Tissue microarray (TMA) applications: implications for molecular medicine

Modern expression-screening platforms such as complementary DNA (cDNA) arrays allow for high-throughput lead discovery in cancer and other diseases. For evaluation of promising candidate genes, however, in situ analysis of high numbers of clinical tissues samples--for example, by immunohistochemistry or fluorescence in situ hybridisation--is mandatory. Tissue microarray (TMA) technology greatly facilitates such analysis. Minute tissue cores (diameter 0.6 mm) are removed from up to a thousand different conventional paraffin blocks and re-assembled in a single empty paraffin block at predefined positions. Sections of the resulting TMA can be utilised for the range of research applicable to conventional tissue sections. Important advantages of the TMA technology are speed (parallel analysis of up to a thousand tissues), cost efficiency (the same amount of reagents required for a single large-section analysis is sufficient for a thousand samples), and standardisation (the same experimental conditions are applied to all samples). Because of the high numbers of samples usually included in TMAs, they are optimally suited to detect genotype-phenotype associations with high statistical power. Thus, TMA technology will markedly accelerate the transition from basic research to clinical applications.     

Plant–Pathogen Interactions: What Microarray Tells About It?

Plant defense responses are mediated by elementary regulatory proteins that affect expression of thousands of genes. Over the last decade, microarray technology has played a key role in deciphering the underlying networks of gene regulation in plants that lead to a wide variety of defence responses. Microarray is an important tool to quantify and profile the expression of thousands of genes simultaneously, with two main aims: (1) gene discovery and (2) global expression profiling. Several microarray technologies are currently in use; most include a glass slide platform with spotted cDNA or oligonucleotides. Till date, microarray technology has been used in the identification of regulatory genes, end-point defence genes, to understand the signal transduction processes underlying disease resistance and its intimate links to other physiological pathways. Microarray technology can be used for in-depth, simultaneous profiling of host/pathogen genes as the disease progresses from infection to resistance/susceptibility at different developmental stages of the host, which can be done in different environments, for clearer understanding of the processes involved. A thorough knowledge of plant disease resistance using successful combination of microarray and other high throughput techniques, as well as biochemical, genetic, and cell biological experiments is needed for practical application to secure and stabilize yield of many crop plants. This review starts with a brief introduction to microarray technology, followed by the basics of plant–pathogen interaction, the use of DNA microarrays over the last decade to unravel the mysteries of plant–pathogen interaction, and ends with the future prospects of this technology.     

Prostate cancer and the genomic revolution: Advances using microarray analyses

The emerging technology of microarray analysis allows the establishment of molecular portraits of prostate cancer and the discovery of novel genes involved in the carcinogenesis process. Many novel genes have already been identified using this technique, and functional analyses of these genes are currently being tested. The combination of microarray analysis with other recently developed high-throughput techniques, such as proteomics, tissue arrays, and gene promoter-methylation, especially using tissue microdissection methods, will provide us with more comprehensive insights into how prostate cancer develops and responds to gene-targeted therapies. Animal models of prostate cancer are being characterized by high throughput techniques to better define the similarities and differences between those models and the human disease, and to determine whether particular models may be useful for specific targeted therapies in pre-clinical studies. Although profiling of mRNA expression provides important information of gene expression, the development of proteomic technologies will allow for an even more precise global insight into cellular signaling and structural alterations during prostate carcinogenesis. Not only will the "omic" revolution change basic science, but it will lead to a new era of molecular medicine.     

基因表达系列分析(SAGE)的研究进展

基因表达系列分析方法（SAGE）是一种新的基因表达分析方法,它可同时分析数千种转录子的表达情况.SAGE不仅可以定量分析已知基因,还可分析未知的基因表达情况.SAGE为从分子水平阐明疾病的发病机制找到有效的治疗靶位和诊断标志创造了条件.     

