Differential gene expression analysis in ageing muscle and drug discovery perspectives.

Identifying therapeutic target genes represents the key step in functional genomics-based therapies. Within this context, the disease heterogeneity, the exogenous factors and the complexity of genomic structure and function represent important challenges. The functional genomics aims to overcome such obstacles via identifying the gene functions and therefore highlight disease-causing genes as therapeutic targets. Genomic technologies promise to reshape the research on ageing muscle, exercise response and drug discovery. Herein, we describe the functional genomics strategies, mainly differential gene expression methods microarray, serial analysis of gene expression (SAGE), massively parallel signature sequence (MPSS), RNA sequencing (RNA seq), representational difference analysis (RDA), and suppression subtractive hybridization (SSH). Furthermore, we review these illustrative approaches that have been used to discover new therapeutic targets for some complex diseases along with the application of these tools to study the modulation of the skeletal muscle transcriptome.

Next generation of network medicine: interdisciplinary signaling approaches.

In the last decade, network approaches have transformed our understanding of biological systems. Network analyses and visualizations have allowed us to identify essential molecules and modules in biological systems, and improved our understanding of how changes in cellular processes can lead to complex diseases, such as cancer, infectious and neurodegenerative diseases. "Network medicine" involves unbiased large-scale network-based analyses of diverse data describing interactions between genes, diseases, phenotypes, drug targets, drug transport, drug side-effects, disease trajectories and more. In terms of drug discovery, network medicine exploits our understanding of the network connectivity and signaling system dynamics to help identify optimal, often novel, drug targets. Contrary to initial expectations, however, network approaches have not yet delivered a revolution in molecular medicine. In this review, we propose that a key reason for the limited impact, so far, of network medicine is a lack of quantitative multi-disciplinary studies involving scientists from different backgrounds. To support this argument, we present existing approaches from structural biology, 'omics' technologies (e.g., genomics, proteomics, lipidomics) and computational modeling that point towards how multi-disciplinary efforts allow for important new insights. We also highlight some breakthrough studies as examples of the potential of these approaches, and suggest ways to make greater use of the power of interdisciplinarity. This review reflects discussions held at an interdisciplinary signaling workshop which facilitated knowledge exchange from experts from several different fields, including in silico modelers, computational biologists, biochemists, geneticists, molecular and cell biologists as well as cancer biologists and pharmacologists.

Microfluidics in microbiology: putting a magnifying glass on microbes.

Microfluidic technologies enable unique studies in the field of microbiology to facilitate our understanding of microorganisms. Using miniaturized and high-throughput experimental capabilities in microfluidics, devices with controlled microenvironments can be created for microbial studies in research fields such as healthcare and green energy. In this research highlight, we describe recently developed tools for diagnostic assays, high-throughput mutant screening, and the study of human disease development as well as a future outlook on microbes for renewable energy.

Multi-Omics of Single Cells: Strategies and Applications.

Most genome-wide assays provide averages across large numbers of cells, but recent technological advances promise to overcome this limitation. Pioneering single-cell assays are now available for genome, epigenome, transcriptome, proteome, and metabolome profiling. Here, we describe how these different dimensions can be combined into multi-omics assays that provide comprehensive profiles of the same cell.

Organs-on-Chips: How Microsystems Technology Can Transform the Drug Development Process.

The drug development pipeline, once one of the most successful and lucrative commercial sectors in the United States, is now strained by a combination of factors: increased development costs, lengthy time lines, and the poor predictive power of preclinical studies, among others. These factors, in combination with the need to respond to newly evolving demands?including the trend toward personalized or precision medicine, rising rates for many chronic diseases, and continued threats from emerging infectious diseases?are placing extraordinary pressure on an already strained development process.

Expression of PAM50 Genes in Lung Cancer: Evidence that Interactions between Hormone Receptors and HER2/HER3 Contribute to Poor Outcome.

