Perspectives in tissue microarrays

Tissue microarrays (TMAs) are means of combining tens to hundreds of specimens of tissue onto a single slide for analysis at one time. TMAs are most frequently constructed from paraffin embedded tissue; however, they can be constructed from frozen tissue. The construction of TMAs is flexible, meeting the focused needs of the investigator. A TMA slide can be processed like an ordinary tissue section, and used for histochemical, immunohistochemical staining or in situ hybridization. Combined with automated new image analysis systems, TMAs are a powerful molecular profiling tool. By confirming the findings of microarray experiments or protein arrays, TMAs can be applied systematically to global cellular network analysis within tissue cell. TMAs are commonly used to confirm the results of expression microarrays as well as in the development of diagnostic and prognostics markers for clinical applications. This review will cover recent advancements in technology for the construction and use of TMAs. Because TMAs can be constructed from archival paraffin embedded tissue, they open up the vast archive of patient samples and make them accessible for medical research. TMAs play an ever increasing role in translational medicine, bridging the chasm of discovery at the research bench to the demonstration of clinical utility prior to implementation in patient care.     

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Investigation of the enantioselectivity of tetramethylammonium‐lactobionate chiral ionic liquid based dual selector systems toward basic drugs in capillary electrophoresis

Recently, chiral ionic liquids (CILs) have received increasing interest in chiral separation by CE. Nevertheless, the lack of deep perception of the specific mechanism about CILs in CE for enantioseparation still perplexes a legion of researchers, despite the strenuous efforts. In this paper, a lactobionic acid based ionic liquid, tetramethylammonium‐lactobionate (TMA‐LA) was applied for the first time in CE to establish dual selector system with clindamycin phosphate (CP) for enantiomeric separation. Compared to single CP system or single TMA‐LA system significantly improved separations of seven tested rameric drugs (propranolol, nefopam, citalopram, chlorphenamine, metoprolol, bisoprolol, and esmolol) were observed in the dual selector systems. Several crucial parameters such as type and proportion of organic modifier, buffer composition and pH, and concentration of TMA‐LA/CP were systematically investigated to achieve satisfied enantioseparation. Meanwhile, molecular modeling was applied to demonstrate the chiral recognition mechanism of the TMA‐LA/CP dual‐selector separation system using the molecular docking software Autodock, which well supported the experimental results. The existence of TMA‐LA/CP complex may give rise to a higher discriminatory ability against the enantiomers, indicating the reason of improved separation in TMA‐LA/CP system. All the influence factors evaluated by means of Statistical Product and Service Solutions (SPSS) to research the influences on the chiral separation system.     

Gene selection from microarray data for cancer classification--a machine learning approach

A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in the classification of cancers. Cancer microarray data normally contains a small number of samples which have a large number of gene expression levels as features. To select relevant genes involved in different types of cancer remains a challenge. In order to extract useful gene information from cancer microarray data and reduce dimensionality, feature selection algorithms were systematically investigated in this study. Using a correlation-based feature selector combined with machine learning algorithms such as decision trees, nave Bayes and support vector machines, we show that classification performance at least as good as published results can be obtained on acute leukemia and diffuse large B-cell lymphoma microarray data sets. We also demonstrate that a combined use of different classification and feature selection approaches makes it possible to select relevant genes with high confidence. This is also the first paper which discusses both computational and biological evidence for the involvement of zyxin in leukaemogenesis.     

Rapid screening assay of trimethylaminuria in urine with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Trimethyamine (TMA) and trimethylamine N-oxide (TMAO) are the most important urine parameters for diagnosing and monitoring trimethylaminuria. A rapid, simple, and specific method based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) was developed to determine the presence of TMA and TMAO in urine samples from patients with trimethylaminuria. Formation of the quaternary tetramethylamino iodide by derivatization of TMA with methyl iodide allows measurement of TMA by MALDI-TOFMS. The method is repeatable and reproducible, with coefficients of variance (CVs)<3%. This new method was used for direct determination of TMA and TMAO in urine specimens obtained from normal children and patients. The proposed method allows for rapid and reliable measurements of TMA and TMAO in urine specimens from patients affected by trimethylaminuria.     