Protein profiling in respiratory disease: techniques and impact

Multifactorial diseases such as respiratory disease call for a global analysis of such disorders. Recent advances in protein profiling techniques may allow for early diagnosis of respiratory disease, which is crucial for intervention and treatment. In order to reduce false-positive rates, clinical diagnosis requires a high degree of sensitivity and specificity to be an effective screening tool. Protein profiles identified by ProteinChip^® (Ciphergen Biosystems) technology coupled with mass spectrometry affords a global analysis of clinical samples and is beginning to reach acceptable levels of sensitivity and specificity. Combining the profile with another diagnostic tool enhances the effectiveness of protein profiles to classify disease. Although current efforts have centered on serum protein profiling, the local environment of the lung may be better reflected in proteins of bronchoalveolar lavage or sputum. Identification of biomarkers of disease by protein profiling anaylses may lead to an understanding of the mechanisms of this disease and contribute to the discovery of new therapeutics for the prevention and treatment of disease. Advancing these analyses are techniques such as ProteinChip mass spectrometry, laser capture microdissection, tissue microarrays and fluorescently labeled antibody bead arrays, which enable the direct global analysis of complex mixtures. Effective high-throughput and ease of use of clinical testing will arrive with improvements in bioinformatics and decreases in instrumentation costs.     

Protein profiling in respiratory disease: techniques and impact

Multifactorial diseases such as respiratory disease call for a global analysis of such disorders. Recent advances in protein profiling techniques may allow for early diagnosis of respiratory disease, which is crucial for intervention and treatment. In order to reduce false-positive rates, clinical diagnosis requires a high degree of sensitivity and specificity to be an effective screening tool. Protein profiles identified by ProteinChip (Ciphergen Biosystems) technology coupled with mass spectrometry affords a global analysis of clinical samples and is beginning to reach acceptable levels of sensitivity and specificity. Combining the profile with another diagnostic tool enhances the effectiveness of protein profiles to classify disease. Although current efforts have centered on serum protein profiling, the local environment of the lung may be better reflected in proteins of bronchoalveolar lavage or sputum. Identification of biomarkers of disease by protein profiling analyses may lead to an understanding of the mechanisms of this disease and contribute to the discovery of new therapeutics for the prevention and treatment of disease. Advancing these analyses are techniques such as ProteinChip mass spectrometry, laser capture microdissection, tissue microarrays and fluorescently labeled antibody bead arrays, which enable the direct global analysis of complex mixtures. Effective high-throughput and ease of use of clinical testing will arrive with improvements in bioinformatics and decreases in instrumentation costs.     

TmaDB: a repository for tissue microarray data

Background  

Tissue microarray (TMA) technology has been developed to facilitate large, genome-scale molecular pathology studies. This technique provides a high-throughput method for analyzing a large cohort of clinical specimens in a single experiment thereby permitting the parallel analysis of molecular alterations (at the DNA, RNA, or protein level) in thousands of tissue specimens. As a vast quantity of data can be generated in a single TMA experiment a systematic approach is required for the storage and analysis of such data.     

Post-genomic applications of tissue microarrays: basic research, prognostic oncology, clinical genomics and drug discovery

Tissue microarrays (TMAs) are an ordered array of tissue cores on a glass slide. They permit immunohistochemical analysis of numerous tissue sections under identical experimental conditions. The arrays can contain samples of every organ in the human body, or a wide variety of common tumors and obscure clinical cases alongside normal controls. The arrays can also contain pellets of cultured tumor cell lines. These arrays may be used like any histological section for immunohistochemistry and in situ hybridization to detect protein and gene expression. This new technology will allow investigators to analyze numerous biomarkers over essentially identical samples, develop novel prognostic markers and validate potential drug targets. The ability to combine TMA technology with DNA microarrays and proteomics makes it a very attractive tool for analysis of gene expression in clinically stratified tumor specimens and relate expression of each particular protein with clinical outcome. Public domain software allows researchers to examine digital images of individual histological specimens from TMAs, evaluate and score them and store the quantitative data in a relational database. TMA technology may be specifically applied to the profiling of proteins of interest in other pathophysiological conditions such as congestive heart failure, renal disease, hypertension, diabetes, cystic fibrosis and neurodegenerative disorders. This review is intended to summarize the strengths and weaknesses of TMA technology which will have an increasingly important role in the laboratories of the post-genomic era.     

