Digital microscopy for boosting database integration and analysis in TMA studies.

The enormous amount of clinical, pathological, and staining data to be linked, analyzed, and correlated in a tissue microarray (TMA) project makes digital slides ideal to be integrated into TMA database systems. With the help of a computer and dedicated software tools, digital slides offer dynamic access to microscopic information at any magnification with easy navigation, annotation, measurement, and archiving features. Advanced slide scanners work both in transmitted light and fluorescent modes to support biomarker testing with immunohistochemistry, immunofluorescence or fluorescence in situ hybridization (FISH). Currently, computer-driven integrated systems are available for creating TMAs, digitalizing TMA slides, linking sample and staining data, and analyzing their results. Digital signals permit image segmentation along color, intensity, and size for automated object quantification where digital slides offer superior imaging features and batch processing. In this chapter, the workflow and the advantages of digital TMA projects are demonstrated through the project-based MIRAX system developed by 3DHISTECH and supported by Zeiss.The enhanced features of digital slides compared with those of still images can boost integration and intelligence in TMA database management systems, offering essential support for high-throughput biomarker testing, for example, in tumor progression/prognosis, drug discovery, and target therapy research.

[1]  J. Kononen,et al.  A high‐throughput strategy for protein profiling in cell microarrays using automated image analysis , 2007, Proteomics.

[2]  Nigam H. Shah,et al.  The Stanford Tissue Microarray Database , 2007, Nucleic Acids Res..

[3]  B. Molnár,et al.  Immunophenotypic Profiling of Nonsmall Cell Lung Cancer Progression Using the Tissue Microarray Approach , 2007, Applied immunohistochemistry & molecular morphology : AIMM.

[4]  Ashok Patel,et al.  The tissue microarray data exchange specification: implementation by the Cooperative Prostate Cancer Tissue Resource , 2004, BMC Bioinformatics.

[5]  O. Kallioniemi,et al.  Tissue microarray technology for high-throughput molecular profiling of cancer. , 2001, Human molecular genetics.

[6]  M. Becich,et al.  Practical aspects of planning, building, and interpreting tissue microarrays: The Cooperative Prostate Cancer Tissue Resource experience , 2007, Journal of Molecular Histology.

[7]  Martina Uray,et al.  TAMEE: data management and analysis for tissue microarrays , 2007, BMC Bioinformatics.

[8]  K. Pienta,et al.  Tissue Microarray Sampling Strategy for Prostate Cancer Biomarker Analysis , 2002, The American journal of surgical pathology.

[9]  Virgilia Macias,et al.  The Cooperative Prostate Cancer Tissue Resource , 2004, Clinical Cancer Research.

[10]  B. Molnár,et al.  Collagen XVII/BP180 Protein Expression in Squamous Cell Carcinoma of the Skin Detected With Novel Monoclonal Antibodies in Archived Tissues Using Tissue Microarrays and Digital Microscopy , 2008, Applied immunohistochemistry & molecular morphology : AIMM.

[11]  Jun Luo,et al.  Trefoil factor 3 overexpression in prostatic carcinoma: Prognostic importance using tissue microarrays , 2004, The Prostate.

[12]  Ash A. Alizadeh,et al.  Software tools for high-throughput analysis and archiving of immunohistochemistry staining data obtained with tissue microarrays. , 2002, The American journal of pathology.

[13]  C. Perou,et al.  Human epidermal growth factor receptor-2 and estrogen receptor expression, a demonstration project using the residual tissue respository of the Surveillance, Epidemiology, and End Results (SEER) program , 2008, Breast Cancer Research and Treatment.

[14]  L. Goldstein,et al.  Automated quantitative analysis of estrogen receptor expression in breast carcinoma does not differ from expert pathologist scoring: a tissue microarray study of 3,484 cases , 2008, Breast Cancer Research and Treatment.

[15]  D. Botstein,et al.  Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[16]  J. Kononen,et al.  Tissue microarrays for high-throughput molecular profiling of tumor specimens , 1998, Nature Medicine.

[17]  Yu Rang Park,et al.  The tissue microarray object model: a data model for storage, analysis, and exchange of tissue microarray experimental data. , 2006, Archives of pathology & laboratory medicine.

[18]  Sophia Hober,et al.  Human protein atlas and the use of microarray technologies. , 2008, Current opinion in biotechnology.

[19]  Z. Trajanoski,et al.  Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome , 2006, Science.