Non-small cell lung cancers (NSCLCs) frequently express estrogen receptor (ER) ß, and estrogen signaling is active in many lung tumors. We investigated the ability of genes contained in the prediction analysis of microarray 50 (PAM50) breast cancer risk predictor gene signature to provide prognostic information in NSCLC. Supervised principal component analysis of mRNA expression data was used to evaluate the ability of the PAM50 panel to provide prognostic information in a stage I NSCLC cohort, in an all-stage NSCLC cohort, and in The Cancer Genome Atlas data. Immunohistochemistry was used to determine status of ERß and other proteins in lung tumor tissue. Associations with prognosis were observed in the stage I cohort. Cross-validation identified seven genes that, when analyzed together, consistently showed survival associations. In pathway analysis, the seven-gene panel described one network containing the ER and progesterone receptor, as well as human epidermal growth factor receptor (HER)2/HER3 and neuregulin-1. NSCLC cases also showed a significant association between ERß and HER2 protein expression. Cases positive for HER2 expression were more likely to express HER3, and ERß-positive cases were less likely to be both HER2 and HER3 negative. Prognostic ability of genes in the PAM50 panel was verified in an ERß-positive cohort representing all NSCLC stages. In The Cancer Genome Atlas data sets, the PAM50 gene set was prognostic in both adenocarcinoma and squamous cell carcinoma, whereas the seven-gene panel was prognostic only in squamous cell carcinoma. Genes in the PAM50 panel, including those linking ER and HER2, identify lung cancer patients at risk for poor outcome, especially among ERß-positive cases and squamous cell carcinoma.

Recent advances and future applications of microfluidic live-cell microarrays.

Microfluidic live-cell microarrays show much promise as screening tools for biomedical research because they could shed light on key biological processes such as cell signaling and cell-to-cell and cell-to-substrate dynamic responses. While miniaturization reduces the need for expensive clinical grade reagents, the integration of functional components including micropumps, biosensors, actuators, mixers and gradient generators results in improved assay reliability, reproducibility and well-defined cell culture conditions. The present review addresses recent technological advances in microfluidic live-cell microarray technology with a special focus on the applications of microfluidic single-cell, multi-cell and 3D cell microarrays.

Toward a mechanism-based in vitro safety test for pertussis toxin.

Pertussis vaccines are routinely administered to infants to protect them from whooping cough. Still, an adequate safety test for pertussis toxin (PT), one of the main antigens in these vaccines, is not available. The histamine sensitization test is currently the only assay accepted by regulatory authorities to test for the absence of active PT in vaccines. This is however, a lethal animal test with poor reproducibility. In addition, it is not clear whether the assumed underlying mechanism, i.e., ADP-ribosylation of G proteins, is the only effect that should be considered in safety evaluation of PT. The in vitro safety test for PT that we developed is based on the clinical effects of PT in humans. For this, human cell lines were chosen based on the cell types involved in the clinical effects of PT. These cell lines were exposed to PT and analyzed by microarray. In this review, we discuss the clinical effects of PT and the mechanisms that underlie them. The approach taken may provide as an example for other situations in which an in vitro assay based on clinical effects in humans is required.

High-throughput cellular microarray platforms: applications in drug discovery, toxicology and stem cell research.

Cellular microarrays are powerful experimental tools for high-throughput screening of large numbers of test samples. Miniaturization increases assay throughput while reducing reagent consumption and the number of cells required, making these systems attractive for a wide range of assays in drug discovery, toxicology, stem cell research and potentially therapy. Here, we provide an overview of the emerging technologies that can be used to generate cellular microarrays, and we highlight recent significant advances in the field. This emerging and multidisciplinary approach offers new opportunities for the design and control of stem cells in tissue engineering and cellular therapies and promises to expedite drug discovery in the biotechnology and pharmaceutical industries.

Tissue Microarray: A rapidly evolving diagnostic and research tool.