Antibody microarrays: current status and key technological advances

Antibody-based microarrays are among the novel classes of rapidly evolving proteomic technologies that holds great promise in biomedicine. Miniaturized microarrays (< 1 cm2) can be printed with thousands of individual antibodies carrying the desired specificities, and with biological sample (e.g., an entire proteome) added, virtually any specifically bound analytes can be detected. While consuming only minute amounts (< microL scale) of reagents, ultra- sensitive assays (zeptomol range) can readily be performed in a highly multiplexed manner. The microarray patterns generated can then be transformed into proteomic maps, or detailed molecular fingerprints, revealing the composition of the proteome. Thus, protein expression profiling and global proteome analysis using this tool will offer new opportunities for drug target and biomarker discovery, disease diagnostics, and insights into disease biology. Adopting the antibody microarray technology platform, several biomedical applications, ranging from focused assays to proteome-scale analysis will be rapidly emerging in the coming years. This review will discuss the current status of the antibody microarray technology focusing on recent technological advances and key issues in the process of evolving the methodology into a high-performing proteomic research tool.     

Integrative analysis of multiple gene expression profiles applied to liver cancer study

A statistical method for combining multiple microarray studies has been previously developed by the authors. Here, we present the application of the method to our hepatocellular carcinoma (HCC) data and report new findings on gene expression changes accompanying HCC. From the cross-verification result of our studies and that of published studies, we found that single microarray analysis might lead to false findings. To avoid those pitfalls of single-set analyses, we employed our effect size method to integrate multiple datasets. Of 9982 genes analyzed, 477 significant genes were identified with a false discovery rate of 10%. Gene ontology (GO) terms associated with these genes were explored to validate our method in the biological context with respect to HCC. Furthermore, it was demonstrated that the data integration process increases the sensitivity of analysis and allows small but consistent expression changes to be detected. These integration-driven discoveries contained meaningful and interesting genes not reported in previous expression profiling studies, such as growth hormone receptor, erythropoietin receptor, tissue factor pathway inhibitor-2, etc. Our findings support the use of meta-analysis for a variety of microarray data beyond the scope of this specific application.     

Analysis of protein expression in cell microarrays: a tool for antibody-based proteomics.

Tissue microarray (TMA) technology provides a possibility to explore protein expression patterns in a multitude of normal and disease tissues in a high-throughput setting. Although TMAs have been used for analysis of tissue samples, robust methods for studying in vitro cultured cell lines and cell aspirates in a TMA format have been lacking. We have adopted a technique to homogeneously distribute cells in an agarose gel matrix, creating an artificial tissue. This enables simultaneous profiling of protein expression in suspension- and adherent-grown cell samples assembled in a microarray. In addition, the present study provides an optimized strategy for the basic laboratory steps to efficiently produce TMAs. Presented modifications resulted in an improved quality of specimens and a higher section yield compared with standard TMA production protocols. Sections from the generated cell TMAs were tested for immunohistochemical staining properties using 20 well-characterized antibodies. Comparison of immunoreactivity in cultured dispersed cells and corresponding cells in tissue samples showed congruent results for all tested antibodies. We conclude that a modified TMA technique, including cell samples, provides a valuable tool for high-throughput analysis of protein expression, and that this technique can be used for global approaches to explore the human proteome.     

New tissue microarray technology for analyses of gene expression in frozen pathological samples

Tissue microarrays (TMAs) are widely used to analyze gene expression in multiple pathological samples on a single slide. Currently, most TMA slides are made by coring paraffin-embedded tissues and arraying them into a paraffin block, from which TMA sections are cut. However paraffin-based TMA technology may not be compatible with frozen clinical tissue samples, which have a higher quality of RNAs and proteins for preparing TMAs than paraffin-embedded tissue samples. In this study, we developed an alternative TMA technology that is applicable to a broader range of frozen tissue samples. Our method takes advantage of a newly developed array recipient block that can be used to array small tissue cores. After arraying tissue cores, the tissue block can be immediately sectioned on a cryostat microtome to make TMA slides. TMAs made using this method have well-defined array configurations and good tissue/cell morphology. Immunohistochemistry and in situ hybridization study also revealed well-preserved proteins and mRNAs on TMA slides. Our method significantly simplifies TMA preparation and assembly when frozen pathological tissues are used. Our technology provides an alternative tool for creating high-quality TMAs for the general research community to study gene expressions in pathological samples.     