Characterization of polymeric dielectric insulation by thermomechanical analysis

Use of a thermomechanical analyzer, TMA, affords a rapid, precise method for determining linear expansion coefficients and linear expansivities of cross-linked polymeric insulation material. Completed cable samples were dissassembled and insulation specimens were cut longitudinally and examined with repeated temperature cycling: ethylene—propylene copolymer rubbers and filled and unfilled crosslinked polyethylenes. The TMA results indicated that all specimes were oriented, likely incurred from extrusion processing. The facility of TMA for investigating potential anisotropic behavior from prior orientation is illustrated by examples of TMA measurements on radial specimens, similarly free of mechanical constraints.     

Towards single-spot multianalyte molecular beacon biosensors

The separate developments of microarray patterning of DNA oligonucleotides, and of DNA hairpins as sensitive probes for oligonucleotide identification in solution, have had a tremendous impact on basic biological research and clinical applications. Herein, we will discuss several successful efforts to develop oligonucleotide sensors based on the surface immobilization of functionalized DNA hairpins. We also will discuss the development of prototypical single-spot multianalyte “Molecular Beacon” biosensors. Importantly, we show that organic fluorophores will likely be inadequate in moving this technology forward and new approaches, such as the use of nanotechnology, will be needed.     

Expression profiling in cancer using cDNA microarrays

Currently there are over 1,000,000 human expressed sequence tag (EST) sequences available on the public database, representing perhaps 50-90% of all human genes. The cDNA microarray technique is a recently developed tool that exploits this wealth of information for the analysis of gene expression. In this method, DNA probes representing cDNA clones are arrayed onto a glass slide and interrogated with fluorescently labeled cDNA targets. The power of the technology is the ability to perform a genome-wide expression profile of thousands of genes in one experiment. In our review we describe the principles of the microarray technology as applied to cancer research, summarize the literature on its use so far, and speculate on the future application of this powerful technique.     

Feature-size limitations of microarray technology - a critical review

The appeal of microarray technology is the possibility of large-scale parallel determination of a variety of variables simultaneously. Hence, microarray technologies attract the interest of both the scientific and business worlds alike. High-throughput screening has been the major focus of the utilization of microarray technologies in recent years, and has provided the strong driving force for developments in this field. DNA chip and biochip technologies have been developed as a consequence of worldwide activity in genome research. This review focuses on microarray-based analysis and emphasizes some of its principal constraints, especially detection limits.     

A novel aptamer-based histochemistry assay for specific diagnosis of clinical breast cancer tissues

Pathological detection using immunohistochemistry (IHC) has become an indispensable process in the diagnosis confirmation of various cancers. However, the production of monoclonal antibodies is always very complex, expensive and time-consuming, and the batch differences are significant due to the corporeity and health statuses of animals may be different. In this work, an aptamer-based histochemistry (aptahistochemistry) assay was developed using a DNA aptamer for specific diagnosis of clinical breast cancer tissue sections. This aptahistochemistry assay can specifically distinguish Luminal A breast cancer molecular subtype from Luminal B (HER2+), HER2-enriched, and triple-negative breast cancer molecular subtypes, as well as para-carcinoma tissue, mastitis tissue and normal breast tissue. The accuracy of this aptahistochemistry assay for the diagnosis of Luminal A breast cancer was as high as 80%, which showed a great potential for clinical pathological diagnosis applications.     

Multiplexed immunoassays for the analysis of breast cancer biopsies

Within the last decade, protein microarray technology has been successfully used for the simultaneous quantification of target proteins from minimal amounts of samples in basic and applied proteome research. The robustness and appropriate sensitivity of these miniaturized assays have been demonstrated and thus the transfer to routine and high-throughput applications is now possible. In this study, multiplexed bead-based sandwich immunoassays were used to determine the concentrations of 54 protein analytes, including HER 2 and the estrogen receptor, from ultrasound-guided large-core needle biopsies (LCNBs) from breast cancer patients. Expression levels for HER 2, estrogen receptors and progesterone receptors were also assessed by immunohistochemical routine staining, performed in the clinic on corresponding biopsy samples. The high concordance of the data sets generated with the bead-based protein arrays and by conventional immunohistochemical assessment of HER 2 and the estrogen receptor expressed by breast cancer cells present in the biopsies was demonstrated.     