Tissue microarray is a recent innovation in the field of pathology. A microarray contains many small representative tissue samples from hundreds of different cases assembled on a single histologic slide, and therefore allows high throughput analysis of multiple specimens at the same time. Tissue microarrays are paraffin blocks produced by extracting cylindrical tissue cores from different paraffin donor blocks and re-embedding these into a single recipient (microarray) block at defined array coordinates. Using this technique, up to 1000 or more tissue samples can be arrayed into a single paraffin block. It can permit simultaneous analysis of molecular targets at the DNA, mRNA, and protein levels under identical, standardized conditions on a single glass slide, and also provide maximal preservation and use of limited and irreplaceable archival tissue samples. This versatile technique, in which data analysis is automated, facilitates retrospective and prospective human tissue studies. It is a practical and effective tool for high-throughput molecular analysis of tissues that is helping to identify new diagnostic and prognostic markers and targets in human cancers, and has a range of potential applications in basic research, prognostic oncology and drug discovery. This article summarizes the technical aspects of tissue microarray construction and sectioning, advantages, application, and limitations.

Tissue microarray: a simple technology that has revolutionized research in pathology.

Tissue microarray (TMA) technology is a high-throughput research tool, which has greatly facilitated and accelerated tissue analyses by in-situ technologies. TMAs are amenable to every research method that can be applied on the standard whole sections at enhanced speed. It plays a central role in target verification of results from cDNA arrays, expression profiling of tumors and tissues, and is proving to be a powerful platform for proteomic research. In this review article, primarily meant for students of pathology and oncology, we briefly discuss its basic methodology, applications and merits and limitations.

Molecular information obtained from radiobiological tissue archives: achievements of the past and visions of the future.

Radiobiological archives have not been overwhelmed by applications to use their stored tissue materials, in part because of lack of technologies to conduct quantitative analysis of the tissues. Over the last decade, advances in methodology have made it possible to routinely extract both DNA and RNA from archival materials. The quantitative analysis of gene expression by reverse transcription real-time PCR (QRT-PCR), and of gene copy number by array-based CGH (aCGH), are now firmly established methods for the study of tissue samples stored as paraffin blocks. More recent developments in proteomic technology have enabled the extraction of proteins from formalin-fixed paraffin-embedded (FFPE) tissue samples. These protein extracts have been used to produce quantitative data by Western blotting and even to identify proteins through LC/MS analysis. The development of applications using gel-based proteomics (2D/MS) is still a future challenge. This report gives an overview of the methodology already applicable on FFPE tissue, as well as the novel technologies to be used in the future research. Our goal is to collect existing animal and human tissue samples for use by the radiation biology community, to test new technologies for preparation of material from tissue samples, and to actively pursue materials arising from ongoing research.

Protein microchips in biomedicine and biomarker discovery.

Protein microarray technology is of high recent interest, especially for generating confirmatory and complementary information for transcriptomic studies. In this paper, the advantages, technical limitations, main application fields, and some early results of protein microarrays are reviewed. Today protein microchip technology is mostly available in the form of printed glass slides, bioaffinity surfaces, and tissue microarray (TMA)-based techniques. The advantages of glass slide-based microchips are the simplicity of their application and their relatively low cost. Affinity surface-based protein chip techniques are applicable to minute amounts of starting material (< 1 microg), but interrogation of these chips requires expensive instrumentation, such as mass spectrometers. TMAs are useful for parallel testing of antibody specificities on a broad range of histological specimens in a single slide. Protein microarrays have been successfully implemented for serum tumor marker profiling, cell physiology studies, and mRNA expression study verification. Some of the bottlenecks of the technology are protein instability, problems with nonspecific interactions, and the lack of amplification techniques to generate sufficient amounts of the lower abundance proteins. In spite of the current difficulties, protein microchips are envisioned to be available for routine biomedical and diagnostic applications provided that the ongoing technological developments are successful in improving sensitivity, specificity, and reducing costs.

