMA) technology and an internet-database tool, Profiler. TMA technology allows investigators to study hundreds of patient samples on a single glass slide resulting in the conservation of tissue and the reduction in inter-experimental variability. The Profiler system allows investigator to reliably track, store, and evaluate TMA experiments. Here within we describe the process that has evolved through an empirical basis over the past 5 years at two academic institutions.

Results

The generic design of this system makes it compatible with multiple organ system (e.g., prostate, breast, lung, renal, and hematopoietic system,). Studies and folders are restricted to authorized users as required. Over the past 5 years, investigators at 2 academic institutions have scanned 656 TMA experiments and collected 63,311 digital images of these tissue samples. 68 pathologists from 12 major user groups have accessed the system. Two groups directly link clinical data from over 500 patients for immediate access and the remaining groups choose to maintain clinical and pathology data on separate systems. Profiler currently has 170 K data points such as staining intensity, tumor grade, and nuclear size. Due to the relational database structure, analysis can be easily performed on single or multiple TMA experimental results. The TMA module of Profiler can maintain images acquired from multiple systems.

Conclusion

We have developed a robust process to develop molecular biomarkers using TMA technology and an internet-based database system to track all steps of this process. This system is extendable to other types of molecular data as separate modules and is freely available to academic institutions for licensing.