A renewable, chemoselective, and quantitative ligand density microarray for the study of biospecific interactions

Novel renewable microarray technology has been developed to immobilize and release carbohydrates and proteins from self-assembled monolayers (SAMs) of electroactive quinone-terminated alkanethiolates on gold surfaces. This method may be applied to a variety of research fields for use in biosensor technology and the generation of renewable and tailored microarrays for biospecific cell-based assays.     

Porous silicon surfaces: a candidate substrate for reverse protein arrays in cancer biomarker detection

This paper introduces a new substrate for reverse-phase protein microarray applications based on macroporous silicon. A key feature of the microarray substrate is the vastly surface enlarging properties of the porous silicon, which simultaneously offers highly confined microarray spots. The proof of principle of the reverse array concept was demonstrated in the detection of different levels of cyclin E, a possible cancer biomarker candidate which regulates G1-S transition and correlates with poor prognosis in different types of human cancers. The substrate properties were studied performing analysis of total cyclin E expression in human colon cancer cell lines Hct116 and SW480. The absence of unspecific binding and good microarray quality was demonstrated. In order to verify the performance of the 3-D textured macroporous surface for complex biological samples, lysates of the human tissue spiked to different levels with cell extract overproducing cyclin E (Hct116) were arrayed on the chip surface. The samples were spotted in a noncontact mode in 100 pL droplets with spots sizes ranged between 50 and 70 mum and spot-to-spot center distances 100 mum, allowing microarray spot densities up to 14 000 spots per cm(2). The different sample types of increasing complexities did not have any impact on the spot intensities recorded and the protein spots showed good homogeneity and reproducibility over the recorded microarrays. The data demonstrate the potential use of macroporous silicon as a substrate for quantitative determination of a cancer biomarker cyclin E in tissue lysates.     

Studies of structures of poly-ε-caprolactam/montmorillonite nanocomposite: Part 1. Tests of compression moulded specimens

A poly-ε-caprolactam (PA6) taken as a reference and its nanocomposite (PNC) containing 1.6 wt.% of montmorillonite were examined. The specimens as discs were prepared by compression moulding at 235 °C and 70 MPa. Using the novel version of TMA, in the PA6 and PNC specimens, within the temperature range from −100 to 250 °C, a semi-crystalline structure with anisotropy of distribution of the more ordered (crystalline?) portion was found in the surface layer up to 0.5 mm thick. The amorphous regions have differed in a state of order (different transition temperatures) and related compactness. The free volume fraction in amorphous regions determined in machine direction (normal to the surface) is increased when in transverse direction is reduced; simultaneously molecular weights of polymer chains between junctions were increased by incorporation of the nanofiller.     

Protein microarrays and multiplexed sandwich immunoassays: what beats the beads?

Protein microarray technology allows the simultaneous determination of a large variety of parameters from a minute amount of sample within a single experiment. Assay systems based on this technology are currently applied for the identification, quantitation and functional analysis of proteins. Protein microarray technology is of major interest for proteomic research in basic and applied biology as well as for diagnostic applications. Miniaturized and parallelized assay systems have reached adequate sensitivity and hence have the potential to replace singleplex analysis systems. However, robustness and automation needs to be demonstrated before this technology will finally prove suitable for high-throughput applications. Miniaturized and parallelized sandwich immunoassays are the most advanced assays formats among the different protein microarray applications. Multiplexed sandwich immunoassays can be used for the identification of biomarkers and the validation of potential target molecules. In this review an overview will be given on the current stage of protein microarray technology with a special focus on miniaturized multiplexed sandwich immunoassays.     