Contribution of DNA and tissue microarray technology to the identification and validation of biomarkers and personalised medicine in breast cancer.

Completion of the human genome project has revolutionised translational medicine. High-throughput technology now permits investigators to systematically interrogate the genome, transcriptome, proteome and metabolome. It is expected that these advances will eventually be translated into new more sensitive diagnostic tests and less toxic therapeutics. A major shift is expected in clinical oncology over the next few decades as we start to move away from currently practiced, population-based approaches to personalised medicine. In this emerging approach, the molecular and pathophysiological characteristics of an individual patient and tumour will be measured and tailored therapeutic regimens will be administered based on these profiles. One of the key steps in this process will be the identification and validation of biomarkers. Whilst great advances have been made in the discovery of putative biomarkers, disappointingly few have been translated into clinically applicable assays. It is widely believed that this is due to a lack of well-designed, thorough validation studies. Here, we review the role of DNA microarrays and tissue microarrays in the validation of biomarkers in breast cancer, with emphasis on their potential application to determine mode of personalised therapy in the future.

Dr. David Rimm is interviewed by Feras Akbik.

Dr. David Rimm, MD PhD, is a professor of Pathology at the Yale University School of Medicine specializing in developing quantitative, diagnostic techniques. His lab recently engineered a fluorescence-based algorithm, Automated Quantitative Analysis (AQUA), to analyze tissue microarrays in the hope of moving toward personalized medicine and diagnoses.

Past, present, and future of high content screening and the field of cellomics.

High content screening (HCS) was created in 1996 to offer a new platform that could be used to permit relatively high-throughput screening of cells, in which each cell in an array would be analyzed at a sub-cellular resolution using multicolored, fluorescence-based reagents for both specificity and sensitivity. We developed HCS with the perspective of the history of the development of the automated DNA sequencers that revolutionized the field of genomics. Furthermore, HCS was based on a history of important developments in modern cytology. HCS integrates the instrumentation, application software, reagents, sample preparation, and informatics/bioinformatics required to rapidly flow from producing data, generating information, and ultimately creating new cellular knowledge. The HCS platform is beginning to have an important impact on early drug discovery, basic research in systems cell biology, and is expected to play a role in personalized medicine.

Caged substrates applied to high content screening: an introduction with an eye to the future.

The use of photoremovable protecting groups in biology affords the end user high temporal, spatial, and concentration control of reagents and substrates. High content screening and other large-scale biology applications would benefit greatly from these advantages. Herein, we report progress in this field by highlighting the recent development of controllable siRNA (csiRNA), which is a dormant siRNA that can be activated using 365 nm light. Two different experimental designs are described to highlight the temporal and concentration variables that can be controlled. First, the RNAi process is activated at two timepoints, 24- and 48-h post-transfection, to demonstrate that the action of csiRNA does not begin until activated. Second, increasing light dosage exposure to cells transfected with csiRNA that controls the concentration of active siRNA molecules. All experiments are conducted in a 96-well format with light delivered through the UCOM device.

Reverse-phase protein microarrays for tissue-based analysis.

The deciphering of the human genome has elucidated our biological structural design and has generated insights into disease development and pathogenesis. At the same time, knowledge of genetic changes during disease processes has demonstrated the need to move beyond genomics towards proteomics and a systems biology approach to science. Analyzing the proteome comprises more than just a numeration of proteins. In fact, it characterizes proteins within cells in the context of their functional status and interactions in their physiological micro- and macroenvironments. As dysregulated signaling often underpins most human diseases, an overarching goal of proteomics is to profile the working state of signaling pathways, to develop 'circuit maps' of normal and diseased protein networks and identify hyperactive, defective or inoperable transduction pathways. Reverse-phase protein microarrays represent a new technology that can generate a multiplex readout of dozens of phosphorylated events simultaneously to profile the state of a signaling pathway target even after the cell is lyzed and the contents denatured.