Pathway and ontology analysis: emerging approaches connecting transcriptome data and clinical endpoints

The increasing use of gene expression profiling offers great promise in clinical research into disease biology and its treatment. Along with the ability to measure changing expression levels in thousands of genes at once, comes the challenge of analyzing and interpreting the vast sets of data generated. Analysis tools are evolving rapidly to meet such challenges. The next step is to interpret observed changes in terms of the biological properties or relationships underlying them. One powerful approach is to make associations between the genes that are under investigation and well-known biochemical or signaling pathways, and further to assess the significance of such associations. Similarly, genes can be mapped to standardized biological categories via an ontology resource. We discuss these approaches and several web-based resources and tools designed to facilitate such analyses. This information can be used to facilitate understanding and to help design more focused experiments for validating the relevance and importance of these biological pathways and processes in human disease and therapeutics.     

Gene profiling for defining targets for new therapeutics in autoimmune diseases

The identification of novel targets for improved diagnosis and pharmaceutical intervention is of critical importance for better treatment of autoimmune diseases in the future. The possibility to measure levels of gene expression for tens of thousands of genes simultaneously and in a quantitative fashion will greatly enhance our knowledge of genes and pathways involved in disease pathogenesis. Initial studies have focused on the gene expression profiling of homogeneous cell populations. Genomic-scale gene expression profiling has also more recently been applied to tissue samples from patients with immunopathologies. The scope of the present review is to discuss recent progress in this field with respect to the identification of novel target molecules.     

Studying Gene Expression System Regulation at the Program Level

Understanding how gene expression systems influence biological outcomes is an important goal for diverse areas of research. Gene expression profiling allows for the simultaneous measurement of expression levels for thousands of genes and the opportunity to use this information to increase biological understanding. Yet, the best way to relate this immense amount of information to biological outcomes is far from clear. Here, a novel approach to gene expression systems research is presented that focuses on understanding gene expression systems at the level of gene expression program regulation. It is suggested that such an approach has important advantages over current techniques and may provide novel insights into how gene expression systems are regulated to shape biological outcomes such as the development of disease or response to treatment.     

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

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.     

The Application of the Tissue Microarray (TMA) Technology to Analyze Cerebral Organoids

“Multi-Omics” technologies have contributed greatly to the understanding of various diseases by enabling researchers to accurately and rapidly investigate the molecular circuitry that connects cellular systems. The tissue-engineered, three-dimensional (3D), in vitro disease model “organoid” integrates the “omics” results in a model system, elucidating the complex links between genotype and phenotype. These 3D structures have been used to model cancer, infectious disease, toxicity, and neurological disorders. Here, we describe the advantage of using the tissue microarray (TMA) technology to analyze human-induced pluripotent stem cell–derived cerebral organoids. Compared with the conventional processing of individual samples, sectioning and staining of TMA slides are faster and can be automated, decreasing labor and reagent costs. The TMA technology faithfully captures cell morphology variations and detects specific biomarkers. The use of this technology can scale up organoid research results in at least two ways: (1) in the number of specimens that can be analyzed simultaneously and (2) in the number of consecutive sections that can be produced for analysis with different probes and antibodies.     

In search of differentially expressed genes and proteins

A great challenge for modern cell biology is the successful examination of the co-expression of thousands of genes under physiological or pathological conditions and how the expression patterns define the different states of a single cell, tissue or a microorganism. Gene expression can be analyzed today on a large scale by advanced technical approaches for differential screening of proteins and mRNAs. The identification of differentially expressed mRNAs has been successfully applied to understand gene function and the underlying molecular mechanism(-s) of differentiation, development and disease state. Analysis of gene expression by the systematic mapping of thousands of proteins present in a cell or tissue can be achieved by the use of two-dimensional (2D) gel electrophoresis, quantitative computer image analysis, and protein identification techniques. In this article, we comment on some of these techniques and try to stress their advantages and drawbacks. We show how data from RNA/DNA mapping, sequence information from genome projects and protein pattern profiling can be linked with each other and annotated. These comprehensive approaches permit the study of differential gene and protein expressions in cells or tissues.