Development of a microfluidic device for the maintenance and interrogation of viable tissue biopsies

A microfluidic based experimental methodology has been developed that offers a biomimetic microenvironment in which pseudo in vivo tissue studies can be carried out under in vitro conditions. Using this innovative technique, which utilizes the inherent advantages of microfluidic technology, liver tissue has been kept in a viable and functional state for over 70 h during which time on-chip cell lysis has been repeatedly performed. Tissue samples were also disaggregated in situ on-chip into individual primary cells, using a collagenase digestion procedure, enabling further cell analysis to be carried out off-line. It is anticipated that this methodology will have a wide impact on biological and clinical research in fields such as cancer prognosis and treatment, drug development and toxicity, as well as enabling better fundamental research into tissue/cell processes.     

Multi-class tumor classification by discriminant partial least squares using microarray gene expression data and assessment of classification models

High-throughput DNA microarray provides an effective approach to the monitoring of expression levels of thousands of genes in a sample simultaneously. One promising application of this technology is the molecular diagnostics of cancer, e.g. to distinguish normal tissue from tumor or to classify tumors into different types or subtypes. One problem arising from the use of microarray data is how to analyze the high-dimensional gene expression data, typically with thousands of variables (genes) and much fewer observations (samples). There is a need to develop reliable classification methods to make full use of microarray data and to evaluate accurately the predictive ability and reliability of such derived models. In this paper, discriminant partial least squares was used to classify the different types of human tumors using four microarray datasets and showed good prediction performance. Four different cross-validation procedures (leave-one-out versus leave-half-out; incomplete versus full) were used to evaluate the classification model. Our results indicate that discriminant partial least squares using leave-half-out cross-validation provides a more realistic estimate of the predictive ability of a classification model, which may be overestimated by some of the cross-validation procedures, and the information obtained from different cross-validation procedures can be used to evaluate the reliability of the classification model.     

Development of highly fluorescent silica nanoparticles chemically doped with organic dye for sensitive DNA microarray detection

Increasing the sensitivity in DNA microarray hybridization can significantly enhance the capability of microarray technology for a wide range of research and clinical diagnostic applications, especially for those with limited sample biomass. To address this issue, using reverse microemulsion method and surface chemistry, a novel class of homogenous, photostable, highly fluorescent streptavidin-functionalized silica nanoparticles was developed, in which Alexa Fluor 647 (AF647) molecules were covalently embedded. The coating of bovine serum albumin on the resultant fluorescent particles can greatly eliminate nonspecific background signal interference. The thus-synthesized fluorescent nanoparticles can specifically recognize biotin-labeled target DNA hybridized to the microarray via streptavidin–biotin interaction. The response of this DNA microarray technology exhibited a linear range within 0.2 to 10 pM complementary DNA and limit of detection of 0.1 pM, enhancing microarray hybridization sensitivity over tenfold. This promising technology may be potentially applied to other binding events such as specific interactions between proteins.     

Lectin microarrays: a powerful tool for glycan-based biomarker discovery

Cell surfaces, especially mammalian cell surfaces, are heavily coated with complex poly- and oligosaccharides, and these glycans have been implicated in many functions, such as cell-to-cell communication, host-pathogen interactions and cell matrix interactions. Not surprisingly then, the aberrations of glycosylation are usually indicative of the onset of specific diseases, such as cancer. Therefore, glycans are expected to serve as important biomarkers for disease diagnosis and/or prognosis. Recent development of the lectin microarray technology has allowed researchers to profile the glycans in complex biological samples in a high throughput fashion. This relatively new tool is highly suitable for both live cell and cell lysate analyses and has the potential for rapid discovery of glycan-based biomarkers. In this review, we will focus on the basic concepts and the latest advances of lectin microarray technology. We will also emphasize the application of lectin microarrays for biomarker discovery, and then discuss the challenges faced by this technology and potential future directions. Based on the tremendous progress already achieved, it seems apparent that lectin microarrays will soon become an indispensible tool for glycosylation biomarker discovery.